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Purpose: Radiation-induced lymphopenia (RIL) is common among patients undergoing radiation therapy (RT)' Severe RIL has been linked to adverse outcomes. The severity and risk of RIL can be predicted from baseline clinical characteristics and dosimetric parameters. However, dosimetric parameters, e.g. dose-volume (DV) indices, are highly correlated with one another and are only weakly associated with RIL. Here we introduce the novel concept of "composite dosimetric score" (CDS) as the index that condenses the dose distribution in immune tissues of interest to study the dosimetric dependence of RIL. We derived an improved multivariate classification scheme for risk of grade 4 RIL (G4RIL), based on this novel RT dosimetric feature, for patients receiving chemo RT for esophageal cancer., Methods and Materials: DV indices were extracted for 734 patients who received chemo RT for biopsy-proven esophageal cancer. Nonnegative matrix factorization was used to project the DV indices of lung, heart, and spleen into a single CDS; XGBoost was employed to explore significant interactions among predictors; and logistic regression was applied to combine the resultant CDS with baseline clinical factors and interaction terms to facilitate individualized prediction of immunotoxicity. Five-fold cross-validation was applied to evaluate the model performance., Results: The CDS for selected immune organs at risk (ie, heart, lung, and spleen) (OR 1.791; 95 CI [1.350, 2.377]) was a statistically significant risk determinant for G4RIL. Pearson correlation coefficients for CDS versus G4RIL risk for individual immune organs at risk were greater than any single DV indicx. Personalized prediction of G4RIL based on CDS and 4 clinical risk factors yielded an area under the curve value of 0.78. Interaction between age and CDS revealed that G4RIL risk increased more sharply with increasing CDS for patients aged ≥65 years., Conclusions: Risk of immunotoxicity for patients undergoing chemo RT for esophageal cancer can be predicted by CDS. The CDS concept can be extended to immunotoxicity in other cancer types and in dose-response models currently based on DV indices. Personalized treatment planning should leverage composite dosimetric scoring methods rather than using individual or subsets of DV indices., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: Radiation-induced lymphopenia is a common immune toxicity that adversely impacts treatment outcomes. We report here our approach to translate a deep-learning (DL) model developed to predict severe lymphopenia risk among esophageal cancer into a strategy for incorporating the immune system as an organ-at-risk (iOAR) to mitigate the risk., Materials and Methods: We conducted "virtual clinical trials" utilizing retrospective data for 10 intensity-modulated radiation therapy (IMRT) and 10 passively-scattered proton therapy (PSPT) esophageal cancer patients. For each patient, additional treatment plans of the modality other than the original were created employing standard-of-care (SOC) dose constraints. Predicted values of absolute lymphocyte count (ALC) nadir for all plans were estimated using a previously-developed DL model. The model also yielded the relative magnitudes of contributions of iOARs dosimetric factors to ALC nadir, which were used to compute iOARs dose-volume constraints, which were incorporated into optimization criteria to produce "IMRT-enhanced" and "intensity-modulated proton therapy (IMPT)-enhanced" plans., Results: Model-predicted ALC nadir for the original IMRT (IMRT-SOC) and PSPT plans agreed well with actual values. IMPT-SOC showed greater immune sparing vs IMRT and PSPT. The average mean body doses were 13.10 Gy vs 7.62 Gy for IMRT-SOC vs IMPT-SOC for patients treated with IMRT-SOC; and 8.08 Gy vs 6.68 Gy for PSPT vs IMPT-SOC for patients treated with PSPT. For IMRT patients, the average predicted ALC nadir of IMRT-SOC, IMRT-enhanced, IMPT-SOC, and IMPT-enhanced was 281, 327, 351, and 392 cells/µL, respectively. For PSPT patients, the average predicted ALC nadir of PSPT, IMPT-SOC, and IMPT-enhanced was 258, 316, and 350 cells/µL, respectively. Enhanced plans achieved higher predicted ALC nadir, with an average improvement of 40.8 cells/µL (20.6%)., Conclusion: The proposed DL model-guided strategy to incorporate the immune system as iOAR in IMRT and IMPT optimization has the potential for radiation-induced lymphopenia mitigation. A prospective clinical trial is planned., Competing Interests: Wenhua Cao reports financial support was provided by the National Institutes of Health. Radhe Mohan reports financial support was provided by the National Institutes of Health. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Purpose: Radiation-induced lymphopenia (RIL) is common during chemoradiation therapy. Severe lymphopenia is associated with reduced survival. Proton beam therapy (PBT), with its substantially more compact dose distributions, spares circulating lymphocytes and immune organs at risk to a greater extent than photon therapy. Recent studies comparing PBT to photon radiation therapy, specifically intensity-modulated radiation therapy (IMRT) for esophageal cancer (EC), showed that the incidence of grade 4 RIL (G4RIL) is significantly reduced among patients receiving PBT for EC. However, whether the extent of this reduction has a direct causative link with improved survival is unknown. This study applies causal mediation analysis to answer this question., Methods and Materials: We retrospectively assessed 734 patients treated with concurrent chemoradiation therapy for biopsy-proven EC from 2004 to 2017. To address the potential for bias in the choice of radiation modality, propensity score analysis was used to evaluate and reduce imbalances between the PBT and IMRT cohorts. Causal mediation analysis was applied to decompose the total effect of radiation modality on overall survival (OS) into indirect (mediated through G4RIL) and direct effects., Results: We found that PBT was associated with a significantly lower incidence of G4RIL and prolonged OS compared with IMRT (odds ratio, 0.41; 95% CI, 0.28-0.60; P < .001). In the propensity-matched cohort of 506 patients (253 PBT, 253 IMRT), G4RIL risk reduction with PBT versus IMRT translated into a 5% reduction in the relative rate of death ( P = .032). Mediation of G4RIL explained ∼14.5% of the difference in OS., Conclusions: G4RIL was found to mediate survival; however, a statistically significant direct effect of PBT on survival was not observed. In other words, the statistical significance of survival benefit from protons over photons in this EC cohort was lost in the absence of G4RIL risk reduction., Competing Interests: Steven H. Lin discloses grant funding from Beyond Spring Pharmaceuticals, Nektar Therapeutics, STCube Pharmaceuticals, and IntraOp Corporation, serving on the advisory board for Beyond Spring Pharmaceuticals, STCube Pharmaceuticals, and AstraZeneca, and being a consultant for XRAD Therapeutics. Brian P. Hobbs discloses serving on the advisory board for CSL Behring and Telperian. All other authors: None., (© 2024 The Authors.)

The tumor microenvironment (TME) plays a fundamental role in tumorigenesis, tumor progression, and anti-cancer immunity potential of emerging cancer therapeutics. Understanding inter-patient TME heterogeneity, however, remains a challenge to efficient drug development. This article applies recent advances in machine learning (ML) for survival analysis to a retrospective study of NSCLC patients who received definitive surgical resection and immune pathology following surgery. ML methods are compared for their effectiveness in identifying prognostic subtypes. Six survival models, including Cox regression and five survival machine learning methods, were calibrated and applied to predict survival for NSCLC patients based on PD-L1 expression, CD3 expression, and ten baseline patient characteristics. Prognostic subregions of the biomarker space are delineated for each method using synthetic patient data augmentation and compared between models for overall survival concordance. A total of 423 NSCLC patients (46% female; median age [inter quantile range]: 67 [60-73]) treated with definite surgical resection were included in the study. And 219 (52%) patients experienced events during the observation period consisting of a maximum follow-up of 10 years and median follow up 78 months. The random survival forest (RSF) achieved the highest predictive accuracy, with a C-index of 0.84. The resultant biomarker subtypes demonstrate that patients with high PD-L1 expression combined with low CD3 counts experience higher risk of death within five-years of surgical resection., (© 2024. The Author(s).)

Purpose: Evidence suggests that proton-beam therapy (PBT) results in less toxicity and postoperative complications compared to photon-based radiotherapy in patients who receive chemoradiotherapy followed by esophagectomy for cancer. Ninety-day mortality (90DM) is an important measure of the postoperative (nononcologic) outcome as proxy of quality-of-care. We hypothesize that PBT could reduce 90DM compared to photon-based radiotherapy., Materials and Methods: From a single-center retrospective database patients treated with chemoradiotherapy before esophagectomy for cancer were selected (1998-2022). Univariable logistic regression was used to study the association of radiotherapy modality with 90DM. Three separate methods were applied to adjust for confounding bias, including multivariable logistic regression, propensity score matching, and inverse probability of treatment weighting. Stratified analysis for the age threshold that maximized the difference in 90DM (ie, ≥67 vs <67 years) was performed., Results: A total of 894 eligible patients were included and 90DM was 5/202 (2.5%) in the PBT versus 29/692 (4.2%) in the photon-based radiotherapy group ( P  = .262). After adjustment for age and tumor location, PBT versus photon-based radiotherapy was not significantly associated with 90DM ( P  = .491). The 90DM was not significantly different for PBT versus photon-based radiotherapy in the propensity score matching ( P  = .379) and inverse probability of treatment weighting cohort ( P  = .426). The stratified analysis revealed that in patients aged ≥67 years, PBT was associated with decreased 90DM (1.3% vs 8.8%; P  = .026). Higher age significantly increased 90DM risk within the photon-based radiotherapy (8.8% vs 2.7%; P  = .001), but not within the PBT group (1.3% vs 3.2%; P  = .651)., Conclusion: No statistically significant difference was observed in postoperative 90DM after esophagectomy for cancer between PBT and photon-based neoadjuvant chemoradiotherapy. However, among older patients a signal was observed that PBT may reduce 90DM risk., (© 2024 The Author(s).)

Purpose: Lymphocytes play an important role in antitumor immunity; however, they are also especially vulnerable to depletion during chemoradiation therapy (CRT). The purpose of this study was to compare the incidence of grade 4 lymphopenia (G4L) between proton beam therapy (PBT) and intensity modulated photon radiation therapy (IMRT) in patients with esophageal cancer treated with CRT in a completed randomized trial and to ascertain patient heterogeneity to G4L risk based on treatment and established prognostic factors., Methods and Materials: Between April 2012 and March 2019, a single-institution, open-label, nonblinded, phase 2 randomized trial (NCT01512589) was conducted at the University of Texas MD Anderson Cancer Center. Patients were randomly assigned to IMRT or PBT, either definitively or preoperatively. This secondary analysis of the randomized trial was G4L during concurrent CRT according to Common Terminology Criteria for Adverse Events version 5.0., Results: Among 105 patients evaluable for analysis, 44 patients (42%) experienced G4L at a median of 28 days after the start date of concurrent CRT. Induction chemotherapy (P = .003), baseline absolute lymphocyte count (P < .001), radiation therapy modality (P = .002), and planning treatment volume (P = .033) were found to be significantly associated with G4L. Multivariate classification analysis partitioned patients into 5 subgroups for whom the incidence of G4L was observed in 0%, 14%, 35%, 70%, and 100% of patients. The benefit of PBT over IMRT was most pronounced in patients with an intermediate baseline absolute lymphocyte count and large planning treatment volume (P = .011)., Conclusions: This is the first prospective evidence that limiting dose scatter by PBT significantly reduced the incidence of G4L, especially in the intermediate-risk patients. The implication of this immune-sparing effect of PBT, especially in the context of standard adjuvant immunotherapy, needs further examination in the current phase 3 randomized trials., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: ERK5 (extracellular signal-regulated kinase 5) is a dual kinase transcription factor containing an N-terminal kinase domain and a C-terminal transcriptional activation domain. Many ERK5 kinase inhibitors have been developed and tested to treat cancer and inflammatory diseases. However, recent data have raised questions about the role of the catalytic activity of ERK5 in proliferation and inflammation. We aimed to investigate how ERK5 reprograms myeloid cells to the proinflammatory senescent phenotype, subsequently leading to atherosclerosis., Methods: A ERK5 S496A (dephosphorylation mimic) knock in (KI) mouse model was generated using CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat-associated 9), and atherosclerosis was characterized by hypercholesterolemia induction. The plaque phenotyping in homozygous ERK5 S496A KI and wild type (WT) mice was studied using imaging mass cytometry. Bone marrow-derived macrophages were isolated from hypercholesterolemic mice and characterized using RNA sequencing and functional in vitro approaches, including senescence, mitochondria reactive oxygen species, and inflammation assays, as well as by metabolic extracellular flux analysis., Results: We show that atherosclerosis was inhibited in ERK5 S496A KI mice. Furthermore, ERK5 S496 phosphorylation mediates both senescence-associated secretory phenotype and senescence-associated stemness by upregulating AHR (aryl hydrocarbon receptor) in plaque and bone marrow-derived macrophages isolated from hypercholesterolemic mice. We also discovered that ERK5 S496 phosphorylation could induce NRF2 (NFE2-related factor 2) SUMOylation at a novel K518 site to inhibit NRF2 transcriptional activity without altering ERK5 catalytic activity and mediates oxidized LDL (low-density lipoprotein)-induced senescence-associated secretory phenotype. Specific ERK5 kinase inhibitors (AX15836 and XMD8-92) also inhibited ERK5 S496 phosphorylation, suggesting the involvement of ERK5 S496 phosphorylation in the anti-inflammatory effects of these ERK5 kinase inhibitors., Conclusions: We discovered a novel mechanism by which the macrophage ERK5-NRF2 axis develops a unique senescence-associated secretory phenotype/stemness phenotype by upregulating AHR to engender atherogenesis. The finding of senescence-associated stemness phenotype provides a molecular explanation to resolve the paradox of senescence in proliferative plaque by permitting myeloid cells to escape the senescence-induced cell cycle arrest during atherosclerosis formation., Competing Interests: Disclosures S.H. Lin is an Advisory Board member of AstraZeneca, Beyond Spring Pharmaceuticals, and STCube Pharmaceuticals. The other authors report no conflicts.

Objective: CT perfusion (CTp) values are affected by CT scan acquisition duration (t acq ); their reproducibility is adversely affected by uncertainty in their measurement. The objectives were to assess the effects of t acq on CTp parameter values in metastases from renal cell carcinoma (mRCC) in thoracic and abdominal locations., Materials and Methods: 131 CTp evaluations in 53 patients with mRCC were retrospectively analyzed by distributed parameter modeling to yield tissue blood flow (BF), blood volume (BV), mean transit time (MTT), permeability (PS), and also hepatic arterial perfusion (HAP) and hepatic arterial fraction (HAF) for liver metastases and normal liver, with t acq from 25 to 590 s. Penalized piecewise polynomial regression (SPLINE) characterized functional relationships between CTp parameters and acquisition duration, t acq . Evidence for time-invariance was evaluated for each parameter at multiple time points by conducting inference on the fitted derivative to assess its proximity to zero as a function of acquisition time. Equivalence testing was implemented with three levels of confidence (low (20%), moderate (70%), high (95%))., Results: Systematic and non-systematic variability was observed for CTp parameter values with limited t acq . All parameters in all locations approached increasing stability with increasing t acq . PS, HAP and HAF required longer acquisition times than BF, BV and MTT to attain comparable levels of stability. Stabilization tended to require longer acquisition in liver than other tissues. t acq =380 s was required to obtain at least moderate level of confidence for all parameters and organs., Conclusion: Increasing t acq yields increasingly more stable CT perfusion parameters, and thereby better reproducibility., Competing Interests: CSN is a consultant to GE Healthcare. AGC was previously employed by GE Healthcare. NMT is a Scientific Advisor to Nektar Therapeutics; Pfizer, Oncorena; Eli Lilly, Eisai Medical Research, And Consultant to Bristol-Myers-Squibb; Pfizer; Nektar Therapeutics; Exelisis, Inc, Eisai Medical Research; Eli Lilly; Oncorena; Calithera Bioscience; Surface Oncology; Novartis, Ipsen; Merck Sharp & Dohme. BPH is a Scientific Advisor to Amgen, STCube, Bayer HealthCare Pharmaceuticals Inc., Presagia. And Consultant to Pfizer. YC, WW have no disclosures., (© 2023 The Author(s).)

Clinical cancer trials are designed to collect radiographic measurements of each patient's baseline and residual tumor burden at regular intervals over the course of study. For solid tumors, the extent of reduction in tumor size following treatment is used as a measure of a drug's antitumor activity. Statistical estimation of treatment efficacy routinely reduce the longitudinal assessment of tumor burden to a binary outcome describing the presence versus absence of an objective tumor response as defined by RECIST criteria. The objective response rate (ORR) is the predominate method for evaluating an experimental therapy in a single-arm trial. Additionally, ORR is routinely compared against a control therapy in phase III randomized controlled trials. The longitudinal assessments of tumor burden are seldom integrated into a formal statistical model, nor integrated into mediation analysis to characterize the relationships among treatment, residual tumor burden, and survival. This article presents a frameworkfor landmark mediation survival analyses devised to incorporate longitudinal assessment of tumor burden. R 2 effect-size measures are developed to quantify the survival treatment mediation effects using longitudinal predictors. Analyses are demonstrated with applications to two colorectal cancer trials. Survival prediction is compared in the presence versus absence of longitudinal analysis. Simulation studies elucidate settings wherein patterns of tumor burden dynamics require longitudinal analysis., Competing Interests: JZ is employed by Novartis. XJ and HX are employed by Amgen. BH reports Scientific Advisory for Telperian and Amgen outside the scope of submitted work. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhou, Jiang, Xia, Hobbs and Wei.)

Introduction: Efforts to develop biomarker-targeted anti-cancer therapies have progressed rapidly in recent years. With efforts to expedite regulatory reviews of promising therapies, several targeted cancer therapies have been granted accelerated approval on the basis of evidence acquired in single-arm phase II clinical trials. And yet, in the absence of randomization, patient prognosis for progression-free survival and overall survival may not have been studied under standard of care chemotherapies for emerging biomarker subpopulations prior to the submission of an accelerated approval application. Historical control rates used to design and evaluate emerging targeted therapies often arise as population averages, lacking specificity to the targeted genetic or immunophenotypic profile. Thus, historical trial results are inherently limited for inferring the potential "comparative efficacy" of novel targeted therapies. Consequently, randomization may be unavoidable in this setting. Innovations in design methodology are needed, however, to enable efficient implementation of randomized trials for agents that target biomarker subpopulations., Methods: This article proposes three randomized designs for early phase biomarker-guided oncology clinical trials. Each design utilizes the optimal efficiency predictive probability method to monitor multiple biomarker subpopulations for futility. Only designs with type I error between 0.05 and 0.1 and power of at least 0.8 were considered when selecting an optimal efficiency design from among the candidate designs formed by different combinations of posterior and predictive threshold. A simulation study motivated by the results reported in a recent clinical trial studying atezolizumab treatment in patients with locally advanced or metastatic urothelial carcinoma is used to evaluate the operating characteristics of the various designs., Results: Out of a maximum of 300 total patients, we find that the enrichment design has an average total sample size under the null of 101.0 and a total average sample size under the alternative of 218.0, as compared to 144.8 and 213.8 under the null and alternative, respectively, for the stratified control arm design. The pooled control arm design enrolled a total of 113.2 patients under the null and 159.6 under the alternative, out of a maximum of 200. These average sample sizes that are 23-48% smaller under the alternative and 47-64% smaller under the null, as compared to the realized sample size of 310 patients in the phase II study of atezolizumab., Discussion: Our findings suggest that potentially smaller phase II trials to those used in practice can be designed using randomization and futility stopping to efficiently obtain more information about both the treatment and control groups prior to phase III study., Competing Interests: BH declares advising/consulting for Amgen, Bayer HealthCare Pharmaceuticals Inc., Telperian, and STCube Pharmaceuticals. NP declares advising/consulting for AstraZeneca, Merck, Pfizer, Eli Lilly/LOXO, Genentech, BMS, Amgen, Mirati, Inivata, G1 Therapeutics, Viosera, Xencor, Janssen, Boehringer Ingelheim, and Sanofi-Genzyme. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zabor, Kaizer, Pennell and Hobbs.)

Advances in biology and immunology have elucidated genetic and immunologic origins of cancer. Innovations in sequencing technologies revealed that distinct cancer histologies shared common genetic and immune phenotypic traits. Pharmacologic developments made it possible to target these alterations, yielding novel classes of targeted agents whose therapeutic potential span multiple tumor types. Basket trials, one type of master protocol, emerged as a tool for evaluating biomarker-targeted therapies among multiple tumor histologies. Conventionally conducted within the phase II setting and designed to estimate high and durable objective responses, basket trials pose challenges to statistical design and interpretation of results. This article reviews basket trials implemented in oncology studies and discusses issues related to their statistical design and analysis.

Background: Hybrid controlled trials with real-world data (RWD), where the control arm is composed of both trial and real-world patients, could facilitate research when the feasibility of randomized controlled trials (RCTs) is challenging and single-arm trials would provide insufficient information., Methods: We propose a frequentist two-step borrowing method to construct hybrid control arms. We use parameters informed by a completed randomized trial in metastatic triple-negative breast cancer to simulate the operating characteristics of dynamic and static borrowing methods, highlighting key trade-offs and analytic decisions in the design of hybrid studies., Results: Simulated data were generated under varying residual-bias assumptions (no bias: HR RWD  = 1) and experimental treatment effects (target trial scenario: HR Exp  = 0.78). Under the target scenario with no residual bias, all borrowing methods achieved the desired 88% power, an improvement over the reference model (74% power) that does not borrow information externally. The effective number of external events tended to decrease with higher bias between RWD and RCT (i.e. HR RWD away from 1), and with weaker experimental treatment effects (i.e. HR Exp closer to 1). All dynamic borrowing methods illustrated (but not the static power prior) cap the maximum Type 1 error over the residual-bias range considered. Our two-step model achieved comparable results for power, type 1 error, and effective number of external events borrowed compared to other borrowing methodologies., Conclusion: By pairing high-quality external data with rigorous simulations, researchers have the potential to design hybrid controlled trials that better meet the needs of patients and drug development., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: At the time of the study, BDS, MDC, SSB, WKT, SS, MS report employment in Flatiron Health, Inc., and stock ownership in Roche. BPH reports research fundings from Amgen, scientific advisor role and stock ownership in Presagia. RAH reports grant funding from 10.13039/100004319Pfizer. JZ and WBC report employment in Roche/Genentech and stock ownership in Roche. DSH reports research/grant funding from 10.13039/100006483AbbVie, Adaptimmune, Aldi-Norte, 10.13039/100002429Amgen, Astra-Zeneca, 10.13039/100004326Bayer, BMS, 10.13039/501100002973Daiichi-Sankyo, 10.13039/501100003769Eisai, Fate Therapeutics, 10.13039/100004328Genentech, Genmab, 10.13039/100014584Ignyta, Infinity, Kite, Kyowa, Lilly, LOXO, 10.13039/100004334Merck, 10.13039/501100004628MedImmune, Mirati, miRNA, Molecular Templates, Mologen, NCI-CTEP, 10.13039/100004336Novartis, 10.13039/100004319Pfizer, 10.13039/100010293Seattle Genetics, Takeda, and Turning Point Therapeutics; travel and accommodation expenses from 10.13039/100004326Bayer, LOXO, miRNA, Genmab, 10.13039/100000043AACR, 10.13039/100006293ASCO, SITC; consulting or advisory roles with Alpha Insights, Acuta, 10.13039/100002429Amgen, Axiom, Adaptimmune, 10.13039/100004702Baxter, 10.13039/100004326Bayer, COG, Ecor1, 10.13039/100004328Genentech, GLG, Group H, Guidepoint, Infinity, Janssen, Merrimack, Medscape, Numab, 10.13039/100004319Pfizer, Prime Oncology, 10.13039/100010293Seattle Genetics, Takeda, Trieza Therapeutics, and WebMD; and other ownership interests in Molecular Match, OncoResponse, and Presagia Inc. Other authors: nothing to disclose., (© 2022 Flatiron Health, Inc.)

Introduction: Durvalumab after concurrent chemoradiation (CCRT) for NSCLC improves survival, but only in a subset of patients. We investigated the effect of severe radiation-induced lymphopenia (sRIL) on survival in these patients., Methods: Outcomes after CCRT (2010-2019) or CCRT followed by durvalumab (2018-2019) were reviewed. RIL was defined by absolute lymphocyte count (ALC) nadir in samples collected at end of CCRT; sRIL was defined as nadir ALC less than 0.23 × 10 9 /L (the lowest tertile). Progression-free survival (PFS) and overall survival (OS) were calculated by the Kaplan-Meier method. Cox proportional hazard modeling evaluated associations between clinical variables and survival., Results: Of 309 patients, 192 (62%) received CCRT only and 117 (38%) CCRT plus durvalumab. Multivariable logistic regression analysis indicated that sRIL was associated with planning target volume (OR = 1.002, p  = 0.001), stage IIIB disease (OR = 2.77, p  = 0.04), and baseline ALC (OR = 0.36, p < 0.01). Durvalumab extended median PFS (23.3 versus 14.1 mo, p  = 0.003) and OS (not reached versus 30.8 mo, p < 0.01). sRIL predicted poorer PFS and OS in both treatment groups. Among patients with sRIL, durvalumab did not improve survival (median = 24.6 mo versus 18.1 mo CCRT only, p  = 0.079). On multivariable analyses, sRIL (OR = 1.81, p < 0.01) independently predicted poor survival., Conclusions: Severe RIL compromises survival benefits from durvalumab after CCRT for NSCLC. Measures to mitigate RIL after CCRT may be warranted to enhance the benefit of consolidation durvalumab., (© 2022 The Authors.)

Background: Recent advances in developing "tumor agnostic" oncology therapies have identified molecular targets that define patient subpopulations in a manner that supersedes conventional criteria for cancer classification. These successes have produced effective targeted therapies that are administered to patients regardless of their tumor histology. Trials have evolved as well with master protocol designs. By blending translational and clinical science, basket trials in particular are well-suited to investigate and develop targeted therapies among multiple cancer histologies. However, basket trials intrinsically involve more complex design decisions, including issues of multiple testing across baskets, and guidance for investigators is needed., Methods: The sensitivity of the multisource exchangeability model to prior specification under differing degrees of response heterogeneity is explored through simulation. Then, a multisource exchangeability model design that incorporates control of the false-discovery rate is presented and a simulation study compares the operating characteristics to a design where the family-wise error rate is controlled and to the frequentist approach of treating the baskets as independent. Simulations are based on the original design of a real-world clinical trial, the SUMMIT trial, which investigated Neratinib treatment for a variety of solid tumors. The methods studied here are specific to single-arm phase II trials with binary outcomes., Results: Values of prior probability of exchangeability in the multisource exchangeability model between 0.1 and 0.3 provide the best trade-offs between gain in precision and bias, especially when per-basket sample size is below 30. Application of these calibration results to a re-analysis of the SUMMIT trial showed that the breast basket exceeded the null response rate with posterior probability of 0.999 while having low posterior probability of exchangeability with all other baskets. Simulations based on the design of the SUMMIT trial revealed that there is meaningful improvement in power even in baskets with small sample size when the false-discovery rate is controlled as opposed to the family-wise error rate. For example, when only the breast basket was active, with a sample size of 25, the power was 0.76 when the false-discovery rate was controlled at 0.05 but only 0.56 when the family-wise error rate was controlled at 0.05, indicating that impractical sample sizes for the phase II setting would be needed to achieve acceptable power while controlling the family-wise error rate in this setting of a trial with 10 baskets., Conclusion: Selection of the prior exchangeability probability based on calibration and incorporation of false-discovery rate control result in multisource exchangeability model designs with high power to detect promising treatments in the context of phase II basket trials.

Purpose: Recent studies have shown that severe depletion of the absolute lymphocyte count (ALC) induced by radiation therapy (RT) has been associated with poor overall survival of patients with many solid tumors. In this paper, we aimed to predict radiation-induced lymphocyte depletion in esophageal cancer patients during the course of RT based on patient characteristics and dosimetric features., Methods: We proposed a hybrid deep learning model in a stacked structure to predict a trend toward ALC depletion based on the clinical information before or at the early stages of RT treatment. The proposed model consisted of four channels, one channel based on long short-term memory (LSTM) network and three channels based on neural networks, to process four categories of features followed by a dense layer to integrate the outputs of four channels and predict the weekly ALC values. Moreover, a discriminative kernel was developed to extract temporal features and assign different weights to each part of the input sequence that enabled the model to focus on the most relevant parts. The proposed model was trained and tested on a dataset of 860 esophageal cancer patients who received concurrent chemoradiotherapy., Results: The performance of the proposed model was evaluated based on several important prediction metrics and compared to other commonly used prediction models. The results showed that the proposed model outperformed off-the-shelf prediction methods with at least a 30% reduction in the mean squared error (MSE) of weekly ALC predictions based on pretreatment data. Moreover, using an extended model based on augmented first-week treatment, data reduced the MSE of predictions by 70% compared to the model based on the pretreatment data., Conclusions: In conclusion, our model performed well in predicting radiation-induced lymphocyte depletion for RT treatment planning. The ability to predict ALC will enable physicians to evaluate individual RT treatment plans for lymphopenia risk and to identify patients at high risk who would benefit from modified treatment approaches., (© 2022 American Association of Physicists in Medicine.)

Background: There is a paucity of data regarding the association between radiation exposure of heart substructures and the incidence of major coronary events (MCEs) in patients with esophageal cancer (ESOC) undergoing chemoradiation therapy. We studied radiation dosimetric determinants of MCE risk and measured their impact on patient prognosis using a cohort of ESOC patients treated at a single institution. Methods: Between March 2005 and October 2015, 355 ESOC patients treated with concurrent chemoradiotherapy were identified from a prospectively maintained and institutional-regulatory-board-approved clinical database. Dose-distribution parameters of the whole heart, the atria, the ventricles, the left main coronary artery, and three main coronary arteries were extracted for analysis. Results: Within a median follow-up time of 67 months, 14 patients experienced MCEs at a median of 16 months. The incidence of MCEs was significantly associated with the left anterior descending coronary artery (LAD) receiving ≥30 Gy (V30Gy) (p = 0.048). Patients receiving LAD V30Gy ≥ 10% of volume experienced a higher incidence of MCEs versus the LAD V30Gy < 10% group (p = 0.044). The relative rate of death increased with the left main coronary artery (LMA) mean dose (Gy) (p = 0.002). Furthermore, a mutual promotion effect of hyperlipidemia and RT on MCEs was observed. Conclusion: Radiation dose to coronary substructures is associated with MCEs and overall survival in patients with ESOC. In this study, the doses to these substructures appeared to be better predictors of toxicity outcomes than mean heart dose (MHD) or whole-heart V30Gy. These findings have implications for reducing coronary events through radiation therapy planning.

Purpose: The customary approach to early-phase clinical trial design, where the focus is on identification of the maximum tolerated dose, is not always suitable for noncytotoxic or other targeted therapies. Many trials have continued to follow the 3 + 3 dose-escalation design, but with the addition of phase I dose-expansion cohorts to further characterize safety and assess efficacy. Dose-expansion cohorts are not always planned in advance nor rigorously designed. We introduce an approach to the design of phase I expansion cohorts on the basis of sequential predictive probability monitoring., Methods: Two optimization criteria are proposed that allow investigators to stop for futility to preserve limited resources while maintaining traditional control of type I and type II errors. We demonstrate the use of these designs through simulation, and we elucidate their implementation with a redesign of the phase I expansion cohort for atezolizumab in metastatic urothelial carcinoma., Results: A sequential predictive probability design outperforms Simon's two-stage designs and posterior probability monitoring with respect to both proposed optimization criteria. The Bayesian sequential predictive probability design yields increased power while significantly reducing the average sample size under the null hypothesis in the context of the case study, whereas the original study design yields too low type I error and power. The optimal efficiency design tended to have more desirable properties, subject to constraints on type I error and power, compared with the optimal accuracy design., Conclusion: The optimal efficiency design allows investigators to preserve limited financial resources and to maintain ethical standards by halting potentially large dose-expansion cohorts early in the absence of promising efficacy results, while maintaining traditional control of type I and II error rates., Competing Interests: Elizabeth Garrett-MayerConsulting or Advisory Role: Deciphera Brian P. HobbsStock and Other Ownership Interests: PresagiaConsulting or Advisory Role: STCube Pharmaceuticals Inc, BayerResearch Funding: Amgen(OPTIONAL) Uncompensated Relationships: PresagiaNo other potential conflicts of interest were reported.

Pivotal cancer trials often fail to yield evidence in support of new therapies thought to offer promising alternatives to standards-of-care. Conducting randomized controlled trials in oncology tends to be considerably more expensive than studies of other diseases with comparable sample size. Moreover, phase III trial design often takes place with a paucity of survival data for experimental therapies. Experts have explained the failures on the basis of design flaws which produce studies with unrealistic expectations. This article presents a framework for predicting outcomes of phase III oncology trials using Bayesian mediation models. Predictions, which arise from interim analyses, derive from multivariate modeling of the relationships among treatment, tumor response, and their conjoint effects on survival. Acting as a safeguard against inaccurate pre-trial design assumptions, the methodology may better facilitate rapid closure of negative studies. Additionally the models can be used to inform re-estimations of sample size for under-powered trials that demonstrate survival benefit via tumor response mediation. The methods are applied to predict the outcomes of two colorectal cancer studies. Simulation is used to evaluate and compare models in the absence versus presence of reliable surrogate markers of survival., (© 2021 John Wiley & Sons Ltd.)

Definitive clinical trials are resource intensive, often requiring a large number of participants over several years. One approach to improve the efficiency of clinical trials is to incorporate historical information into the primary trial analysis. This approach has tremendous potential in the areas of pediatric or rare disease trials, where achieving reasonable power is difficult. In this article, we introduce a novel Bayesian group-sequential trial design based on Multisource Exchangeability Models, which allows for dynamic borrowing of historical information at the interim analyses. Our approach achieves synergy between group sequential and adaptive borrowing methodology to attain improved power and reduced sample size. We explore the frequentist operating characteristics of our design through simulation and compare our method to a traditional group-sequential design. Our method achieves earlier stopping of the primary study while increasing power under the alternative hypothesis but has a potential for type I error inflation under some null scenarios. We discuss the issues of decision boundary determination, power and sample size calculations, and the issue of information accrual. We present our method for a continuous and binary outcome, as well as in a linear regression setting., (© 2021 John Wiley & Sons Ltd.)

Multisource exchangeability models (MEMs), a BayeTsian approach for dynamically integrating information from multiple clinical trials, are a promising approach for gaining efficiency in randomized controlled trials. When the supplementary trials are considerably larger than the primary trial, care must be taken when integrating supplementary data to avoid overwhelming the primary trial. In this paper, we propose "capping priors," which controls the extent of dynamic borrowing by placing an a priori cap on the effective supplemental sample size. We demonstrate the behavior of this technique via simulation, and apply our method to four randomized trials of very low nicotine content cigarettes.

Determining the extent to which a patient is benefiting from cancer therapy is challenging. Criteria for quantifying the extent of "tumor response" observed within a few cycles of treatment have been established for various types of solids as well as hematologic malignancies. These measures comprise the primary endpoints of phase II trials. Regulatory approvals of new cancer therapies, however, are usually contingent upon the demonstration of superior overall survival with randomized evidence acquired with a phase III trial comparing the novel therapy to an appropriate standard of care treatment. With nearly two-thirds of phase III oncology trials failing to achieve statistically significant results, researchers continue to refine and propose new surrogate endpoints. This article presents a Bayesian framework for studying relationships among treatment, patient subgroups, tumor response, and survival. Combining classical components of a mediation analysis with Bayesian model averaging, the methodology is robust to model misspecification among various possible relationships among the observable entities. A posterior inference is demonstrated via an application to a randomized controlled phase III trial in metastatic colorectal cancer. Moreover, the article details posterior predictive distributions of survival and statistical metrics for quantifying the extent of direct and indirect, or tumor response mediated treatment effects.

Background: Several randomized trials have been performed comparing partial breast irradiation (PBI) and whole breast irradiation (WBI) though controversy remains, including regarding differences by PBI technique. We performed a meta-analysis to compare results between WBI versus PBI and between PBI techniques., Methods: A systematic review was performed to identify modern randomized studies listed in MEDLINE from 2005 to 2020. PBI trials were divided into external beam radiation and brachytherapy techniques, with intraoperative radiation excluded. A Bayesian logistic regression model evaluated the risk of ipsilateral breast tumor recurrence (IBTR) and acute and chronic toxicities. The primary outcome was IBTR at 5 years with WBI compared with PBI., Results: A total of 9758 patients from 7 studies were included (4840-WBI, 4918-PBI). At 5 years, no statistically significant difference in the rate of IBTR was noted between PBI (1.8%, 95% HPD 0.68-3.2%) and WBI (1.7%, 95% HPD 0.92-2.4%). By PBI technique, the 5-year rate of IBTR rate for external beam was 1.7% and 2.2% for brachytherapy. Rates of grade 2 + acute toxicity were 7.1% with PBI versus 47.5% with WBI. For late toxicities, grade 2/3 rates were 0%/0% with PBI compared with 1.0%/0% with WBI., Conclusions: IBTR rates were similar between PBI and WBI with no significant differences noted by PBI technique; PBI had reduced acute toxicities compared to WBI. Because studies did not provide toxicity data in a consistent fashion, definitive conclusions cannot be made with additional data from randomized trials needed to compare toxicity profiles between PBI techniques., (© 2021. Society of Surgical Oncology.)

Purpose: Radiotherapy (RT)-induced lymphopenia (RIL) is commonly associated with adverse clinical outcomes in patients with cancer. Using machine learning techniques, a retrospective study was conducted for patients with esophageal cancer treated with proton and photon therapies to characterize the principal pretreatment clinical and radiation dosimetric risk factors of grade 4 RIL (G4RIL) as well as to establish G4RIL risk profiles., Methods: A single-institution retrospective data of 746 patients with esophageal cancer treated with photons (n = 500) and protons (n = 246) was reviewed. The primary end point of our study was G4RIL. Clustering techniques were applied to identify patient subpopulations with similar pretreatment clinical and radiation dosimetric characteristics. XGBoost was built on a training set (n = 499) to predict G4RIL risks. Predictive performance was assessed on the remaining n = 247 patients. SHapley Additive exPlanations were used to rank the importance of individual predictors. Counterfactual analyses compared patients' risk profiles assuming that they had switched modalities., Results: Baseline absolute lymphocyte count and volumes of lung and spleen receiving ≥ 15 and ≥ 5 Gy, respectively, were the most important G4RIL risk determinants. The model achieved sensitivity testing-set 0.798 and specificity testing-set 0.667 with an area under the receiver operating characteristics curve (AUC testing-set ) of 0.783. The G4RIL risk for an average patient receiving protons increased by 19% had the patient switched to photons. Reductions in G4RIL risk were maximized with proton therapy for patients with older age, lower baseline absolute lymphocyte count, and higher lung and heart dose., Conclusion: G4RIL risk varies for individual patients with esophageal cancer and is modulated by radiotherapy dosimetric parameters. The framework for machine learning presented can be applied broadly to study risk determinants of other adverse events, providing the basis for adapting treatment strategies for mitigation., Competing Interests: Cong ZhuStock and Other Ownership Interests: Biogen, AbbVie, Regeneron, Hepion Pharmaceuticals, Galectin Therapeutics Radhe MohanStock and Other Ownership Interests: General Electric, Berkshire Hathaway Steven H. LinEmployment: MD Anderson Cancer CenterHonoraria: AstraZeneca/MedImmune, BeyondSpring PharmaceuticalsSpeakers' Bureau: AstraZenecaResearch Funding: BeyondSpring Pharmaceuticals, Nektar, STCube Pharmaceuticals IncTravel, Accommodations, Expenses: STCube Pharmaceuticals Inc, Elekta Qianxia WangEmployment: Philips (I) Brian P. HobbsStock and Other Ownership Interests: PresagiaConsulting or Advisory Role: STCube Pharmaceuticals Inc, BayerResearch Funding: AmgenUncompensated Relationships: PresagiaNo other potential conflicts of interest were reported.

Misgivings have been raised about the operating characteristics of the canonical 3+3 dose-escalation phase I clinical trial design. Yet, the traditional 3+3 design is still the most commonly used. Although it has been implied that adhering to this design is due to a stubborn reluctance to adopt change despite other designs performing better in hypothetical computer-generated simulation models, the continued adherence to 3+3 dose-escalation phase I strategies is more likely because these designs perform the best in the real world, pinpointing the correct dose and important side effects with an acceptable degree of precision. Beyond statistical simulations, there are little data to refute the supposed shortcomings ascribed to the 3+3 method. Even so, to address the unique nuances of gene- and immune-targeted compounds, a variety of inventive phase 1 trial designs have been suggested. Strategies for developing these therapies have launched first-in-human studies devised to acquire a breadth of patient data that far exceed the size of a typical phase I design and blur the distinction between dose selection and efficacy evaluation. Recent phase I trials of promising cancer therapies assessed objective tumor response and durability at various doses and schedules as well as incorporated multiple expansion cohorts spanning a variety of histology or biomarker-defined tumor subtypes, sometimes resulting in U.S. Food and Drug Administration approval after phase I. This article reviews recent innovations in phase I design from the perspective of multiple stakeholders and provides recommendations for future trials.

Background: Radiotherapy might augment systemic antitumoral responses to immunotherapy. In the PEMBRO-RT (phase 2) and MDACC (phase 1/2) trials, patients with metastatic non-small-cell lung cancer were randomly allocated immunotherapy (pembrolizumab) with or without radiotherapy. When the trials were analysed individually, a potential benefit was noted in the combination treatment arm. However, owing to the small sample size of each trial, differences in response rates and outcomes were not statistically significant but remained clinically notable. We therefore did a pooled analysis to infer whether radiotherapy improves responses to immunotherapy in patients with metastatic non-small-cell lung cancer., Methods: Inclusion criteria for the PEMBRO-RT and MDACC trials were patients (aged ≥18 years) with metastatic non-small-cell lung cancer and at least one unirradiated lesion to monitor for out-of-field response. In the PEMBRO-RT trial, patients had previously received chemotherapy, whereas in the MDACC trial, patients could be either previously treated or newly diagnosed. Patients in both trials were immunotherapy-naive. In the PEMBRO-RT trial, patients were randomly assigned (1:1) and stratified by smoking status (<10 vs ≥10 pack-years). In the MDACC trial, patients were entered into one of two cohorts based on radiotherapy schedule feasibility and randomly assigned (1:1). Because of the nature of the intervention in the combination treatment arm, blinding to radiotherapy was not feasible in either trial. Pembrolizumab was administered intravenously (200 mg every 3 weeks) with or without radiotherapy in both trials. In the PEMBRO-RT trial, the first dose of pembrolizumab was given sequentially less than 1 week after the last dose of radiotherapy (24 Gy in three fractions), whereas in the MDACC trial, pembrolizumab was given concurrently with the first dose of radiotherapy (50 Gy in four fractions or 45 Gy in 15 fractions). Only unirradiated lesions were measured for response. The endpoints for this pooled analysis were best out-of-field (abscopal) response rate (ARR), best abscopal disease control rate (ACR), ARR at 12 weeks, ACR at 12 weeks, progression-free survival, and overall survival. The intention-to-treat populations from both trials were included in analyses. The PEMBRO-RT trial (NCT02492568) and the MDACC trial (NCT02444741) are registered with ClinicalTrials.gov., Findings: Overall, 148 patients were included in the pooled analysis, 76 of whom had been assigned pembrolizumab and 72 who had been assigned pembrolizumab plus radiotherapy. Median follow-up for all patients was 33 months (IQR 32·4-33·6). 124 (84%) of 148 patients had non-squamous histological features and 111 (75%) had previously received chemotherapy. Baseline variables did not differ between treatment groups, including PD-L1 status and metastatic disease volume. The most frequently irradiated sites were lung metastases (28 of 72 [39%]), intrathoracic lymph nodes (15 of 72 [21%]), and lung primary disease (12 of 72 [17%]). Best ARR was 19·7% (15 of 76) with pembrolizumab versus 41·7% (30 of 72) with pembrolizumab plus radiotherapy (odds ratio [OR] 2·96, 95% CI 1·42-6·20; p=0·0039), and best ACR was 43·4% (33 of 76) with pembrolizumab versus 65·3% (47 of 72) with pembrolizumab plus radiotherapy (2·51, 1·28-4·91; p=0·0071). Median progression-free survival was 4·4 months (IQR 2·9-5·9) with pembrolizumab alone versus 9·0 months (6·8-11·2) with pembrolizumab plus radiotherapy (hazard ratio [HR] 0·67, 95% CI 0·45-0·99; p=0·045), and median overall survival was 8·7 months (6·4-11·0) with pembrolizumab versus 19·2 months (14·6-23·8) with pembrolizumab plus radiotherapy (0·67, 0·54-0·84; p=0·0004). No new safety concerns were noted in the pooled analysis., Interpretation: Adding radiotherapy to pembrolizumab immunotherapy significantly increased responses and outcomes in patients with metastatic non-small-cell lung cancer. These results warrant validation in a randomised phase 3 trial., Funding: Merck Sharp & Dohme., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: Cancer immunotherapy is associated with several immune-related adverse events, but the relationship between immunotherapy and venous thromboembolism has not been thoroughly studied., Methods: We conducted a retrospective cohort study of 1,686 patients who received immunotherapy for a variety of malignancies to determine the incidence of venous thromboembolism and the impact of venous thromboembolism on survival. To examine the potential role of inflammation in venous thromboembolism, we also profiled immune cells and plasma cytokines in blood samples obtained prior to initiation of immunotherapy in a sub-cohort of patients treated on clinical trials who subsequently did (N = 15), or did not (N = 10) develop venous thromboembolism., Findings: Venous thromboembolism occurred while on immunotherapy in 404/1686 patients (24%) and was associated with decreased overall survival [HR=1.22 (95% CI 1.06-1.41), p<0.008]. Patients that developed venous thromboembolism had significantly higher pretreatment levels of myeloid-derived suppressor cells (5.382 ± 0.873 vs. 3.341 ± 0.3402, mean ± SEM; p=0.0045), interleukin 8 (221.2 ± 37.53 vs. 111.6 ± 25.36, mean ± SEM; p=0.016), and soluble vascular cell adhesion protein 1 (1210 ± 120.6 vs. 895.5 ± 53.34, mean ± SEM; p=0.0385)., Conclusions: These findings demonstrate that venous thromboembolism is an underappreciated and important immune-related adverse event associated with cancer immunotherapy, and may implicate an interleukin 8 and myeloid-derived suppressor cell-driven pathway in pathogenesis.

Breakthroughs in cancer biology have defined new research programs emphasizing the development of therapies that target specific pathways in tumor cells. Innovations in clinical trial design have followed with master protocols defined by inclusive eligibility criteria and evaluations of multiple therapies and/or histologies. Consequently, characterization of subpopulation heterogeneity has become central to the formulation and selection of a study design. However, this transition to master protocols has led to challenges in identifying the optimal trial design and proper calibration of hyperparameters. We often evaluate a range of null and alternative scenarios; however, there has been little guidance on how to synthesize the potentially disparate recommendations for what may be optimal. This may lead to the selection of suboptimal designs and statistical methods that do not fully accommodate the subpopulation heterogeneity. This article proposes novel optimization criteria for calibrating and evaluating candidate statistical designs of master protocols in the presence of the potential for treatment effect heterogeneity among enrolled patient subpopulations. The framework is applied to demonstrate the statistical properties of conventional study designs when treatments offer heterogeneous benefit as well as identify optimal designs devised to monitor the potential for heterogeneity among patients with differing clinical indications using Bayesian modeling.

Morphologic interpretation is the standard in diagnosing myelodysplastic syndrome (MDS), but it has limitations, such as varying reliability in pathologic evaluation and lack of integration with genetic data. Somatic events shape morphologic features, but the complexity of morphologic and genetic changes makes clear associations challenging. This article interrogates novel clinical subtypes of MDS using a machine-learning technique devised to identify patterns of cooccurrence among morphologic features and genomic events. We sequenced 1079 MDS patients and analyzed bone marrow morphologic alterations and other clinical features. A total of 1929 somatic mutations were identified. Five distinct morphologic profiles with unique clinical characteristics were defined. Seventy-seven percent of higher-risk patients clustered in profile 1. All lower-risk (LR) patients clustered into the remaining 4 profiles: profile 2 was characterized by pancytopenia, profile 3 by monocytosis, profile 4 by elevated megakaryocytes, and profile 5 by erythroid dysplasia. These profiles could also separate patients with different prognoses. LR MDS patients were classified into 8 genetic signatures (eg, signature A had TET2 mutations, signature B had both TET2 and SRSF2 mutations, and signature G had SF3B1 mutations), demonstrating association with specific morphologic profiles. Six morphologic profiles/genetic signature associations were confirmed in a separate analysis of an independent cohort. Our study demonstrates that nonrandom or even pathognomonic relationships between morphology and genotype to define clinical features can be identified. This is the first comprehensive implementation of machine-learning algorithms to elucidate potential intrinsic interdependencies among genetic lesions, morphologies, and clinical prognostic in attributes of MDS., (© 2020 by The American Society of Hematology.)

Background: The optimal tumor-free margin definition and width following breast-conserving therapy (BCT) for early-stage invasive cancers has been evaluated in previous meta-analyses and guidelines. We performed an updated meta-analysis to assess how improvements in treatment over time have affected the impact of margins on local recurrence (LR) rates over time., Methods: A systematic literature review identified 38 eligible studies comprising 54,502 patients treated between 1968 and 2010. Inclusion criteria included patients treated with BCT and minimum follow-up of 50 months, pathologic definitions of margin status explicitly stated, and LR data in relation to margin status. Data were pooled using a Bayesian logistic regression model to evaluate the risk of LR in relation to both margin status and study enrollment periods., Results: Median follow-up was 7.25 years. Absolute LR rates decreased over time for each margin width cohort, with maximum differences between negative margin groups of less than 1% for the most recent enrollment period. However, relative rates of LR between different margin groups remained stable over time., Conclusions: With an additional 22,000 patients compared with the previous meta-analysis, this updated meta-analysis supports the consensus guideline of "no tumor on ink" for the majority of patients. Additionally, while concerns exist regarding a benefit with wider margins from previous studies, the analysis demonstrates the impact of margin width on LR rates has declined substantially over time, with very small differences between the narrowest and widest margin groups in the most recent cohort. Hence, older studies appear to have limited value to inform current management guidelines.

Background: Disparities in breast cancer survival by race/ethnicity and socioeconomic status have been reported. However, it is unclear if these findings are reproducible among subpopulations. This study aimed to assess if socially oriented factors are predictive of overall survival (OS) among patients with hormone receptor-positive (HR + ), human epidermal growth factor 2-positive (HER2 + ) metastatic breast cancer (MBC)., Patients and Methods: We analyzed patients with MBC included in the National Cancer Database diagnosed with HR + and HER2 + disease treated between 2010 and 2015. Multivariate analyses describe the association between non-clinical prognostic factors and OS. A matched analysis, which balanced prognostic factors between whites and African Americans (AA), was also conducted., Results: Of the 6200 patients analyzed, the majority were 50 years or older, white, and treated with hormonal therapy. Disparities in OS were observed; multivariate analysis revealed diminished survival was associated with low income (< $38K vs. ≥ $63K, hazard ratio [HR], 1.30; P < .001), having government insurance (government vs. private, HR, 1.55; P < .001), living closer to one's treatment facility (< 4 miles vs. ≥ 18 miles, HR, 1.16; P = .04), and being AA (AA vs. white, HR, 1.20; P = .006). The mortality disparity attributed to race was insignificant in the matched analysis (AA vs. white, HR, 1.13; 95% confidence interval, 0.98-1.30; P = .09)., Conclusions: This study confirms that the known sociodemographic disparities in OS among patients with MBC are similar within the HR + /HER2 + subpopulation. The discordance of outcomes between matched and unmatched analysis demonstrate that there is a highly vulnerable subgroup of AAs. Further investigation is required to determine if the identified associations are independently causal of poor prognosis., (Copyright © 2020 Elsevier Inc. All rights reserved.)

With advances in tumour biology and immunology that continue to refine our understanding of cancer, therapies are now being developed to treat cancers on the basis of specific molecular alterations and markers of immune phenotypes that transcend specific tumour histologies. With the landmark approvals of pembrolizumab for the treatment of patients whose tumours have high microsatellite instability and larotrectinib and entrectinib for those harbouring NTRK fusions, a regulatory pathway has been created to facilitate the approval of histology-agnostic indications. Negative results presented in the past few years, however, highlight the intrinsic complexities faced by drug developers pursuing histology-agnostic therapeutic agents. When patient selection and statistical analysis involve multiple potentially heterogeneous histologies, guidance is needed to navigate the challenges posed by trial design. Additionally, as new therapeutic agents are tested and post-approval data become available, the regulatory framework for acting on these data requires further optimization. In this Review, we summarize the development and testing of approved histology-agnostic therapeutic agents and present data on other agents currently under development. Finally, we discuss the challenges intrinsic to histology-agnostic drug development in oncology, including biological, regulatory, design and statistical considerations.

Randomized controlled trials (RCTs) are considered the highest level of evidence to establish causal associations in clinical research. There are many RCT designs and features that can be selected to address a research hypothesis. Designs of RCTs have become increasingly diverse as new methods have been proposed to evaluate increasingly complex scientific hypotheses. This article reviews the principles and general concepts behind many common RCT designs and introduces newer designs that have been proposed, such as adaptive and cluster randomized trials. A focus on the many choices for randomization within an RCT is described, along with their potential tradeoffs. To illustrate their diversity, examples of RCTs from the literature are provided. Statistical considerations, such as power and type I error rates, are discussed with the intention of providing practical guidance about how to specify study hypotheses that address the scientific question while being statistically appropriate. Finally, the freely available Consolidated Standards of Reporting Trials guidelines and US Food and Drug Administration guidance documents are introduced, along with a set of guidelines one should consider when planning an RCT or reviewing RCTs submitted for publication in peer-reviewed academic journals., (Copyright © 2020 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Purpose: Whether dosimetric advantages of proton beam therapy (PBT) translate to improved clinical outcomes compared with intensity-modulated radiation therapy (IMRT) remains unclear. This randomized trial compared total toxicity burden (TTB) and progression-free survival (PFS) between these modalities for esophageal cancer., Methods: This phase IIB trial randomly assigned patients to PBT or IMRT (50.4 Gy), stratified for histology, resectability, induction chemotherapy, and stage. The prespecified coprimary end points were TTB and PFS. TTB, a composite score of 11 distinct adverse events (AEs), including common toxicities as well as postoperative complications (POCs) in operated patients, quantified the extent of AE severity experienced over the duration of 1 year following treatment. The trial was conducted using Bayesian group sequential design with three planned interim analyses at 33%, 50%, and 67% of expected accrual (adjusted for follow-up)., Results: This trial (commenced April 2012) was approved for closure and analysis upon activation of NRG-GI006 in March 2019, which occurred immediately prior to the planned 67% interim analysis. Altogether, 145 patients were randomly assigned (72 IMRT, 73 PBT), and 107 patients (61 IMRT, 46 PBT) were evaluable. Median follow-up was 44.1 months. Fifty-one patients (30 IMRT, 21 PBT) underwent esophagectomy; 80% of PBT was passive scattering. The posterior mean TTB was 2.3 times higher for IMRT (39.9; 95% highest posterior density interval, 26.2-54.9) than PBT (17.4; 10.5-25.0). The mean POC score was 7.6 times higher for IMRT (19.1; 7.3-32.3) versus PBT (2.5; 0.3-5.2). The posterior probability that mean TTB was lower for PBT compared with IMRT was 0.9989, which exceeded the trial's stopping boundary of 0.9942 at the 67% interim analysis. The 3-year PFS rate (50.8% v 51.2%) and 3-year overall survival rates (44.5% v 44.5%) were similar., Conclusion: For locally advanced esophageal cancer, PBT reduced the risk and severity of AEs compared with IMRT while maintaining similar PFS.

Introduction: Stereotactic body radiotherapy (SBRT) results in excellent local control of stage I NSCLC. Radiobiology models predict greater tumor response when higher biologically effective doses (BED 10 ) are given. Prior studies support a BED 10 greater than or equal to 100 Gy with SBRT; however, data are limited comparing outcomes after various SBRT regimens. We therefore sought to evaluate national trends and the effect of using "low" versus "high" BED 10 SBRT courses on overall survival (OS)., Methods: This retrospective study used the National Cancer Data Base to identify patients diagnosed with clinical stage I (cT1-2aN0M0) NSCLC from 2004 to 2014 treated with SBRT. Patients were categorized into LowBED (100-129 Gy) or HighBED (≥130 Gy) groups. A 1:1 matched analysis based on patient and tumor characteristics was used to compare OS by BED 10 group. Tumor centrality was not assessed., Results: O 25,039 patients treated with LowBED (n = 14,756; 59%) or HighBED (n = 10,283; 41%) SBRT, 20,542 were matched. Shifts in HighBED to LowBED SBRT regimen use correlated with key publications in the literature. In the matched cohort, 5-year OS rates were 26% for LowBED and 34% for HighBED groups (p = 0.039). On multivariate analysis, receipt of LowBED was associated with significantly worse survival (hazard ratio = 1.046, 95% confidence interval: 1.004-1.090, p = 0.032)., Conclusions: LowBED SBRT for treating stage I NSCLC is becoming more common. However, our findings suggest SBRT regimens with BED 10 greater than or equal to 130 Gy may confer an additional survival benefit. Additional studies are required to evaluate the dose-response relationship and toxicities associated with modern HighBED SBRT., (Copyright © 2019 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

Perfusion computed tomography is an emerging functional imaging modality that uses physiological models to quantify characteristics pertaining to the passage of fluid through blood vessels. Perfusion characteristics provide physiological correlates for neovascularization induced by tumor angiogenesis and thus a quantitative basis for cancer detection, prognostication, and treatment monitoring. We consider a liver cancer study where patients underwent a dynamic computed tomography protocol to enable evaluation of multiple perfusion characteristics derived from interrogating the time-attenuation of the concentration of the intravenously administered contrast medium. The objective is to determine the effectiveness of using perfusion characteristics to identify and discriminate between regions of liver that contain malignant tissues from normal tissue. Each patient contributes multiple regions of interest which are spatially correlated due to the shared vasculature. We propose a multivariate functional data model to disclose the correlation over time and space as well as the correlation among multiple perfusion characteristics. We further propose a simultaneous classification approach that utilizes all the correlation information to predict class assignments for collections of regions. The proposed method outperforms conventional classification approaches in the presence of strong spatial correlation. The method offers maximal relative improvement in the presence of temporal sparsity wherein measurements are obtainable at only a few time points.

Treatment patterns and outcomes are unclear for metastatic breast cancer (MBC) patients diagnosed with hormone receptor-positive (HR+), human epidermal growth factor 2-positive (HER2+) disease. This study aimed to: (1) examine the utilization of first-line therapy among HR+/HER2+/MBC patients and (2) compare overall survival (OS) between the identified regimens. We analyzed National Cancer Database patients (HR+/HER2+/MBC) who were treated between 2010 and 2015. Multivariable logistic and Cox regression were used to: (1) identify independent predictors of treatment receipt and (2) determine significant prognostic factors for OS. Kaplan-Meier method and log-rank test were used to estimate and evaluate OS, respectively. Propensity scores were added to all multivariate OS models, thereby accounting for bias in treatment receipt. Of 6,234 patients analyzed, 3770 (60.5%) received hormonal therapy and 2464 (39.5%) received chemotherapy. Receipt of hormonal therapy was associated with older age, grade 1/grade 2 disease, no visceral involvement, higher comorbidity scores, and being white. Multivariate analysis suggest patients receiving hormonal therapy + anti-HER2 experienced improved OS, when compared to chemotherapy + anti-HER2 (HR: 0.74, p = 0.004). Overall, the cohort receiving hormonal therapy + anti-HER2 reported the highest 5-year OS (hormonal + anti-HER2: 47.5% vs. chemotherapy + anti-HER2: 39.8% vs. hormonal: 38.5% vs. chemotherapy: 36.3%, p < 0.001). Our findings suggest de-escalated therapy may be the preferred and potentially more effective care path for HR+/HER2+/MBC patients, signaling a need for randomized studies.

Progress in the areas of genomics, disease pathways, and drug discovery has advanced into clinical and translational cancer research. The latest innovations in clinical trials have followed with master protocols, which are defined by inclusive eligibility criteria and devised to interrogate multiple therapies for a given tumor histology and/or multiple histologies for a given therapy under one protocol. The use of master protocols for oncology has become more common with the desire to improve the efficiency of clinical research and accelerate overall drug development. Basket trials have been devised to ascertain the extent to which a treatment strategy offers benefit to various patient subpopulations defined by a common molecular target. Conventionally conducted within the phase II setting, basket designs have become popular as drug developers seek to effectively evaluate and identify preliminary efficacy signals among clinical indications identified as promising in preclinical study. This article reviews basket trial designs in oncology settings and discusses several issues that arise with their design and analysis.

The scientific purpose of phase I trials is to determine the maximum tolerated dose and/or optimal biological dose of experimental agents. Yet most participants in phase I oncology trials enroll hoping for direct medical benefit. The most common phase I trial designs use low starting doses and escalate cautiously in a "risk-escalation" model focused on minimizing risk for each participant. This approach ensures that a proportion of subjects will likely not receive any benefit, even if the intervention proves to be successful at appropriate doses. In this article, we propose that trial designs should employ dosing strategies that increase chances of providing benefit if the investigational agent should prove to be successful while limiting risk to reasonable levels. We then describe how adaptive trial designs can facilitate refined dose optimization based on both therapeutic benefit and toxicity, which can simultaneously decrease the risk of harm while increasing the chances of benefit., (© 2019 by The Hastings Center. All rights reserved.)

Background: Checkpoint inhibitor therapy is a standard of care for patients with metastatic renal cell carcinoma. Treatment options after checkpoint inhibitor therapy include vascular endothelial growth factor receptor (VEGF-R) tyrosine kinase inhibitors, although no prospective data regarding their use in this setting exist. Axitinib is a VEGF-R inhibitor with clinical data supporting increased activity with dose titration. We aimed to investigate the activity of dose titrated axitinib in patients with metastatic renal cell carcinoma who were previously treated with checkpoint inhibitor., Methods: We did a multicentre, phase 2 trial of axitinib given on an individualised dosing algorithm. Patients at least 18 years of age with histologically or cytologically confirmed locally recurrent or metastatic renal cell carcinoma with clear cell histology, a Karnofsky Performance Status of 70% or more, and measurable disease who received checkpoint inhibitor therapy as the most recent treatment were eligible. There was no limit on number of previous therapies received. Patients received oral axitinib at a starting dose of 5 mg twice daily with dose titration every 14 days in 1 mg increments (ie, 5 mg twice daily to 6 mg twice daily, up to 10 mg twice daily maximum dose) if there was no axitinib-related grade 2 or higher mucositis, diarrhoea, hand-foot syndrome, or fatigue. If one or more of these grade 2 adverse events occurred, axitinib was withheld for 3 days before the same dose was resumed. Dose reductions were made if recurrent grade 2 adverse events despite treatment breaks or grade 3-4 adverse events occurred. The primary outcome was progression-free survival. Analyses were done per protocol in all patients who received at least one dose of axitinib. Recruitment has been completed and the trial is ongoing. This trial is registered with ClincalTrials.gov, number NCT02579811., Findings: Between Jan 5, 2016 and Feb 21, 2018, 40 patients were enrolled and received at least one dose of study treatment. With a median follow-up of 8·7 months (IQR 3·7-14·2), the median progression-free survival was 8·8 months (95% CI 5·7-16·6). Fatigue (83%) and hypertension (75%) were the most common all-grade adverse events. The most common grade 3 adverse event was hypertension (24 patients [60%]). There was one (3%) grade 4 adverse event (elevated lipase) and no treatment-related deaths occurred. Serious adverse events that were likely related to therapy occurred in eight (20%) patients; the most common were dehydration (n=4) and diarrhoea (n=2)., Interpretation: Individualised axitinib dosing in patients with metastatic renal cell inoma previously treated with checkpoint inhibitors did not meet the prespecified threshold for progression free survival, but these data show that this individualised titration scheme is feasible and has robust clinical activity. These prospective results warrant consideration of axitinib in this setting., Funding: Pfizer., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Precision medicine has emerged from the awareness that many human diseases are intrinsically heterogeneous with respect to their pathogenesis and composition among patients as well as dynamic over the course therapy. Its successful application relies on our understanding of distinct molecular profiles and their biomarkers which can be used as targets to devise treatment strategies that exploit current understanding of the biological mechanisms of the disease. Precision medicine present challenges to traditional paradigms of clinical translational, however, for which estimates of population-averaged effects from large randomized trials are used as the basis for demonstrating improvements comparative effectiveness. A general approach for estimating the relative effectiveness of biomarker-guided therapeutic strategies is presented herein. The statistical procedure attempts to define the local benefit of a given biomarker-guided therapeutic strategy in consideration of the treatment response surfaces, selection rule, and inter-cohort balance of prognostic determinants. Theoretical and simulation results are provided. Additionally, the methodology is demonstrated through a proteomic study of lower grade glioma.

Introduction: Dovitinib is an oral, potent inhibitor of FGFR and VEGFR, and can be a promising strategy in patients with recurrent or progressive glioblastoma (GBM)., Methods: This was an open label phase II study of two arms: Arm 1 included anti-angiogenic naïve patients with recurrent GBM and Arm 2 included patients with recurrent GBM that had progressed on prior anti-angiogenic therapy. Nineteen subjects were enrolled in Arm 1 and 14 subjects in Arm 2. The primary endpoint was 6-month progression-free survival (PFS-6) in Arm 1 and time to progression (TTP) in Arm 2. The secondary endpoints were toxicity, objective response rate (ORR) and overall survival., Results: Patients in Arm 2 (compared to Arm 1) tended to have longer intervals from diagnosis to study entry (median 26.9 vs. 8.9 months, p = 0.002), experienced more recurrences (64%, had 3-4 prior recurrences compared to 0, p < 0.0001) and tended to be heavily pretreated (71% vs. 26-32% p = 0.04 or 0.02). 6-month PFS was 12% ± 6% for the Arm 1 and 0% for Arm 2. TTP was similar in both treatment arms (median 1.8 months Arm 1 and 0.7-1.8 months Arm 2, p = 0.36). Five patients (15%) had grade 4 toxicities and 22 patients (67%) had grade 3 toxicities. There were no significant differences between the two arms with respect to the amount of change in the levels of biomarkers from baseline., Conclusion: Dovitinib was not efficacious in prolonging the PFS in patients with recurrent GBM irrespective of prior treatment with anti-angiogenic therapy (including bevacizumab).

The evolution of "informatics" technologies has the potential to generate massive databases, but the extent to which personalized medicine may be effectuated depends on the extent to which these rich databases may be utilized to advance understanding of the disease molecular profiles and ultimately integrated for treatment selection, necessitating robust methodology for dimension reduction. Yet, statistical methods proposed to address challenges arising with the high-dimensionality of omics-type data predominately rely on linear models and emphasize associations deriving from prognostic biomarkers. Existing methods are often limited for discovering predictive biomarkers that interact with treatment and fail to elucidate the predictive power of their resultant selection rules. In this article, we present a Bayesian predictive method for personalized treatment selection that is devised to integrate both the treatment predictive and disease prognostic characteristics of a particular patient's disease. The method appropriately characterizes the structural constraints inherent to prognostic and predictive biomarkers, and hence properly utilizes these complementary sources of information for treatment selection. The methodology is illustrated through a case study of lower grade glioma. Theoretical considerations are explored to demonstrate the manner in which treatment selection is impacted by prognostic features. Additionally, simulations based on an actual leukemia study are provided to ascertain the method's performance with respect to selection rules derived from competing methods., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: Nivolumab is approved for mRCC patients who have received prior anti-angiogenic therapy but the duration of therapy required for sustained clinical benefit is unknown. A phase II clinical trial to investigate the feasibility of intermittent nivolumab dosing was conducted., Methods: Patients ≥18 years of age with mRCC who were previously treated with at least one antiangiogenic therapy were eligible. Patients were treated with nivolumab for twelve weeks. Patients who had RECIST PD were removed from the trial. Patients who did not initially achieve ≥10% reduction in tumor burden (TB) continued nivolumab per standard of care. Patients with ≥10% TB reduction entered a treatment-free observation phase with re-imaging every 12 weeks. Nivolumab was restarted in patients with a ≥ 10% TB increase and again held with TB reduction ≥10%. This intermittent nivolumab dosing continued until RECIST PD while on nivolumab. The primary objective was feasibility of intermittent nivolumab, defined as the proportion of patients eligible for intermittent therapy who elect to receive intermittent nivolumab. Intermittent nivolumab would be considered "feasible" if the acceptance rate was ≥80%. Forty patients provides > 95% power with 0.05 type I error, assuming a null acceptance rate of 50%. With the approval of the combination of ipilimumab/nivolumab (April 2018) in front-line mRCC, this cohort was closed prior to completed pre-planned approval., Results: Of the 14 patients enrolled, 13 (93%) were male with a median age 65. All had a prior nephrectomy and 12 (86%) were intermediate-risk by IMDC criteria. Five patients (36%) met the criteria for the intermittent phase of the trial (median TB decrease 46%) and all agreed to intermittent therapy. With a median follow-up of 48 weeks, only one patient restarted therapy. The four remaining patients have a sustained response for a median of 34 weeks (range, 16-53) off therapy. No patients developed RECIST PD while off therapy., Conclusions: This prospective experience of intermittent nivolumab dosing in mRCC supports further investigation of intermittent immunotherapy dosing strategies in RCC., Trial Registration: NCT03126331 (Intermittent Nivolumab in Metastatic Renal Cell Carcinoma Patients; Date of registration 4/27/2017; https://clinicaltrials.gov/ct2/show/NCT03126331 ).

Background: Clips are often placed to mark axillary nodes with biopsy-confirmed metastases in patients with breast cancer. The evaluation of clipped nodes after chemotherapy can identify patients who have eradication of nodal disease. The goal of this study was to determine whether preoperative fine-needle aspiration (FNA) of clipped nodes after neoadjuvant chemotherapy (NAC) could predict the presence of residual disease., Methods: This prospective registry study enrolled 50 patients with a clip placed to mark nodes with biopsy-confirmed metastases who had completed NAC. Participants underwent FNA of the clipped node before seed-localized lymph node excision. FNA pathology was compared with surgical pathology., Results: There were 36 patients (72%) with residual disease on surgical pathology: 3 (8%) had a nondiagnostic aspirate, carcinoma was seen in 14 (39%), and 19 (53%) had a false-negative result. The sensitivity of FNA was 42.4%, its specificity was 100%, and its negative predictive value was 40.6%. In a univariate analysis, the odds of a true-positive result increased significantly with the mean initial size of the clipped node (odds ratio [OR], 4.3; P = .004) and the size of the metastatic focus after NAC (OR, 1.3; P = 0.003), whereas normalization of nodes after chemotherapy (OR, 0.1) and a lack of response on ultrasound (OR, 0.11) were associated with a false-negative result (P = .01)., Conclusions: FNA of marked nodes after chemotherapy has a high false-negative rate. This highlights the need for surgical staging of the axilla after NAC to assess the response., (© 2018 American Cancer Society.)

Traditionally, drug development has evaluated dose, safety, activity, and comparative benefit in a sequence of phases using trial designs and endpoints specifically devised for each phase. Innovations in drug development seek to consolidate the phases and rapidly expand accrual with "seamless" trial designs. Although consolidation and rapid accrual may yield efficiencies, widespread use of seamless first-in-human (FiH) trials without careful consideration of objectives, statistical analysis plans, or trial oversight raises concerns. A working group formed by the National Cancer Institute convened to consider and discuss opportunities and challenges for such trials as well as encourage responsible use of these designs. We reviewed all abstracts presented at American Society of Clinical Oncology annual meetings from 2010 to 2017 for FiH trials enrolling at least 100 patients. We identified 1786 early-phase trials enrolling 57 559 adult patients. Fifty-one of the trials (2.9%) investigated 50 investigational new drugs, were seamless, and accounted for 14.6% of the total patients. The seamless trials included a median of 3 (range = 1-13) expansion cohorts. The overall risk of clinically significant treatment-related adverse events (grade 3-4) was 49.1% (range = 0.0-100%), and seven studies reported at least one toxic death. Rapid expansion of FiH trials may lead to earlier drug approval and corresponding widespread patient access to active therapeutics. Nevertheless, seamless designs must adhere to established ethical, scientific, and statistical standards. Protocols should include prospectively planned analyses of efficacy in disease- or biomarker-defined cohorts of sufficient rigor to support accelerated approval., (© The Author(s) 2018. Published by Oxford University Press.)

Purpose: Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous disease with variable presentations and natural histories of disease. We hypothesized that different morphologic characteristics of PDAC tumors on diagnostic computed tomography (CT) scans would reflect their underlying biology., Experimental Design: We developed a quantitative method to categorize the PDAC morphology on pretherapy CT scans from multiple datasets of patients with resectable and metastatic disease and correlated these patterns with clinical/pathologic measurements. We modeled macroscopic lesion growth computationally to test the effects of stroma on morphologic patterns, hypothesizing that the balance of proliferation and local migration rates of the cancer cells would determine tumor morphology., Results: In localized and metastatic PDAC, quantifying the change in enhancement on CT scans at the interface between tumor and parenchyma (delta) demonstrated that patients with conspicuous (high-delta) tumors had significantly less stroma, higher likelihood of multiple common pathway mutations, more mesenchymal features, higher likelihood of early distant metastasis, and shorter survival times compared with those with inconspicuous (low-delta) tumors. Pathologic measurements of stromal and mesenchymal features of the tumors supported the mathematical model's underlying theory for PDAC growth., Conclusions: At baseline diagnosis, a visually striking and quantifiable CT imaging feature reflects the molecular and pathological heterogeneity of PDAC, and may be used to stratify patients into distinct subtypes. Moreover, growth patterns of PDAC may be described using physical principles, enabling new insights into diagnosis and treatment of this deadly disease., (©2018 American Association for Cancer Research.)

Purpose: To assess whether radiation treatment modality with proton beam therapy (PBT) or intensity-modulated radiation therapy (IMRT) is associated with lymphopenia in patients treated with definitive chemoradiation for esophageal cancer., Methods and Materials: Patients with esophageal cancer treated with bimodality therapy (n = 448) between 2004 and 2016 were retrospectively reviewed. Patients treated with PBT were matched by propensity score with those treated with IMRT, based on key patient and disease factors, and stratified by clinical disease stage. Patients who developed early, distant metastatic disease within 1 month of completing radiation were excluded. Univariable and multivariable logistic regression were used to identify variables associated with increased risk of grade 4 lymphopenia. Multivariable Cox proportional hazards regression was used to assess factors associated with overall survival, disease-free survival, and locoregional relapse-free survival., Results: Patients who had IMRT and PBT matched by propensity score (n = 220) were not different with respect to age, sex, stage, performance status, tumor location, histology, tumor target volume, or induction chemotherapy. Treatment with IMRT, compared with PBT (odds ratio [OR], 2.13; 95% confidence interval [95% CI], 1.19-3.81; P = .01), increased age (OR, 1.039/y increase; 95% CI, 1.003-1.076; P = .03), and greater planning target volume (OR, 3.47 per 1-unit increase in log (planning target volume); 95% CI, 1.67-7.21; P < .001), was associated with increased risk of grade 4 lymphopenia. Radiation modality was associated with lymphocyte reduction in patients with tumors in the lower esophagus ( P = .005) but not for those with tumors in the upper or middle esophagus ( P = 0.32)., Conclusions: In patients with esophageal cancer treated with definitive chemoradiation, PBT reduces the risk of severe, treatment-related lymphopenia, particularly in tumors of the lower esophagus., Competing Interests: Conflicts of Interest: The authors have no conflicts of interest relevant to the current work. B.P.H. reports a consultantship with Ignyta, Inc (San Diego, California), outside the submitted work. S.H.L. reports grants from Elekta (Stockholm, Sweden), STCube Pharmaceuticals (Gaithersburg, Maryland), Hitachi Chemicals (Tokyo, Japan), Peregrine Pharmaceuticals (Tustin, California), and honorarium from AstraZeneca (Cambridge, United Kingdom), outside the submitted work.