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BackgroundThe National Cancer Institute Moonshot research initiative calls for improvements in the analysis and reporting of treatment toxicity to advise key stakeholders on treatment tolerability and inform regulatory and clinical decision making. This study illustrates alternative approaches to toxicity evaluation using the National Surgical Adjuvant Breast and Bowel Project R-04 clinical trial as an example.MethodsNational Surgical Adjuvant Breast and Bowel Project R-04 was a neoadjuvant chemoradiation trial in stage II-III rectal cancer patients. A 2 x 2 factorial design was used to evaluate whether the addition of oxaliplatin (Oxa) to 5-fluorouracil (5FU) or capecitabine (Cape) with radiation therapy improved local-regional tumor control. The toxicity index (TI), which accounts for the frequency and severity of toxicities, was compared across treatments using multivariable probabilistic index models, where Pr A

Background: Cancer screening trials have required large sample sizes and long time-horizons to demonstrate cancer mortality reductions, the primary goal of cancer screening. We examine assumptions and potential power gains from exploiting information from testing control-arm specimens, which we call the "intended effect" (IE) analysis that we explain in detail herein. The IE analysis is particularly suited to tests that can be conducted on stored specimens in the control arm, such as stored blood for multicancer detection (MCD) tests., Methods: We simulated hypothetical MCD screening trials to compare power and sample size for the standard vs IE analysis. Under two assumptions that we detail herein, we projected the IE analysis for 3 existing screening trials (National Lung Screening Trial [NLST], Minnesota Colon Cancer Control Study [MINN-FOBT-A], and Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial-colorectal component [PLCO-CRC])., Results: Compared with the standard analysis for the 3 existing trials, the IE design could have reduced cancer-specific mortality P values 6-fold (NLST), 33-fold (MINN-FOBT-A), or 260 000-fold (PLCO-CRC) or, alternately, reduced sample size (90% power) by 25% (NLST), 47% (MINN-FOBT-A), or 63% (PLCO-CRC). For potential MCD trial designs requiring 100 000 subjects per arm to achieve 90% power for multicancer mortality for the standard analysis, the IE analysis achieves 90% power for only 37 500-50 000 per arm, depending on assumptions concerning control-arm test-positives., Conclusions: Testing stored specimens in the control arm of screening trials to conduct the IE analysis could substantially increase power to reduce sample size or accelerate trials and could provide particularly strong power gains for MCD tests., (Published by Oxford University Press 2024.)

An overview of proceedings, findings, and recommendations from the workshop on "Advancing Symptom Science Through Symptom Cluster Research" sponsored by the National Institute of Nursing Research (NINR) and the Office of Rare Diseases Research, National Center for Advancing Translational Sciences, is presented. This workshop engaged an expert panel in an evidenced-based discussion regarding the state of the science of symptom clusters in chronic conditions including cancer and other rare diseases. An interdisciplinary working group from the extramural research community representing nursing, medicine, oncology, psychology, and bioinformatics was convened at the National Institutes of Health. Based on expertise, members were divided into teams to address key areas: defining characteristics of symptom clusters, priority symptom clusters and underlying mechanisms, measurement issues, targeted interventions, and new analytic strategies. For each area, the evidence was synthesized, limitations and gaps identified, and recommendations for future research delineated. The majority of findings in each area were from studies of oncology patients. However, increasing evidence suggests that symptom clusters occur in patients with other chronic conditions (eg, pulmonary, cardiac, and end-stage renal disease). Nonetheless, symptom cluster research is extremely limited and scientists are just beginning to understand how to investigate symptom clusters by developing frameworks and new methods and approaches. With a focus on personalized care, an understanding of individual susceptibility to symptoms and whether a "driving" symptom exists that triggers other symptoms in the cluster is needed. Also, research aimed at identifying the mechanisms that underlie symptom clusters is essential to developing targeted interventions.

Approaches to reduce the global burden of cancer include two major strategies: screening and early detection and active preventive intervention. The latter is the topic of this Commentary and spans a broad range of activities. The genetic heterogeneity and complexity of advanced cancers strongly support the rationale for early interruption of the carcinogenic process and an enhanced focus on prevention as a priority strategy to reduce the burden of cancer; however, the focus of cancer prevention management should be on individuals at high risk and on primary localized disease in which screening and detection should also play a vital role. The timing and dose of (chemo-)preventive intervention also affects response. The intervention may be ineffective if the target population is very high risk or already presenting with preneoplastic lesions with cellular changes that cannot be reversed. The field needs to move beyond general concepts of carcinogenesis to targeted organ site prevention approaches in patients at high risk, as is currently being done for breast and colorectal cancers. Establishing the benefit of new cancer preventive interventions will take years and possibly decades, depending on the outcome being evaluated. We also propose that comparative effectiveness research designs and the value of information obtained from large-scale prevention studies are necessary in order for preventive interventions to become a routine part of cancer management.

The aim of this review was to highlight why the use of master protocols trial design is particularly useful for radiotherapy intervention trials where complex setup pathways (including quality assurance, user training, and integrating multiple modalities of treatment) may hinder clinical advances. We carried out a systematic review according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, reviewing the findings using a landscape analysis. Results were summarized descriptively, reporting on trial characteristics highlighting the benefits, limitations, and challenges of developing and implementing radiotherapy master protocols, with three case studies selected to explore these issues in more detail. Twelve studies were suitable for inclusion (4 platform trials, 3 umbrella trials, and 5 basket trials), evaluating a mix of solid tumor sites in both curative and palliative settings. The interventions were categorized into 1) novel agent and radiotherapy combinations; 2) radiotherapy dose personalization; and 3) device evaluation, with a case study provided for each intervention. Benefits of master protocol trials for radiotherapy intervention include protocol efficiency for implementation of novel radiotherapy techniques; accelerating the evaluation of novel agent drug and radiotherapy combinations; and more efficient translational research opportunities, leading to cost savings and research efficiency to improve patient outcomes. Master protocols offer an innovative platform under which multiple clinical questions can be addressed within a single trial. Due to the complexity of radiotherapy trial setup, cost and research efficiency savings may be more apparent than in systemic treatment trials. Use of this research approach may be the change needed to push forward oncological innovation within radiation oncology., (© The Author(s) 2024. Published by Oxford University Press.)

There is growing interest in multicancer detection tests, which identify molecular signals in the blood that indicate a potential preclinical cancer. A key stage in evaluating these tests is a prediagnostic performance study, in which investigators store specimens from asymptomatic individuals and later test stored specimens from patients with cancer and a random sample of controls to determine predictive performance. Performance metrics include rates of cancer-specific true-positive and false-positive findings and a cancer-specific positive predictive value, with the latter compared with a decision-analytic threshold. The sample size trade-off method, which trades imprecise targeting of the true-positive rate for precise targeting of a zero-false-positive rate can substantially reduce sample size while increasing the lower bound of the positive predictive value. For a 1-year follow-up, with ovarian cancer as the rarest cancer considered, the sample size trade-off method yields a sample size of 163 000 compared with a sample size of 720 000, based on standard calculations. These design and analysis recommendations should be considered in planning a specimen repository and in the prediagnostic evaluation of multicancer detection tests., (Published by Oxford University Press 2024.)

Over the past decades, some scientific progress has been made in understanding and treating cancer-related fatigue (CRF). However, three major problems have limited further progress: lack of agreement about measurement, inadequate understanding of the underlying biology, and problems in the conduct of clinical trials for CRF. This commentary reports the recommendations of a National Cancer Institute Clinical Trials Planning Meeting and an ongoing National Cancer Institute working group to address these problems so that high-priority research and clinical trials can be conducted to advance the science of CRF and its treatment. Recommendations to address measurement issues included revising the current case definition to reflect more rigorous criteria, adopting the Patient Reported Outcomes Measurement Information System fatigue scales as standard measures of CRF, and linking legacy measures to the scales. With regard to the biology of CRF, the group identified the need for longitudinal research to examine biobehavioral mechanisms underlying CRF and testing mechanistic hypotheses within the context of intervention research. To address clinical trial issues, recommendations included using only placebo-controlled trial designs. setting eligibility to minimize sample heterogeneity or enable subgroup analysis, establishing a CRF severity threshold for participation in clinical trials, conducting dissemination trials of efficacious interventions (such as exercise), and combining nonpharmacologic and pharmacologic interventions to exploit the potential synergy between these approaches. Accomplishing these goals has the potential to advance the science of CRF and improve the clinical management of this troubling symptom.

Although progression-based endpoints, such as progression-free survival, are often key clinical trial endpoints for anticancer agents, the clinical meaning of "objective progression" is much less certain. As scrutiny of progression-based endpoints in clinical trials increases, it should be remembered that the Response Evaluation Criteria In Solid Tumors (RECIST) progression criteria were not developed as a surrogate for survival. Now that progression-free survival has come to be an increasingly important trial endpoint, the criteria that define progression deserve critical evaluation to determine whether alternate definitions of progression might facilitate the development of stronger surrogate endpoints and more meaningful trial results. In this commentary, we review the genesis of the criteria for progression, highlight recent data that question their value as a marker of treatment failure, and advocate for several research strategies that could lay the groundwork for a clinically validated definition of disease progression in solid tumor oncology.

BackgroundTraditional prognostic factors for survival and treatment response of patients with breast cancer do not fully account for observed survival variation. We used available genotype data from a previously conducted two-stage, breast cancer susceptibility genome-wide association study (ie, Studies of Epidemiology and Risk factors in Cancer Heredity [SEARCH]) to investigate associations between variation in germline DNA and overall survival.MethodsWe evaluated possible associations between overall survival after a breast cancer diagnosis and 10 621 germline single-nucleotide polymorphisms (SNPs) from up to 3761 patients with invasive breast cancer (including 647 deaths and 26 978 person-years at risk) that were genotyped previously in the SEARCH study with high-density oligonucleotide microarrays (ie, hypothesis-generating set). Associations with all-cause mortality were assessed for each SNP by use of Cox regression analysis, generating a per rare allele hazard ratio (HR). To validate putative associations, we used patient genotype information that had been obtained with 5' nuclease assay or mass spectrometry and overall survival information for up to 14 096 patients with invasive breast cancer (including 2303 deaths and 70 019 person-years at risk) from 15 international case-control studies (ie, validation set). Fixed-effects meta-analysis was used to generate an overall effect estimate in the validation dataset and in combined SEARCH and validation datasets. All statistical tests were two-sided.ResultsIn the hypothesis-generating dataset, SNP rs4778137 (C>G) of the OCA2 gene at 15q13.1 was statistically significantly associated with overall survival among patients with estrogen receptor-negative tumors, with the rare G allele being associated with increased overall survival (HR of death per rare allele carried = 0.56, 95% confidence interval [CI] = 0.41 to 0.75, P = 9.2 x 10(-5)). This association was also observed in the validation dataset (HR of death per rare allele carried = 0.88, 95% CI = 0.78 to 0.99, P = .03) and in the combined dataset (HR of death per rare allele carried = 0.82, 95% CI = 0.73 to 0.92, P = 5 x 10(-4)).ConclusionThe rare G allele of the OCA2 polymorphism, rs4778137, may be associated with improved overall survival among patients with estrogen receptor-negative breast cancer.

BackgroundAlthough many tools for the assessment of prostate cancer risk have been published, most are designed to predict only biochemical recurrence, usually after a single specified treatment. We assessed the accuracy of the Cancer of the Prostate Risk Assessment (CAPRA) score, which was validated previously to predict pathological and biochemical outcomes after radical prostatectomy, to predict metastases, prostate cancer-specific mortality, and all-cause mortality.MethodsWe studied 10 627 men with clinically localized prostate cancer in the Cancer of the Prostate Strategic Urologic Research Endeavor registry, who underwent primary radical prostatectomy, radiation therapy (external beam or interstitial), androgen deprivation monotherapy, or watchful waiting/active surveillance, and had at least 6 months of follow-up after treatment. CAPRA scores were calculated at diagnosis from the prostate-specific antigen level, Gleason score, percentage of biopsy cores that were positive for cancer, clinical tumor stage, and age at diagnosis. Survival was studied with Kaplan-Meier analyses. Associations between increasing CAPRA scores and bone metastasis, cancer-specific mortality, and all-cause mortality were examined by use of proportional hazards regression, with adjustment for primary treatment; for all-cause mortality, the analysis also included adjustment for age and comorbidity. Accuracy of the CAPRA score was assessed with the concordance (c)-index.ResultsAmong the 10 627 patients, 311 (2.9%) men developed bone metastases, 251 (2.4%) died of prostate cancer, and 1582 (14.9%) died of other causes. Each single-point increase in the CAPRA score was associated with increased bone metastases (hazard ratio [HR] for bone metastases = 1.47, 95% confidence interval [CI] = 1.39 to 1.56), cancer-specific mortality (HR for prostate cancer death = 1.39, 95% CI = 1.31 to 1.48), and all-cause mortality (HR for death = 1.13, 95% CI = 1.10 to 1.16). The CAPRA score was accurate for predicting metastases (c-index = 0.78), cancer-specific mortality (c-index = 0.80), and all-cause mortality (c-index = 0.71).ConclusionsIn a large cohort of patients with clinically localized prostate cancer who were managed with one of five primary modalities, the CAPRA score predicted clinical prostate cancer endpoints with good accuracy. These results support the value of the CAPRA score as a risk assessment and stratification tool for both research studies and clinical practice.

BackgroundResults from randomized trials indicate that treatment with tamoxifen or chemotherapy for primary breast cancer reduces the risk for contralateral breast cancer. However, less is known about how long the risk is reduced and the impact of factors such as age and menopausal status.MethodsThe study included 634 women with contralateral breast cancer (case patients) and 1158 women with unilateral breast cancer (control subjects) from the Women's Environment, Cancer and Radiation Epidemiology Study. The women were younger than age 55 when they were first diagnosed with breast cancer during 1985-1999. Rate ratios (RRs) and 95% confidence intervals (CIs) for contralateral breast cancer after treatment with chemotherapy or tamoxifen were assessed by multivariable adjusted conditional logistic regression analyses.ResultsChemotherapy was associated with a lower risk for contralateral breast cancer (RR = 0.57, 95% CI = 0.42 to 0.75) than no chemotherapy. A statistically significant association between chemotherapy and reduced risk for contralateral breast cancer persisted up to 10 years after the first breast cancer diagnosis and was stronger among women who became postmenopausal within 1 year of the first breast cancer diagnosis (RR = 0.28, 95% CI = 0.11 to 0.76). Tamoxifen use was also associated with reduced risk for contralateral breast cancer (RR = 0.66, 95% CI = 0.50 to 0.88) compared with no use, and the association was statistically significant for 5 years after the first diagnosis.ConclusionThe associations between chemotherapy and tamoxifen treatment and reduced risk for contralateral breast cancer appear to continue for 10 and 5 years, respectively, after the initial breast cancer is diagnosed. Ovarian suppression may have a role in the association between chemotherapy and reduced risk for contralateral breast cancer.

BackgroundEpidemiologic studies of the association between nonsteroidal anti-inflammatory drugs (NSAIDs), such as aspirin and ibuprofen, and breast cancer risk have yielded inconsistent results. We investigated the association of NSAID use with risk of breast cancer in the California Teachers Study cohort, with special attention to risk of specific breast cancer subtypes and to type of NSAID used.MethodsWe analyzed data on 114 460 women in the California Teachers Study cohort who were aged 22 to 85 years and free of breast cancer at baseline in 1995 to 1996. Information on frequency and duration of NSAID use was collected through a self-administered questionnaire. A total of 2391 women were diagnosed with breast cancer during the follow-up period from 1995 to 2001. We used Cox proportional hazards regression to estimate relative risks (RR) and 95% confidence intervals (CI) of breast cancer subtypes with NSAID use.ResultsNeither regular use (more than once a week) of any NSAID (aspirin and ibuprofen combined) nor regular use of aspirin was associated with breast cancer risk (RR = 1.09, 95% CI = 0.97 to 1.21 for daily versus no regular use of NSAIDs and RR = 0.98, 95% CI = 0.86 to 1.13 for daily versus no regular use of aspirin). However, long-term (> or = 5 years) daily aspirin users had a non-statistically significant decreased risk of estrogen receptor and progesterone receptor (ER/PR)-positive breast cancer (RR = 0.80, 95% CI = 0.62 to 1.03). In contrast, we observed a statistically significantly increased risk of ER/PR-negative breast cancer with long-term daily use of aspirin (RR = 1.81, 95% CI = 1.12 to 2.92). In this population, 11 fewer ER/PR-positive breast cancer cases and seven excess ER/PR-negative breast cancer cases may be due to daily long-term aspirin use among 2391 breast cancer cases observed over 6 years if the association were proven to be causal. Long-term daily use of ibuprofen was also associated with an increased risk of breast cancer (RR = 1.51, 95% CI = 1.17 to 1.95), particularly of nonlocalized tumors (RR = 1.92, 95% CI = 1.24 to 2.97). If causality were subsequently proven, 16 of the observed 2391 breast cancer cases and 8 of the 713 non-localized breast cancer cases would be attributable to long-term daily use of ibuprofen.ConclusionsLong-term daily use of NSAIDs was not associated with breast cancer risk overall. Ibuprofen use was associated with an increased risk of breast cancer, and long-term daily aspirin use was associated with an increased risk of ER/PR-negative breast cancer. However, it is not clear if the observed association is causal.

BackgroundThere is great interest in whether exposure to tobacco smoke, a substance containing human carcinogens, may contribute to a woman's risk of developing breast cancer. To date, literature addressing this question has been mixed, and the question has seldom been examined in large prospective study designs.MethodsIn a 1995 baseline survey, 116 544 members of the California Teachers Study (CTS) cohort, with no previous breast cancer diagnosis and living in the state at initial contact, reported their smoking status. From entry into the cohort through 2000, 2005 study participants were newly diagnosed with invasive breast cancer. We estimated hazard ratios (HRs) for breast cancer associated with several active smoking and household passive smoking variables using Cox proportional hazards models.ResultsIrrespective of whether we included passive smokers in the reference category, the incidence of breast cancer among current smokers was higher than that among never smokers (HR = 1.32, 95% confidence interval [CI] = 1.10 to 1.57 relative to all never smokers; HR = 1.25, 95% CI = 1.02 to 1.53 relative to only those never smokers who were unexposed to household passive smoking). Among active smokers, breast cancer risks were statistically significantly increased, compared with all never smokers, among women who started smoking at a younger age, who began smoking at least 5 years before their first full-term pregnancy, or who had longer duration or greater intensity of smoking. Current smoking was associated with increased breast cancer risk relative to all nonsmokers in women without a family history of breast cancer but not among women with such a family history. Breast cancer risks among never smokers reporting household passive smoking exposure were not greater than those among never smokers reporting no such exposure.ConclusionOur study provides evidence that active smoking may play a role in breast cancer etiology and suggests that further research into the connection is warranted, especially with respect to genetic susceptibilities.

Background: The patterns and determinants of long-term income among adolescent and young adult (AYA) cancer survivors, and the differences compared with peers, have not yet been fully explored. This study investigated the long-term effects of cancer on the income of AYA cancer survivors., Methods: The Netherlands Cancer Registry identified all AYA cancer patients (aged 18-39 years) diagnosed in 2013 and alive 5 years postdiagnosis. Clinical data of the selected AYA patients were linked to individual, administrative real-world labor market data of Statistics Netherlands. The control group consisted of a random sample of individuals of the same age, sex, and migration background without cancer. Data on 2434 AYA cancer patients and 9736 controls were collected annually from 2011 until 2019. Changes in income level were measured and compared with the control group using difference-in-difference regression models., Results: AYA cancer survivors experience, on average, an 8.5% decrease in annual earnings, relative to the control population. The effects are statistically significant and permanent (P < .01). Younger AYAs (those aged 18-25 years 15.5% income reduction), married cancer survivors (12.3%), females (11.6%), those diagnosed with stage IV disease (38.1%), and central nervous system (15.7%) cancer patients experienced the largest decline in income, on average, relative to controls, all else constant., Conclusion: Although dependent on the sociodemographic and clinical characteristics, a cancer diagnosis at AYA age has significant implications on the income of cancer patients. Awareness of vulnerable groups and the development of policies to mitigate the financial impact of cancer are critical., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: The traditional more-is-better dose selection paradigm, originally developed for cytotoxic chemotherapeutics, can be problematic when applied to the development of novel molecularly targeted agents. Recognizing this issue, the US Food and Drug Administration initiated Project Optimus to reform the dose optimization and selection paradigm in oncology drug development, emphasizing the need for greater attention to benefit-risk considerations., Methods: We identify different types of phase II/III dose-optimization designs, classified according to trial objectives and endpoint types. Through computer simulations, we examine their operating characteristics and discuss the relevant statistical and design considerations for effective dose optimization., Results: Phase II/III dose-optimization designs are capable of controlling family-wise type I error rates and achieving appropriate statistical power with substantially smaller sample sizes than the conventional approach while also reducing the number of patients who experience toxicity. Depending on the design and scenario, the sample size savings range from 16.6% to 27.3%, with a mean savings of 22.1%., Conclusions: Phase II/III dose-optimization designs offer an efficient way to reduce sample sizes for dose optimization and accelerate the development of targeted agents. However, because of interim dose selection, the phase II/III dose-optimization design presents logistical and operational challenges and requires careful planning and implementation to ensure trial integrity., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

We consider the design of phase II trials evaluating combinations of experimental therapies. In the modern era, many immunotherapy and targeted therapy regimens are being developed as combination regimens, including combinations consisting only of experimental agents. In some clinical or drug development scenarios, it may be difficult to isolate the effect of the individual agents composing a combination of this type, which makes the evaluation of the combination challenging. One such scenario arises when none of the agents making up the experimental combination have demonstrated single-agent activity in the clinical setting of interest. One solution to this problem is to use a randomized comparative trial in which the combination of interest is compared with 1 or both of its component agents, but some modifications to more traditional randomized comparative phase II trials must be made because all arms in such a trial would be experimental. In this manuscript, we present sensible modifications to randomized phase II trial designs that can be used in 2 common drug development scenarios of this type and provide a detailed discussion of the practical aspects of designing these trials. We also include 2 worked examples to further illustrate how to design such a trial., (Published by Oxford University Press 2023.)

Background: Patients with cancer living in rural areas have inferior cancer outcomes; however, studies examining this association use varying definitions of "rural," complicating comparisons and limiting the utility of the results for policy makers and future researchers., Methods: Surveillance, Epidemiology, and End Results data (2000-2016) were used to assess risk of cancer mortality and mortality from any cause across 4 definitions of rurality: Urban Influence codes (UIC), National Center for Health Statistics (NCHS), Rural-Urban continuum codes (RUCC), and Index of Relative Rurality. Binary (urban vs rural) and ternary (urban, micropolitan, rural) definitions were evaluated. Multivariable parametric survival models estimated hazards of mortality overall and among 3 cancer groupings: screening related, obesity related, and tobacco related. Definition agreement was also assessed., Results: Overall, 3 788 273 patients with an incident cancer representing 605 counties were identified. There was little discordance between binary definitions of rural vs urban and moderate agreement at the 3 levels. Adjusted models using binary definitions revealed 15% to 17% greater hazard of cancer mortality in rural compared with urban. At the 3 levels when comparing rural with metropolitan, RUCC and NCHS saw similarly increased hazard ratios; however, Index of Relative Rurality did not. Screening-related cancers saw the highest hazards of mortality and the largest divergence between definitions. Obesity-related and tobacco-related cancers saw similarly increased hazards of mortality at the binary and ternary levels., Conclusions: Hazard of death is similar across binary definitions; however, this differed when categorized as ternary or continuous, especially among screening-related cancers. Results suggest that study purpose should direct choice of definitions and categorization., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Generating actionable research findings quickly and efficiently is critical for improving the delivery of cancer-related care and outcomes. To address this issue, the National Cancer Institute convened subject matter experts, researchers, clinicians, and patients for a 2-day virtual meeting in February 2022. The purpose of this meeting was to identify how rapid cycle interventional research methods can be used to generate findings useful in improving routine clinical practice. The meeting yielded an initial conceptualization of rapid cycle interventional research as being comprised of 6 key elements: use of iterative study designs; reliance on proximal primary outcomes; early and continued engagement with community and clinical partners; use of existing data sources to measure primary outcomes; facilitative features of the study setting and context; and consideration of appropriate rigor relative to intended use of findings. The meeting also identified the types of study designs that can be leveraged to conduct rapid cycle interventional research and provided examples of these; considered this approach from the perspective of key partners; described the clinical and data infrastructure, research resources, and key collaborations needed to support this work; identified research topics best addressed using this approach; and considered needed methodological advances. The National Cancer Institute is committed to exploring opportunities to encourage further development and application of this research approach as a means for better promoting improvements in the delivery of cancer-related care., (Published by Oxford University Press 2023.)

The goal of dose optimization during drug development is to identify a dose that preserves clinical benefit with optimal tolerability. Traditionally, the maximum tolerated dose in a small phase I dose escalation study is used in the phase II trial assessing clinical activity of the agent. Although it is possible that this dose level could be altered in the phase II trial if an unexpected level of toxicity is seen, no formal dose optimization has routinely been incorporated into later stages of drug development. Recently it has been suggested that formal dose optimization (involving randomly assigning patients between 2 or more dose levels) be routinely performed early in drug development, even before it is known that the experimental therapy has any clinical activity at any dose level. We consider the relative merits of performing dose optimization earlier vs later in the drug development process and demonstrate that a considerable number of patients may be exposed to ineffective therapies unless dose optimization is delayed until after clinical activity or benefit of the new agent has been established. We conclude that patient and public health interests may be better served by conducting dose optimization after (or during) phase III evaluation, with some exceptions when dose optimization should be performed after activity shown in phase II evaluation., (Published by Oxford University Press 2022.)

This brief report introduces the Cancer Outcomes and Survivorship domain in the PhenX Toolkit (consensus measures for Phenotypes and eXposures), which includes 15 validated measurement protocols for cancer survivorship research that were recommended for inclusion in this publicly available resource. Developed with input from the scientific community, the domain provides researchers with well-established measurement protocols for evaluating physical and psychological effects, financial toxicity, and patient experiences with cancer care. The PhenX Toolkit, funded by the National Human Genome Research Institute since 2007, is an online resource that provides high-quality standard measurement protocols for a wide range of research areas (eg, smoking cessation, harm reduction and biomarkers, and social determinants of health). Use of the PhenX Cancer Survivorship Outcomes and Survivorship domain can simplify the selection of measurement protocols, data sharing, and comparisons across studies investigating the cancer survivorship experience., (© The Author(s) 2023. Published by Oxford University Press.)

Blood-based assays using various technologies and biomarkers are in commercial development for the purpose of detecting multiple cancer types concurrently at an early stage of disease. These multicancer early detection (MCED) assays have the potential to improve the detection of cancers, particularly those for which no current screening modality exists. However, the unknown clinical benefits and harms of using MCED assays for cancer screening necessitate the development and implementation of a randomized controlled trial (RCT) to ascertain their clinical effectiveness. This was the consensus of experts at a National Cancer Institute-hosted workshop to discuss initial design concepts for such a trial. Using these assays to screen simultaneously for multiple cancers poses novel uncertainties for patient care compared with conventional screening tests for single cancers, such as establishing the diagnostic workup to confirm the presence of cancer at any organ site; clarifying appropriate follow-up for a positive assay for which there is no definitive diagnosis; identifying potential harms such as overdiagnosis of indolent disease; determining clinically effective and efficient strategies for disseminating MCED screening in real-world practice; and understanding the ethical implications, such as potentially alleviating or exacerbating existing health disparities. These assays present new and complex challenges for designing an RCT. Issues that emerged from the meeting centered around the need for a flexibly designed, clinical utility RCT to rigorously capture the evidence required to fully understand the net benefit of this promising technology. Specific topic areas were endpoints, screening protocols, recruitment, diagnostic pathway, pilot phase, data elements, specimen collection, and ethical considerations., (Published by Oxford University Press 2022.)

As precision medicine becomes more precise, the sizes of the molecularly targeted subpopulations become increasingly smaller. This can make it challenging to conduct randomized clinical trials of the targeted therapies in a timely manner. To help with this problem of a small patient subpopulation, a study design that is frequently proposed is to conduct a small randomized clinical trial (RCT) with the intent of augmenting the RCT control arm data with historical data from a set of patients who have received the control treatment outside the RCT (historical control data). In particular, strategies have been developed that compare the treatment outcomes across the cohorts of patients treated with the standard (control) treatment to guide the use of the historical data in the analysis; this can lessen the potential well-known biases of using historical controls without any randomization. Using some simple examples and completed studies, we demonstrate in this commentary that these strategies are unlikely to be useful in precision medicine applications., (Published by Oxford University Press 2022.)

Meta-analysis based on individual participant data (IPD) is a powerful methodology for synthesizing evidence by combining information drawn from multiple trials. Hitherto, its principal application has been in questions of clinical management, but an increasingly important use is in clarifying trials methodology, for instance in the selection of endpoints, as discussed in this review. In oncology, the Aide et Recherche en Cancérologie Digestive (ARCAD) Metastatic Colorectal Cancer Database is a leader in the use of IPD-based meta-analysis in methodological research. The ARCAD database contains IPD from more than 38 000 patients enrolled in 46 studies and continues to collect phase III trial data. Here, we review the principal findings of the ARCAD project in respect of endpoint selection and examine their implications for cancer trials. Analysis of the database has confirmed that progression-free survival (PFS) is no longer a valid surrogate endpoint predictive of overall survival in the first-line treatment of colorectal cancer. Nonetheless, PFS remains an endpoint of choice for most first-line trials in metastatic colorectal cancer and other solid tumors. Only substantial PFS effects are likely to translate into clinically meaningful benefits, and accordingly, we advocate an oncology research model designed to identify highly effective treatments in carefully defined patient groups. We also review the use of the ARCAD database in assessing clinical response including novel response metrics and prognostic markers. These studies demonstrate the value of IPD as a tool for methodological studies and provide a reference point for the expansion of this approach within clinical cancer research., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Some concerns have been raised about potential bias in patient-reported outcome (PRO) results from open-label cancer randomized controlled trials (RCTs). We investigated if open-label trials favor the experimental treatment over the standard treatment more frequently than blinded trials. We also examined if the effect of blinding differs for distal vs more proximal PROs. We assessed 538 RCTs with a PRO endpoint conducted in the most prevalent cancers, of which 366 (68.0%) were open-label, 148 (27.5%) were blinded, and 24 (4.5%) were categorized as unclear. In our multivariable logistic regression model, we did not observe a statistically significant association of the independent variable treatment concealment (blinded vs open-label) on the dependent variable measuring the proportion of trials favoring the experimental treatment (adjusted odds ratio = 1.19, 95% confidence interval = 0.79 to 1.79; 2-sided P = .40). This was also the case when comparing distal and proximal PROs. Our findings provide novel evidence-based data that support the validity of PRO results from open-label cancer RCTs., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

In this presentation, issues that influenced the development of policies for inclusion of quality of life end points in certain Southwest Oncology Group clinical trials are reviewed. The key policies recommended by us and adopted by the Cancer Control Research Committee of the Southwest Oncology Group are as follows: (a) Begin assessment of quality of life in specific types of phase III protocols. (b) Always measure physical functioning, emotional functioning, symptoms (general and protocol specific), and global quality of life separately. (c) Include measures of social functioning and additional protocol-specific measures if resources permit. (d) Use patient-based questionnaires with psychometric properties that have been documented in published studies. In this review, we also recommend specific questionnaires. Our recommendations may prove useful for other cancer clinical trials groups and for multi-institution trials of treatment for chronic diseases.

Efficient biomarker-driven randomized clinical trials are a key tool for implementing precision oncology. A commonly used biomarker phase III design is focused on testing the treatment effect in biomarker-positive and overall study populations. This approach may result in recommending new treatments to biomarker-negative patients when these treatments have no benefit for these patients., (Published by Oxford University Press 2021. This work is written by US Government employees and is in the public domain in the US.)

Older adults continue to be underrepresented in cancer clinical trials, despite most cancer occurrence peaking in the later decades of life. Consequently, diagnostic and management strategies are commonly extrapolated from data on younger patients, thus challenging the delivery of informed cancer care in this patient population. Several recommendations and calls to action have been released by cancer societies, advocacy organizations, and regulatory agencies to guide inclusion of older adults in clinical trials. Effective implementation, however, requires awareness and close collaboration between all stakeholders involved in the clinical trial journey. We herein provide insights and experience from a drug developer on key considerations to optimize participation and retention of older adults in cancer clinical trials and discuss those under 4 key domains: trial eligibility and design, assessments and endpoints, patients and oncologists, and data reporting., (© The Author(s) 2021. Published by Oxford University Press.)

Background: Use of value framework thresholds in the design of clinical trials may increase the proportion of randomized controlled trials that identify clinically meaningful advances for patients. Existing frameworks have not been applied to the research output of a cooperative cancer trials group. We apply value frameworks to the randomized controlled trial output of the Canadian Cancer Trials Group (CCTG)., Methods: Statistical design, study characteristics, and results of all published phase III trials of CCTG were abstracted. We applied the European Society for Medical Oncology-Magnitude of Clinical Benefit Scale (ESMO-MCBS) and American Society of Clinical Oncology Net Health Benefit to study results and the statistical power calculations to identify the proportion of all trials that were designed to detect a substantial clinical benefit., Results: During 1979 to 2017, CCTG published 113 phase III trials; 52.2% (59 of 113) of these trials were positive. One-half (50.4%, 57 of 113) of the trials were conducted in the palliative setting. In 37.2% (42 of 113) of trials, the primary endpoint was overall survival; disease-free survival or progression-free survival was used in 38.9% (44 of 113) of trials. The ESMO-MCBS could be applied to the power calculation for 69 trials; 73.9% (51 of 69) of these trials were designed to detect an effect size that could meet ESMO-MCBS thresholds for substantial benefit. Among the 51 positive trials for which the ESMO-MCBS could be applied, 41.1% (21 of 51) met thresholds for substantial benefit., Conclusions: Most CCTG phase III trials were designed to detect clinically meaningful differences in outcome, although less than one-half of positive trials met the threshold for substantial benefit. Application of value frameworks to the design of clinical trials is practical and may improve research efficiency and treatment options for patients., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)