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An antiaromatic cation of the expanded hexapyrrolohexaazacoronene (HPHAC) 1 + was synthesized by a Vilsmeier-type reaction of the partially unfused HPHAC 2 . X-ray diffraction analysis revealed the formation of a seven-membered ring with a methyne linkage between the pyrrole moieties. Although 1 H NMR spectra, indicating 24π antiaromaticity. Global antiaromaticity was also supported by nucleus-independent chemical shift and anisotropy of the induced current density calculations. Cation + is a monocation, upfield shifts of the peripheral ethyl protons were clearly observed in the 1 H NMR spectra, indicating 24π antiaromaticity. Global antiaromaticity was also supported by nucleus-independent chemical shift and anisotropy of the induced current density calculations. Cation 1 + displayed two reversible oxidations and one irreversible reduction in the cyclic voltammetry measurements. Treatment of 1 + with NOSbF 6 gave aromatic trication 1 3+ with 22π-electron conjugation.

A typical biosimilar study in oncology uses the overall response evaluated at a specific time point as the primary endpoint, which is generally acceptable regulatorily, to assess clinical equivalence between a biosimilar and its reference product. The standard primary endpoint for evaluating an anticancer therapy, progression-free or overall survival would be a secondary endpoint in a biosimilar trial. With a conventional analytic procedure via, for example, hazard ratio to quantify the group difference, it is difficult and challenging to assess clinical equivalence with respect to progression-free or overall survival because the study generally has a limited number of clinical events observed in the study. In this article, we show that an alternative procedure based on the restricted mean survival time, which has been discussed extensively for design and analysis of a general equivalence study, is readily applicable to a biosimilar trial. Unlike the hazard ratio, this procedure provides a clinically interpretable estimate for assessing equivalence. Using the restricted mean survival time as a summary measure of the survival curve will enhance better treatment decision making in adopting a biosimilar product over the reference product., (© The Author(s) 2019. Published by Oxford University Press.)

Purpose: Spending for patients with advanced cancer is substantial. Past efforts to characterize this spending usually have not included patients with recurrence (who may differ from those with de novo stage IV disease) or described which services drive spending., Methods: Using SEER-Medicare data from 2008 to 2013, we identified patients with breast, colorectal, and lung cancer with either de novo stage IV or recurrent advanced cancer. Mean spending/patient/month (2012 US dollars) was estimated from 12 months before to 11 months after diagnosis for all services and by the type of service. We describe the absolute difference in mean monthly spending for de novo versus recurrent patients, and we estimate differences after controlling for type of advanced cancer, year of diagnosis, age, sex, comorbidity, and other factors., Results: We identified 54,982 patients with advanced cancer. Before diagnosis, mean monthly spending was higher for recurrent patients (absolute difference: breast, $1,412; colorectal, $3,002; lung, $2,805; all P < .001), whereas after the diagnosis, it was higher for de novo patients (absolute difference: breast, $2,443; colorectal, $4,844; lung, $2,356; all P < .001). Spending differences were driven by inpatient, physician, and hospice services. Across the 2-year period around the advanced cancer diagnosis, adjusted mean monthly spending was higher for de novo versus recurrent patients (spending ratio: breast, 2.39 [95% CI, 2.05 to 2.77]; colorectal, 2.64 [95% CI, 2.31 to 3.01]; lung, 1.46 [95% CI, 1.30 to 1.65])., Conclusion: Spending for de novo cancer was greater than spending for recurrent advanced cancer. Understanding the patterns and drivers of spending is necessary to design alternative payment models and to improve value.

In randomized clinical trials, the magnitude of the treatment effect is often reported using the hazard ratio (HR) even when the proportional hazards (PH) assumption is not met. Conducting numerical studies, this commentary illustrates how/why the HR estimate via the standard Cox's procedure is difficult to interpret even as an “average” treatment effect for non‐PH cases., Competing Interests: Disclosures of potential conflicts of interest may be found at the end of this article.

Bis(bicyclic) molecules dimethanochrysene and diethanochrysene were prepared by Diels-Alder reaction of the naphthodiyne equivalent with cyclopentadiene and 1,3-cyclohexadiene, respectively. Reaction of dimethanochrysene and 7,9-diphenyl-8H-cyclopent[a]acenaphthylen-8-one resulted in the generation of a fluorescent hydrocarbon in unexpected multistep pericyclic reactions. Syn-oriented diethanochrysene-connected bisporphyrin tweezers was prepared from the reaction of chrysene-bridged syn-dipyrrole with tripyrranedicarbaldehyde. The structure of the receptor and its 1 : 1 complex with C 60 or C 70 was determined by X-ray diffraction analysis. The dihedral angles of the bicyclo[2.2.2]octadiene moieties were narrowed by complexation of the receptor with the fullerenes. The binding affinities of the tweezers with C 60 and C 70 were calculated to be 2.7(4)×10 4 and 8.01(7)×10 4  M -1 , respectively by UV-vis and fluorescence spectroscopy., (© 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Purpose: Hospitalizations are a common occurrence during chemotherapy for advanced cancer. Validated risk stratification tools could facilitate proactive approaches for reducing hospitalizations by identifying at-risk patients., Patients and Methods: We assembled two retrospective cohorts of patients receiving chemotherapy for advanced nonhematologic cancer; cohorts were drawn from three integrated health plans of the Cancer Research Network. We used these cohorts to develop and validate logistic regression models estimating 30-day hospitalization risk after chemotherapy initiation. The development cohort included patients in two health plans from 2005 to 2013. The validation cohort included patients in a third health plan from 2007 to 2016. Candidate predictor variables were derived from clinical data in institutional data warehouses. Models were validated based on the C-statistic, positive predictive value, and negative predictive value. Positive predictive value and negative predictive value were calculated in reference to a prespecified risk threshold (hospitalization risk ≥ 18.0%)., Results: There were 3,606 patients in the development cohort (median age, 63 years) and 634 evaluable patients in the validation cohort (median age, 64 years). Lung cancer was the most common diagnosis in both cohorts (26% and 31%, respectively). The selected risk stratification model included two variables: albumin and sodium. The model C-statistic in the validation cohort was 0.69 (95% CI, 0.62 to 0.75); 39% of patients were classified as high risk according to the prespecified threshold; 30-day hospitalization risk was 24.2% (95% CI, 19.9% to 32.0%) in the high-risk group and 8.7% (95% CI, 6.1% to 12.0%) in the low-risk group., Conclusion: A model based on data elements routinely collected during cancer treatment can reliably identify patients at high risk for hospitalization after chemotherapy initiation. Additional research is necessary to determine whether this model can be deployed to prevent chemotherapy-related hospitalizations.

Synthesis of an azacoronene, in which both pyrrole and azulene moieties are circularly fused, was achieved just in three steps. This new azacoronene exhibited multistep reversible oxidations under electrochemical and chemical conditions. Formation of an aromatic 22π-electron conjugation and a tropylium cation (6π-electron conjugation) in the dicationic state was revealed by the single-crystal X-ray crystallographic analysis as well as the nucleus-independent chemical shift (NICS) and anisotropy of the induced current density (ACID) calculations.

Purpose: We previously developed and validated informatic algorithms that used International Classification of Diseases 9th revision (ICD9)-based diagnostic and procedure codes to detect the presence and timing of cancer recurrence (the RECUR Algorithms). In 2015, ICD10 replaced ICD9 as the worldwide coding standard. To understand the impact of this transition, we evaluated the performance of the RECUR Algorithms after incorporating ICD10 codes., Methods: Using publicly available translation tables along with clinician and other expertise, we updated the algorithms to include ICD10 codes as additional input variables. We evaluated the performance of the algorithms using gold standard recurrence measures associated with a contemporary cohort of patients with stage I to III breast, colorectal, and lung (excluding IIIB) cancer and derived performance measures, including the area under the receiver operating curve, average absolute prediction error, and correct classification rate. These values were compared with the performance measures derived from the validation of the original algorithms., Results: A total of 659 colorectal, 280 lung, and 2,053 breast cancer cases were identified. Area under the receiver operating curve derived from the updated algorithms was 89.0% (95% CI, 82.3% to 95.7%), 88.9% (95% CI, 79.3% to 98.2%), and 80.5% (95% CI, 72.8% to 88.2%) for the colorectal, lung, and breast cancer algorithms, respectively. Average absolute prediction errors for recurrence timing were 2.7 (SE, 11.3%), 2.4 (SE, 10.4%), and 5.6 months (SE, 21.8%), respectively, and timing estimates were within 6 months of actual recurrence for more than 80% of colorectal, more than 90% of lung, and more than 50% of breast cancer cases using the updated algorithm., Conclusion: Performance measures derived from the updated and original algorithms had overlapping confidence intervals, suggesting that the ICD9 to ICD10 transition did not affect the RECUR Algorithm performance.

Objective(s): HIV-positive individuals have elevated rates of anal squamous cell carcinoma (SCC), and sexually transmitted infections with its causative agent, high-risk human papillomavirus, and other oncoviruses including hepatitis B virus (HBV). HBV infection can cause liver cancer, and has been associated with increased risk of some extra-hepatic cancers including biliary tract cancer, pancreatic cancer, and non-Hodgkin lymphoma. Whether HBV is associated with anal SCC risk is unknown., Design: Prospective study of anal SCC risk in HIV-positive and HIV-negative MSM in the Multicenter AIDS Cohort Study from 1984 to 2014., Methods: Poisson regression models were used to examine the association between past or current HBV infection (positive tests for HBV core antibodies, surface antigen, and/or DNA) and anal SCC risk., Results: We observed 53 cases of anal SCC among 5298 participants with 79 334 person-years follow-up. Among HIV-positive men, past or current HBV infection was associated with anal SCC risk in models adjusted for age, CD4+ cell counts, HAART use, and other risk factors [incidence rate ratio (IRR), 95% confidence interval 3.15, 1.27-7.82]. Additional risk factors included immunological parameters 1 and 6 years prior to diagnosis (IRR, 95% confidence interval 2.45, 1.31-4.58 and 2.44, 1.3-4.59 for CD4+ cell counts <500 cells/μl; 2.43, 1.34-4.42 and 2.77, 1.5-5.11 for CD4+ : CD8+ ratios <0.5, respectively). Among HIV-negative men, IRR for prior HBV and anal SCC risk was similar, but NS due to small number of cases., Conclusion: HIV-positive MSM with prior HBV infection have increased anal SCC risk. This population may benefit from screening.

Seed and root hair protective protein (SRPP) is expressed in seeds and root hairs, localized in the cell wall, and involved in cell wall integrity. We analyzed a loss-of-function mutant of SRPP, focusing on siliques and seeds. The srpp-1 plants generated dark brown shrunken seeds at a high rate. The germination rate of these defect seeds of srpp-1 was less than 6%, although apparently normal srpp-1 seeds germinated at a rate of 83%. The production ratio of severe phenotypic seeds was dependent on the growth conditions. When the srpp-1 plants were cultivated at low humidity, the defect ratio was 73%, which was significantly higher than that at normal humidity. Defects of the silique and seeds could be detected on day 7 after pollination and the apical region of the siliques displayed a severe phenotype at a high frequency. Complementation with an SRPP gene under the control of promoters specific to the embryo, seed coat, or valve (carpel) partially rescued the phenotype, and complementation using the SRPP promoter fully rescued the phenotype. Furthermore, overexpression of SRPP enhanced the thermotolerance. After the treatment of seeds at 50 °C for 2 h, the germination rate of the seeds from overexpression with the 35S promoter increased to levels twice that of the wild-type seeds. Under the same conditions, no srpp-1 seeds germinated. These results indicate that SRPP is essential for the production of normal viable seeds in siliques under stress conditions. It is possible that modification of the SRPP gene improves seed integrity.

Background: Lung disease is a common comorbidity in people with HIV/AIDS, independent of smoking status. The effects of marijuana smoking on risk of lung disease in HIV-infected individuals are unclear., Methods: In this prospective cohort study, we quantified lung disease risk among men enrolled in the Multicenter AIDS Cohort Study (MACS), a long-term observational cohort of HIV-infected and uninfected men who have sex with men. Eligible participants were aged ≥30 years with self-reported marijuana and tobacco smoking data from biannual study visits between 1996 and 2014. Pulmonary diagnoses were obtained from self-report and medical records. Analyses were performed using Cox models and Generalized Estimating Equations adjusted for tobacco smoking, CD4 T cell count, and other risk factors., Findings: 1,630 incident pulmonary diagnoses were reported among 1,352 HIV-seropositive and 1,352 HIV-seronegative eligible participants matched for race and baseline age (53,794 total person-visits, median follow-up 10.5 years). 27% of HIV-infected participants reported daily or weekly marijuana smoking for one or more years in follow-up, compared to 18% of uninfected participants (median 4·0 and 4·5 years daily/weekly use, respectively). HIV-infected participants had an increased likelihood of infectious or non-infectious pulmonary diagnoses compared to uninfected participants (33·2% vs. 21·5%, and 20·6% vs. 17·2%, respectively). Among HIV-infected participants, recent marijuana smoking was associated with increased risk of infectious pulmonary diagnoses and chronic bronchitis independent of tobacco smoking and other risk factors for lung disease (hazard ratio [95% confidence interval] 1·43 [1·09-1·86], and 1·54 [1·11-2·13], respectively); these risks were additive in participants smoking both substances. There was no association between marijuana smoking and pulmonary diagnoses in HIV-uninfected participants., Interpretation: In this longitudinal study, long-term marijuana smoking was associated with lung disease independent of tobacco smoking and other risk factors in HIV-infected individuals. These findings could be used to reduce modifiable risks of lung disease in high-risk populations., Competing Interests: Declaration of interests We declare no competing interests.

Purpose: Data from claims and electronic medical records (EMRs) are frequently used to identify clinical events (eg, cancer diagnosis, stroke). However, accurately determining the time of clinical events can be challenging, and the methods used to generate time estimates are underdeveloped. We sought to develop an approach to determine the time of a clinical event-cancer recurrence-using high-dimensional longitudinal structured data., Methods: Manual chart abstraction provided information regarding the actual time of cancer recurrence. These data were linked to claims from Medicare or structured EMR data from the Cancer Research Network, which were used to determine time of recurrence for patients with lung or colorectal cancer. We analyzed the longitudinal profile of codes that could help determine the time of recurrence, adjusted for systematic differences between code dates and recurrence dates, and integrated time estimates from different codes to empirically derive an optimal algorithm., Results: We identified twelve code groups that could help determine the time of recurrence. Using claims data for patients with lung cancer, the optimal algorithm consisted of three code groups and provided an average prediction error of 4.8 months. Using EMR data or applying this approach to patients with colorectal cancer yielded similar results., Conclusion: Time estimates were improved by selecting codes not necessarily the same as those used to identify recurrence, combining time estimates from multiple code groups, and adjusting for systematic bias between code dates and recurrence dates. Improving the accuracy of time estimates for clinical events can facilitate research, quality measurement, and process improvement.

Objective: To address the knowledge gap regarding medical care costs for advanced cancer patients, we compared costs for recurrent versus de novo stage IV breast, colorectal, and lung cancer patients., Data Sources/study Setting: Virtual Data Warehouse (VDW) information from three Kaiser Permanente regions: Colorado, Northwest, and Washington., Study Design: We identified patients aged ≥21 with de novo or recurrent breast (n de novo  = 352; n recurrent  = 765), colorectal (n de novo  = 1,072; n recurrent  = 542), and lung (n de novo  = 4,041; n recurrent  = 340) cancers diagnosed 2000-2012. We estimated average total monthly and annual costs in the 12 months preceding, month of, and 12 months following the index de novo/recurrence date, stratified by age at diagnosis (<65, ≥65). Generalized linear repeated-measures models controlled for demographics and comorbidity., Principal Findings: In the pre-index period, monthly costs were higher for recurrent than for de novo breast (<65: +$2,431; ≥65: +$1,360), colorectal (<65: +$3,219; ≥65: +$2,247), and lung cancer (<65: +$3,086; ≥65: +$2,260) patients. Conversely, during the index and post-index periods, costs were higher for de novo patients. Average total annual pre-index costs were five- to ninefold higher for recurrent versus de novo patients <65., Conclusions: Cost differences by type of advanced cancer and by age suggest heterogeneous patterns of care that merit further investigation., (© Health Research and Educational Trust.)

Immunological parameters that influence susceptibility to virus-associated cancers in HIV-seronegative individuals are unclear. We conducted a case-control cohort study of immunological parameters associated with development of incident virus-associated cancers among 532 HIV-seronegative men who have sex with men (MSM) enrolled in the Multicenter AIDS Cohort Study (MACS) with median (IQR) 21 (8-26) years of follow-up. Thirty-two incident virus-associated cancers (anal cancer, non-Hodgkin lymphoma, liver cancer, other cancers with etiologies linked to human papillomavirus, Epstein-Barr virus, hepatitis B virus, or human herpesvirus-8) were identified among 3,408 HIV-seronegative men in the MACS during 1984-2010. Cases were matched for demographics, smoking, and follow-up to 500 controls without cancer. Mixed-effects and Cox regression models were used to examine associations between nadir or recent CD4, CD8, and white blood cell (WBC) counts or CD4:CD8 ratios and subsequent diagnosis of virus-associated cancers. Men with incident virus-associated cancers had lower CD4 and WBC counts over a 6-year window prior to diagnosis compared to men without cancer (p = 0.001 and 0.03, respectively). Low CD4 cell count and nadir, CD4 count-nadir differential, and CD4:CD8 ratio nadir were associated with increased 2-year risk of incident virus-associated cancers in models adjusted for demographics and smoking (hazard ratios 1.2-1.3 per 100 or 0.1 unit decrease, respectively; p < 0.01). Other associated factors included heavy smoking and past or current hepatitis B virus infection. These findings show that low CD4 cell counts, CD4 nadir, and CD4:CD8 cell ratios are independent predictors for subsequent risk of virus-associated cancers in HIV-seronegative MSM.

Purpose of Review: Adolescents with haematological malignancies within adult services, in the UK from 16 years old, have unique needs and require developmentally targeted services and approaches to care delivery. High-risk intensive treatments are common for this cohort and a better understanding of what individualised supportive and palliative care means in this context is required., Recent Findings: Being known and understood as an emerging adult, with particular recognition of developmental stage, is an essential component of quality measures and underpins the adolescent, and caregiver, experience when faced with an uncertain or poor cancer prognosis (UPCP). Healthcare professionals (HCPs) can experience increased emotional labour and feelings of professional inadequacy when caring for adolescents with UPCP. Therapeutic alliance improves HCPs understanding of optimum individualised care by improving communication and supported decision making. Access to training and support for HCPs is required to address the emotional impact of therapeutic alliance with teenage/adolescent and young adults (T/AYAs) with advanced cancer., Summary: Investment in therapeutic alliance, alongside robust support mechanisms and targeted training, can improve the skills, confidence and wellbeing for HCPs, and can also ensure optimum individualised care for T/AYAs with UPCP. Evidence for optimum care for adolescents with advanced cancer is relatively scarce, especially for younger T/AYAs (16-24) in the UK who sit within adult services. Further evaluation of the impact of current UK expertise, services and programs are needed to inform future development., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Traditionally, meta-analysis of time-to-event outcomes reports a single pooled hazard ratio assuming proportional hazards (PH). For health technology assessment evaluations, hazard ratios are frequently extrapolated across a lifetime horizon. However, when treatment effects vary over time, an assumption of PH is not always valid. The Royston-Parmar (RP), piecewise exponential (PE), and fractional polynomial (FP) models can accommodate non-PH and provide plausible extrapolations of survival curves beyond observed data., Methods: Simulation study to assess and compare the performance of RP, PE, and FP models in a Bayesian framework estimating restricted mean survival time difference (RMSTD) at 50 years from a pairwise meta-analysis with evidence of non-PH. Individual patient data were generated from a mixture Weibull distribution. Twelve scenarios were considered varying the amount of follow-up data, number of trials in a meta-analysis, non-PH interaction coefficient, and prior distributions. Performance was assessed through bias and mean squared error. Models were applied to a metastatic breast cancer example., Results: FP models performed best when the non-PH interaction coefficient was 0.2. RP models performed best in scenarios with complete follow-up data. PE models performed well on average across all scenarios. In the metastatic breast cancer example, RMSTD at 50-years ranged from -14.6 to 8.48 months., Conclusions: Synthesis of time-to-event outcomes and estimation of RMSTD in the presence of non-PH can be challenging and computationally intensive. Different approaches make different assumptions regarding extrapolation and sensitivity analyses varying key assumptions are essential to check the robustness of conclusions to different assumptions for the underlying survival function., (© 2024 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.)

Several methods in survival analysis are based on the proportional hazards assumption. However, this assumption is very restrictive and often not justifiable in practice. Therefore, effect estimands that do not rely on the proportional hazards assumption are highly desirable in practical applications. One popular example for this is the restricted mean survival time (RMST). It is defined as the area under the survival curve up to a prespecified time point and, thus, summarizes the survival curve into a meaningful estimand. For two-sample comparisons based on the RMST, previous research found the inflation of the type I error of the asymptotic test for small samples and, therefore, a two-sample permutation test has already been developed. The first goal of the present paper is to further extend the permutation test for general factorial designs and general contrast hypotheses by considering a Wald-type test statistic and its asymptotic behavior. Additionally, a groupwise bootstrap approach is considered. Moreover, when a global test detects a significant difference by comparing the RMSTs of more than two groups, it is of interest which specific RMST differences cause the result. However, global tests do not provide this information. Therefore, multiple tests for the RMST are developed in a second step to infer several null hypotheses simultaneously. Hereby, the asymptotically exact dependence structure between the local test statistics is incorporated to gain more power. Finally, the small sample performance of the proposed global and multiple testing procedures is analyzed in simulations and illustrated in a real data example., (© 2024 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)

What can be considered an appropriate statistical method for the primary analysis of a randomized clinical trial (RCT) with a time-to-event endpoint when we anticipate non-proportional hazards owing to a delayed effect? This question has been the subject of much recent debate. The standard approach is a log-rank test and/or a Cox proportional hazards model. Alternative methods have been explored in the statistical literature, such as weighted log-rank tests and tests based on the Restricted Mean Survival Time (RMST). While weighted log-rank tests can achieve high power compared to the standard log-rank test, some choices of weights may lead to type-I error inflation under particular conditions. In addition, they are not linked to a mathematically unambiguous summary measure. Test statistics based on the RMST, on the other hand, allow one to investigate the average difference between two survival curves up to a pre-specified time point τ $$ \tau $$ -a mathematically unambiguous summary measure. However, by emphasizing differences prior to τ $$ \tau $$ , such test statistics may not fully capture the benefit of a new treatment in terms of long-term survival. In this article, we introduce a graphical approach for direct comparison of weighted log-rank tests and tests based on the RMST. This new perspective allows a more informed choice of the analysis method, going beyond power and type I error comparison., (© 2024 John Wiley & Sons Ltd.)

Aims: To evaluate the impact of adherence to glucagon like peptide-1 receptor agonists (GLP1-RA) and sodium-glucose transporter two inhibitors (SGLT2-I) on clinical outcomes and costs in patients with type 2 diabetes mellitus (T2DM)., Materials and Methods: The 121,115 residents of the Lombardy Region (Italy) aged ≥40 years newly treated with metformin during 2007-2015 were followed to identify those who started therapy with GLP1-RA or SGLT2-I. Adherence to drug therapy over the first year was defined as the proportion of days covered >80%. Within each drug class, for each adherent patient, one non-adherent patient was matched for age, sex, duration, adherence to metformin treatment and propensity score. The primary clinical outcome was a composite of insulin initiation, hospitalisation for micro- and macrovascular complications and all-cause mortality after the first year of drug treatment. Costs were evaluated based on reimbursements from the national healthcare system., Results: After matching, 1182 pairs of adherent and non-adherent GLP1-RA users and 1126 pairs of adherent and non-adherent SGLT2-I users were included. In both groups, adherent patients experienced a significantly lower incidence of the primary outcome (HR: 0.85, 95% CI 0.72-0.98 for GLP1-RA and HR: 0.69, 95% CI 0.55-0.87 for SGLT2-I). A significant reduction in hospitalizations was found for adherent patients in the GLP1-RA group but not for the SGLT2-I group. Results were consistent when analyses were stratified by age and sex. While higher drug-related costs in the adherent group were counterbalanced by decreased hospitalisation costs in SGLT2-I treated patients, this was not the case for GLP1-RA., Conclusions: Higher adherence to drug treatment with GLP1-RA and SGLT2-I during the first year of the drug intake is associated with a lower incidence of adverse clinical outcomes in a real-world setting., (© 2024 The Authors. Diabetes/Metabolism Research and Reviews published by John Wiley & Sons Ltd.)

Importance: Chemotherapy is a mainstay treatment of metastatic non-small cell lung cancer. However, little is known about the comparative risk of hospitalization associated with commonly used chemotherapy regimens., Objective: To evaluate the real-world association of specific lung cancer chemotherapy regimens with measures of acute hospital care (primary objective) and survival (secondary objective)., Design, Setting, and Participants: Retrospective, propensity-matched, cohort study using the Surveillance, Epidemiology, and End Results-Medicare linked data for cancer diagnoses between 2008 and 2013, with follow-up through 2014. Patients were Medicare beneficiaries 66 years of age or older receiving initial chemotherapy for treatment of stage IV, nonsquamous, non-small cell lung cancer. Analyses were performed between September 2017 and April 2018., Exposures: Receipt of chemotherapy with carboplatin-pemetrexed or carboplatin-paclitaxel, with or without concurrent bevacizumab., Main Outcomes and Measures: The primary outcome was risk of hospitalization within 30 days of chemotherapy initiation. Secondary measures included cumulative 90-day hospitalizations, 90-day mean hospital-free survival time, and overall survival., Results: Of the 3310 eligible patients, 1823 received carboplatin-pemetrexed, and 1487 received carboplatin-paclitaxel. The median age at diagnosis was 73 years (interquartile range, 69-77 years), 1784 patients (53.9%) were men, and 2909 patients (87.9%) were non-Hispanic white. In total, 2182 patients were included in the propensity-matched analysis. The 30-day hospitalization risk was 20.7% (95% CI, 18.3%-23.1%) among patients receiving carboplatin-pemetrexed vs 26.0% (95% CI, 23.4%-28.6%) among patients receiving carboplatin-paclitaxel (5.3% difference; P = .003). The 90-day cumulative hospitalizations did not differ significantly between the 2 treatment groups; however, the 90-day mean hospital-free survival time was improved for patients receiving carboplatin-pemetrexed (68.4 days [95% CI, 66.5-70.4 days] vs 63.6 days [95% CI, 61.6-65.7 days]; P = .001). The median survival time was 9.0 months (95% CI, 8.4-9.5 months) with carboplatin-pemetrexed therapy vs 7.6 months (95% CI, 7.0-8.4 months) with carboplatin-paclitaxel therapy (P = .005). Stratified analyses showed no association of bevacizumab use with hospitalization risk or survival when combined with either chemotherapy regimen., Conclusions and Relevance: The findings from this study suggest that patients receiving carboplatin-pemetrexed compared with those receiving carboplatin-paclitaxel have a lower 30-day hospitalization risk, a greater 90-day hospital-free survival, and improved overall survival. Information about hospitalization risk may provide valuable context for evaluating real-world cancer treatment outcomes.

Purpose: As local therapies improve, contralateral breast cancer (CBC) risk for women with ductal carcinoma in situ (DCIS) may exceed the risk of a second ipsilateral breast cancer. We sought to determine whether estrogen-receptor (ER) status influenced CBC risk., Methods: We identified women aged 40-79 with DCIS diagnosed between 1990 and 2002 using the Surveillance, Epidemiology, and End Results database. We used multivariable competing risk regression to examine predictors of time from index DCIS to CBC (invasive or in situ)., Results: Multivariable competing risk regression found ER status to be a highly significant predictor of CBC. The 10-year cumulative incidence was estimated to be 5.3% (95% CI 4.8-5.8%) among ER positive (ER+) cases and 3.3% (95% CI 2.6-4.0%) among ER negative (ER-)., Conclusions: This finding suggests that ER+ DCIS may represent a field effect that confers increased propensity for developing cancer across breast tissue, regardless of laterality. In contrast, ER- DCIS may represent an isolated local event. Given that the majority of DCIS is ER+, and only a minority of DCIS patients receive hormonal therapy, consideration of ER status may influence treatment and surveillance approaches.

Background: Cerebrospinal fluid (CSF) viral escape occurs in 4%-20% of human immunodeficiency virus (HIV)-infected adults, yet the impact of antiretroviral therapy (ART) on CSF escape is unclear., Methods: A prospective study of 1063 participants with baseline plasma viral load (VL) ≤400 copies/mL between 2005 and 2016. The odds ratio (OR) for ART regimens (protease inhibitor with nucleoside reverse transcriptase inhibitor [PI + NRTI] vs other ART) and CSF escape was estimated using mixed-effects models., Results: Baseline mean age was 46 years, median plasma VL, and CD4 count were 50 copies/mL, and 424 cells/μL, respectively. During median follow-up of 4.4 years, CSF escape occurred in 77 participants (7.2%). PI + NRTI use was an independent predictor of CSF escape (OR, 3.1; 95% confidence interval, 1.8-5.0) in adjusted analyses and models restricted to plasma VL ≤50 copies/mL (P < .001). Regimens that contained atazanavir (ATV) were a stronger predictor of CSF viral escape than non-ATV PI + NRTI regimens. Plasma and CSF M184V/I combined with thymidine-analog mutations were more frequent in CSF escape vs no escape (23% vs 2.3%). Genotypic susceptibility score-adjusted central nervous system (CNS) penetration-effectiveness (CPE) values were calculated for CSF escape with M184V/I mutations (n = 34). Adjusted CPE values were low (<5) for CSF in 27 (79%), indicating suboptimal CNS drug availability., Conclusions: PI + NRTI regimens are independent predictors of CSF escape in HIV-infected adults. Reduced CNS ART bioavailability may predispose to CSF escape in patients with M184V/I mutations.

A core-expanded, pyrrole-fused azacoronene analogue containing two unusual N-doped heptagons was obtained from commercially available octafluoronaphthalene and 3,4-diethylpyrrole in two steps as a heteroatom-doped nonplanar nanographene. Full fusion with the formation of the tetraazadipleiadiene framework and the longitudinally twisted structure was unambiguously confirmed by single-crystal X-ray diffraction analysis. The edge-to-edge dihedral angle along the acene moiety was 63°. This electron-rich π-system showed four reversible oxidation peaks. Despite the nonplanar structure, the Hückel aromaticity owing to a peripheral π-conjugation in the dicationic state was concluded from the bond-length alternation and nucleus-independent chemical shift (NICS) and anisotropy of the induced current density (ACID) calculations.

In randomized clinical trials where time-to-event is the primary outcome, almost routinely, the logrank test is prespecified as the primary test and the hazard ratio is used to quantify treatment effect. If the ratio of 2 hazard functions is not constant, the logrank test is not optimal and the interpretation of hazard ratio is not obvious. When such a nonproportional hazards case is expected at the design stage, the conventional practice is to prespecify another member of weighted logrank tests, eg, Peto-Prentice-Wilcoxon test. Alternatively, one may specify a robust test as the primary test, which can capture various patterns of difference between 2 event time distributions. However, most of those tests do not have companion procedures to quantify the treatment difference, and investigators have fallen back on reporting treatment effect estimates not associated with the primary test. Such incoherence in the "test/estimation" procedure may potentially mislead clinicians/patients who have to balance risk-benefit for treatment decision. To address this, we propose a flexible and coherent test/estimation procedure based on restricted mean survival time, where the truncation time τ is selected data dependently. The proposed procedure is composed of a prespecified test and an estimation of corresponding robust and interpretable quantitative treatment effect. The utility of the new procedure is demonstrated by numerical studies based on 2 randomized cancer clinical trials; the test is dramatically more powerful than the logrank, Wilcoxon tests, and the restricted mean survival time-based test with a fixed τ, for the patterns of difference seen in these cancer clinical trials., (Copyright © 2018 John Wiley & Sons, Ltd.)

Objective: To evaluate limitations of common statistical modeling approaches in deriving clinical prediction models and explore alternative strategies., Study Design and Setting: A previously published model predicted the likelihood of having a mutation in germline DNA mismatch repair genes at the time of diagnosis of colorectal cancer. This model was based on a cohort where 38 mutations were found among 870 participants, with validation in an independent cohort with 35 mutations. The modeling strategy included stepwise selection of predictors from a pool of over 37 candidate predictors and dichotomization of continuous predictors. We simulated this strategy in small subsets of a large contemporary cohort (2,051 mutations among 19,866 participants) and made comparisons to other modeling approaches. All models were evaluated according to bias and discriminative ability (concordance index, c) in independent data., Results: We found over 50% bias for five of six originally selected predictors, unstable model specification, and poor performance at validation (median c = 0.74). A small validation sample hampered stable assessment of performance. Model prespecification based on external knowledge and using continuous predictors led to better performance (c = 0.836 and c = 0.852 with 38 and 2,051 events respectively)., Conclusion: Prediction models perform poorly if based on small numbers of events and developed with common but suboptimal statistical approaches. Alternative modeling strategies to best exploit available predictive information need wider implementation, with collaborative research to increase sample sizes., (Copyright © 2017 Elsevier Inc. All rights reserved.)

In comparing two treatments with the event time observations, the hazard ratio (HR) estimate is routinely used to quantify the treatment difference. However, this model dependent estimate may be difficult to interpret clinically especially when the proportional hazards (PH) assumption is violated. An alternative estimation procedure for treatment efficacy based on the restricted means survival time or t-year mean survival time (t-MST) has been discussed extensively in the statistical and clinical literature. On the other hand, a statistical test via the HR or its asymptotically equivalent counterpart, the logrank test, is asymptotically distribution-free. In this article, we assess the relative efficiency of the hazard ratio and t-MST tests with respect to the statistical power under various PH and non-PH models theoretically and empirically. When the PH assumption is valid, the t-MST test performs almost as well as the HR test. For non-PH models, the t-MST test can substantially outperform its HR counterpart. On the other hand, the HR test can be powerful when the true difference of two survival functions is quite large at end but not the beginning of the study. Unfortunately, for this case, the HR estimate may not have a simple clinical interpretation for the treatment effect due to the violation of the PH assumption., (© 2017, The International Biometric Society.)

Objective: Misinterpretation of complex genomic data presents a major challenge in the implementation of precision oncology. We sought to determine whether interactive genomic reports with embedded clinician education and optimized data visualization improved genomic data interpretation., Materials and Methods: We conducted a randomized, vignette-based survey study to determine whether exposure to interactive reports for a somatic gene panel, as compared to static reports, improves physicians' genomic comprehension and report-related satisfaction (overall scores calculated across 3 vignettes, range 0-18 and 1-4, respectively, higher score corresponding with improved endpoints)., Results: One hundred and five physicians at a tertiary cancer center participated (29% participation rate): 67% medical, 20% pediatric, 7% radiation, and 7% surgical oncology; 37% female. Prior to viewing the case-based vignettes, 34% of the physicians reported difficulty making treatment recommendations based on the standard static report. After vignette/report exposure, physicians' overall comprehension scores did not differ by report type (mean score: interactive 11.6 vs static 10.5, difference = 1.1, 95% CI, -0.3, 2.5, P = .13). However, physicians exposed to the interactive report were more likely to correctly assess sequencing quality (P < .001) and understand when reports needed to be interpreted with caution (eg, low tumor purity; P = .02). Overall satisfaction scores were higher in the interactive group (mean score 2.5 vs 2.1, difference = 0.4, 95% CI, 0.2-0.7, P = .001)., Discussion and Conclusion: Interactive genomic reports may improve physicians' ability to accurately assess genomic data and increase report-related satisfaction. Additional research in users' genomic needs and efforts to integrate interactive reports into electronic health records may facilitate the implementation of precision oncology.

Benzene-fused bis(acenaphthoBODIPY)s prepared by retro-Diels-Alder reaction of bicyclo[2.2.2]octadiene-fused precursors showed strong absorption bands in the near-infrared region and very weak absorptions in the visible region., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

The treatments provided to and survival of patients with recurrent vs de novo stage IV advanced breast, lung, and colorectal cancer may differ but have not been well studied. Using population-based data from the Cancer Research Network for 4510 patients with advanced breast, lung, or colorectal cancer, we matched recurrent/de novo patients on demographic factors. We found longer survival for recurrent vs de novo lung cancer (182 matched pairs); no significant difference for colorectal cancer (332 matched pairs); and shorter survival for recurrent vs de novo breast cancer (219 matched pairs). Compared with recurrent cases, chemotherapy use and radiation therapy use were more common among de novo cases. Differences in treatment and survival between recurrent and de novo advanced cancer patients could inform prognostic estimates and clinical trial design.

Background: This study developed, validated, and disseminated a generalizable informatics algorithm for detecting breast cancer recurrence and timing using a gold standard measure of recurrence coupled with data derived from a readily available common data model that pools health insurance claims and electronic health records data., Methods: The algorithm has two parts: to detect the presence of recurrence and to estimate the timing of recurrence. The primary data source was the Cancer Research Network Virtual Data Warehouse (VDW). Sixteen potential indicators of recurrence were considered for model development. The final recurrence detection and timing models were determined, respectively, by maximizing the area under the ROC curve (AUROC) and minimizing average absolute error. Detection and timing algorithms were validated using VDW data in comparison with a gold standard recurrence capture from a third site in which recurrences were validated through chart review. Performance of this algorithm, stratified by stage at diagnosis, was compared with other published algorithms. All statistical tests were two-sided., Results: Detection model AUROCs were 0.939 (95% confidence interval [CI] = 0.917 to 0.955) in the training data set (n = 3370) and 0.956 (95% CI = 0.944 to 0.971) and 0.900 (95% CI = 0.872 to 0.928), respectively, in the two validation data sets (n = 3370 and 3961, respectively). Timing models yielded average absolute prediction errors of 12.6% (95% CI = 10.5% to 14.5%) in the training data and 11.7% (95% CI = 9.9% to 13.5%) and 10.8% (95% CI = 9.6% to 12.2%) in the validation data sets, respectively, and were statistically significantly lower by 12.6% (95% CI = 8.8% to 16.5%, P < .001) than those estimated using previously reported timing algorithms. Similar covariates were included in both detection and timing algorithms but differed substantially from previous studies., Conclusions: Valid and reliable detection of recurrence using data derived from electronic medical records and insurance claims is feasible. These tools will enable extensive, novel research on quality, effectiveness, and outcomes for breast cancer patients and those who develop recurrence.