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We developed a summer research experience program within a freestanding comprehensive cancer center to cultivate undergraduate students with an interest in and an aptitude for quantitative sciences focused on oncology. This unconventional location for an undergraduate program is an ideal setting for interdisciplinary training in the intersection of oncology, statistics, and epidemiology. This article describes the development and implementation of a hands-on research experience program in this unique environment. Core components of the program include faculty-mentored projects, instructional programs to improve research skills and domain knowledge, and professional development activities. We discuss key considerations such as fostering effective partnership between research and administrative units, recruiting students, and identifying faculty mentors with quantitative projects. We describe evaluation approaches and discuss post-program outcomes and lessons learned. In its initial two years, the program successfully improved the students' perception of competence gained in research skills and statistical knowledge across several knowledge domains. The majority of students also went on to pursue graduate degrees in a quantitative field or work in oncology-centric academic research roles. Our research-based training model can be adapted by a variety of organizations motivated to develop a summer research experience program in quantitative sciences for undergraduate students. Supplemental files for this article are available online.

PURPOSE: During ongoing controversies about mammography screening, many investigators have stated that performance improvements in screening mammography may mitigate concerns about harms. However, there have been few attempts to quantify performance improvements required to recommend mammography screening. Based on USPSTF benchmarks, we utilized revealed preference methods to ascertain quantitative thresholds at which screening mammography would be recommended beyond biennial screening in women 50 and older. METHODS: Benefits of routine screening mammography (breast cancer deaths averted) were from published USPSTF meta-analyses. Potential harms (10-year cumulative probability of at least one false-positive) were from published Breast Cancer Surveillance Consortium estimates. We identified the implicit threshold (benefit/harm ratio) to recommend biennial screening starting at age 50. Using this threshold, we ascertained reductions of false-positives required to recommend more frequent screening and screening initiation under age 50 using revealed preference analyses. RESULTS: Using USPSTF implied benefit/harm ratio, routine biennial screening would be recommended starting at 40 if false-positives declined by at least 62%. Reductions of false-positive proportions of 74% would be required to recommend annual screening starting at 40 and reductions of false-positive proportions of 31% would be required to support annual screening starting at 50. CONCLUSIONS: Using USPSTF revealed preferences, 31-74% reductions in false-positives would be required to recommend mammography screening beyond biennial screening starting at age 50. Widespread implementation of tomosynthesis and reducing recall rates to the lower end of recommended recall rates (5-12%) would provide support for expanding screening beyond biennial screening in women age 50.

BACKGROUND: Several organizations have developed frameworks to systematically assess the value of new drugs. OBJECTIVE: To evaluate the convergent validity and interrater reliability of 4 value frameworks to understand the extent to which these tools can facilitate value-based treatment decisions in oncology. METHODS: Eight panelists used the American Society of Clinical Oncology (ASCO), European Society for Medical Oncology (ESMO), Institute for Clinical and Economic Review (ICER), and National Comprehensive Cancer Network (NCCN) frameworks to conduct value assessments of 15 drugs for advanced lung and breast cancers and castration-refractory prostate cancer. Panelists received instructions and published clinical data required to complete the assessments, assigning each drug a numeric or letter score. Kendalls Coefficient of Concordance for Ranks (Kendalls W) was used to measure convergent validity by cancer type among the 4 frameworks. Intraclass correlation coefficients (ICCs) were used to measure interrater reliability for each framework across cancers. Panelists were surveyed on their experiences. RESULTS: Kendalls W across all 4 frameworks for breast, lung, and prostate cancer drugs was 0.560 (P= 0.010), 0.562 (P = 0.010), and 0.920 (P < 0.001), respectively. Pairwise, Kendalls W for breast cancer drugs was highest for ESMO-ICER and ICER-NCCN (W = 0.950, P = 0.019 for both pairs) and lowest for ASCO-NCCN (W = 0.300, P = 0.748). For lung cancer drugs, W was highest pairwise for ESMO-ICER (W = 0.974, P = 0.007) and lowest for ASCO-NCCN (W = 0.218, P = 0.839); for prostate cancer drugs, pairwise W was highest for ICER-NCCN (W = 1.000, P < 0.001) and lowest for ESMO-ICER and ESMO-NCCN (W = 0.900, P = 0.052 for both pairs). When ranking drugs on distinct framework subdomains, Kendalls W among breast cancer drugs was highest for certainty (ICER, NCCN: W = 0.908, P = 0.046) and lowest for clinical benefit (ASCO, ESMO, NCCN: W = 0.345, P = 0.436). Among lung cancer drugs, W was highest for toxicity (ASCO, ESMO, NCCN: W = 0. 944, P < 0.001) and lowest for certainty (ICER, NCCN: W = 0.230, P = 0.827); and among prostate cancer drugs, it was highest for quality of life (ASCO, ESMO: W = 0.986, P = 0.003) and lowest for toxicity (ASCO, ESMO, NCCN: W = 0.200, P = 0.711). ICC (95% CI) for ASCO, ESMO, ICER, and NCCN were 0.800 (0.660-0.913), 0.818 (0.686-0.921), 0.652 (0.466-0.834), and 0.153 (0.045-0.371), respectively. When scores were rescaled to 0-100, NCCN provided the narrowest band of scores. When asked about their experiences using the ASCO, ESMO, ICER, and NCCN frameworks, panelists generally agreed that the frameworks were logically organized and reasonably easy to use, with NCCN rated somewhat easier. CONCLUSIONS: Convergent validity among the ASCO, ESMO, ICER, and NCCN frameworks was fair to excellent, increasing with clinical benefit subdomain concordance and simplicity of drug trial data. Interrater reliability, highest for ASCO and ESMO, improved with clarity of instructions and specificity of score definitions. Continued use, analyses, and refinements of these frameworks will bring us closer to the ultimate goal of using value-based treatment decisions to improve patient care and outcomes. DISCLOSURES: This work was funded by Eisai Inc. Copher and Knoth are employees of Eisai Inc. Bentley, Lee, Zambrano, and Broder are employees of Partnership for Health Analytic Research, a health services research company paid by Eisai Inc. to conduct this research. For this study, Cohen, Huynh, and Neville report fees from Partnership for Health Analytic Research. Outside of this study, Cohen receives grants and direct consulting fees from various companies that manufacture and market pharmaceuticals. Mei reports a grant from Eisai Inc. during this study. The other authors have no disclosures to report. Study concept and design were contributed by Bentley and Broder, with assistance from Elkin and Cohen. Bentley took the lead in data collection, along with Elkin, Huynh, Mukherjea, Neville, Mei, Popescu, Lee, and Zambrano. Data interpretation was performed by Bentley and Broder, along with Elkin, Cohen, Copher, and Knoth. The manuscript was written primarily by Bentley, along with Elkin and Broder, and revised by Bentley, Broder, Elkin, Cohen, Copher, and Knoth. Select components of this works methods were presented at ISPOR 19th Annual European Congress held in Vienna, Austria, October 29-November 2, 2016, and Society for Medical Decision Making 38th Annual North American Meeting held in Vancouver, Canada, October 23-26, 2016.

Lung cancer is the leading cause of mortality and person‐years of life lost from cancer among US men and women. Early detection has been shown to be associated with reduced lung cancer mortality. Our objective was to update the American Cancer Society (ACS) 2013 lung cancer screening (LCS) guideline for adults at high risk for lung cancer. The guideline is intended to provide guidance for screening to health care providers and their patients who are at high risk for lung cancer due to a history of smoking. The ACS Guideline Development Group (GDG) utilized a systematic review of the LCS literature commissioned for the US Preventive Services Task Force 2021 LCS recommendation update; a second systematic review of lung cancer risk associated with years since quitting smoking (YSQ); literature published since 2021; two Cancer Intervention and Surveillance Modeling Network‐validated lung cancer models to assess the benefits and harms of screening; an epidemiologic and modeling analysis examining the effect of YSQ and aging on lung cancer risk; and an updated analysis of benefit‐to‐radiation‐risk ratios from LCS and follow‐up examinations. The GDG also examined disease burden data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program. Formulation of recommendations was based on the quality of the evidence and judgment (incorporating values and preferences) about the balance of benefits and harms. The GDG judged that the overall evidence was moderate and sufficient to support a strong recommendation for screening individuals who meet the eligibility criteria. LCS in men and women aged 50–80 years is associated with a reduction in lung cancer deaths across a range of study designs, and inferential evidence supports LCS for men and women older than 80 years who are in good health. The ACS recommends annual LCS with low‐dose computed tomography for asymptomatic individuals aged 50–80 years who currently smoke or formerly smoked and have a ≥20 pack‐year smoking history (strong recommendation, moderate quality of evidence). Before the decision is made to initiate LCS, individuals should engage in a shared decision‐making discussion with a qualified health professional. For individuals who formerly smoked, the number of YSQ is not an eligibility criterion to begin or to stop screening. Individuals who currently smoke should receive counseling to quit and be connected to cessation resources. Individuals with comorbid conditions that substantially limit life expectancy should not be screened. These recommendations should be considered by health care providers and adults at high risk for lung cancer in discussions about LCS. If fully implemented, these recommendations have a high likelihood of significantly reducing death and suffering from lung cancer in the United States. [ABSTRACT FROM AUTHOR]

We developed a summer research experience program within a freestanding comprehensive cancer center to cultivate undergraduate students with an interest in and an aptitude for quantitative sciences focused on oncology. This unconventional location for an undergraduate program is an ideal setting for interdisciplinary training in the intersection of oncology, statistics, and epidemiology. This article describes the development and implementation of a hands-on research experience program in this unique environment. Core components of the program include faculty-mentored projects, instructional programs to improve research skills and domain knowledge, and professional development activities. We discuss key considerations such as fostering effective partnership between research and administrative units, recruiting students, and identifying facultymentors with quantitative projects. We describe evaluation approaches and discuss post-program outcomes and lessons learned. In its initial two years, the program successfully improved the students' perception of competence gained in research skills and statistical knowledge across several knowledge domains. The majority of students also went on to pursue graduate degrees in a quantitative field or work in oncology-centric academic research roles. Our research-based training model can be adapted by a variety of organizations motivated to develop a summer research experience program in quantitative sciences for undergraduate students. Supplemental files for this article are available online. [ABSTRACT FROM AUTHOR]

Background: Guidelines recommend offering cessation interventions to smokers eligible for lung cancer screening, but there is little data comparing specific cessation approaches in this setting. We compared the benefits and costs of different smoking cessation interventions to help screening programs select specific cessation approaches.Methods: We conducted a societal-perspective cost-effectiveness analysis using a Cancer Intervention and Surveillance Modeling Network model simulating individuals born in 1960 over their lifetimes. Model inputs were derived from Medicare, national cancer registries, published studies, and micro-costing of cessation interventions. We modeled annual lung cancer screening following 2014 US Preventive Services Task Force guidelines plus cessation interventions offered to current smokers at first screen, including pharmacotherapy only or pharmacotherapy with electronic and/or web-based, telephone, individual, or group counseling. Outcomes included lung cancer cases and deaths, life-years saved, quality-adjusted life-years (QALYs) saved, costs, and incremental cost-effectiveness ratios.Results: Compared with screening alone, all cessation interventions decreased cases of and deaths from lung cancer. Compared incrementally, efficient cessation strategies included pharmacotherapy with either web-based cessation ($555 per QALY), telephone counseling ($7562 per QALY), or individual counseling ($35 531 per QALY). Cessation interventions continued to have costs per QALY well below accepted willingness to pay thresholds even with the lowest intervention effects and was more cost-effective in cohorts with higher smoking prevalence.Conclusion: All smoking cessation interventions delivered with lung cancer screening are likely to provide benefits at reasonable costs. Because the differences between approaches were small, the choice of intervention should be guided by practical concerns such as staff training and availability. [ABSTRACT FROM AUTHOR]

Abstract Background Decision curve analysis is a novel method for evaluating diagnostic tests, prediction models and molecular markers. It combines the mathematical simplicity of accuracy measures, such as sensitivity and specificity, with the clinical applicability of decision analytic approaches. Most critically, decision curve analysis can be applied directly to a data set, and does not require the sort of external data on costs, benefits and preferences typically required by traditional decision analytic techniques. Methods In this paper we present several extensions to decision curve analysis including correction for overfit, confidence intervals, application to censored data (including competing risk) and calculation of decision curves directly from predicted probabilities. All of these extensions are based on straightforward methods that have previously been described in the literature for application to analogous statistical techniques. Results Simulation studies showed that repeated 10-fold crossvalidation provided the best method for correcting a decision curve for overfit. The method for applying decision curves to censored data had little bias and coverage was excellent; for competing risk, decision curves were appropriately affected by the incidence of the competing risk and the association between the competing risk and the predictor of interest. Calculation of decision curves directly from predicted probabilities led to a smoothing of the decision curve. Conclusion Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models. Software to implement decision curve analysis is provided.

Purpose: About half of all cancer patients in the United States receive radiation therapy as a part of their cancer treatment. Little is known, however, about the facilities that currently deliver external beam radiation. Our goal was to construct a comprehensive database of all radiation therapy facilities in the United States that can be used for future health services research in radiation oncology. Methods and Materials: From each state’s health department we obtained a list of all facilities that have a linear accelerator or provide radiation therapy. We merged these state lists with information from the American Hospital Association (AHA), as well as 2 organizations that audit the accuracy of radiation machines: the Radiologic Physics Center (RPC) and the Radiation Dosimetry Services (RDS). The comprehensive database included all unique facilities listed in 1 or more of the 4 sources. Results: We identified 2,246 radiation therapy facilities operating in the United States as of 2004–2005. Of these, 448 (20%) facilities were identified through state health department records alone and were not listed in any other data source. Conclusions: Determining the location of the 2,246 radiation facilities in the United States is a first step in providing important information to radiation oncologists and policymakers concerned with access to radiation therapy services, the distribution of health care resources, and the quality of cancer care. [Copyright &y& Elsevier]

OBJECTIVES: Instilling the principles of ethical and responsible medical research is critical for educating the next generation of clinical researchers. We developed a responsible conduct of research (RCR) workshop and associated curriculum for undergraduate trainees in a quantitative clinical research program. METHODS: Topics in this 7-module RCR workshop are relevant to undergraduate trainees in quantitative fields, many of whom are learning about these concepts for the first time. These topics include: (1) research collaboration and mentoring, (2) human subjects and privacy, (3) rigor, reproducibility, and responsibility in data analysis, (4) data safety, security, and sharing, (5) responsible authorship, peer reviews, and conflicts of interest, (6) research misconduct and whistleblowing, and (7) social responsibility and contemporary ethical issues. The workshop adopts an active learning approach and is intended to encourage peer-to-peer learning through a critical review of case studies and contemporary media reports. Workshop materials and discussions are designed to address experiences relevant to undergraduate trainees. For example, for the discussion on human subject protection, trainees are asked to review their own university's policies for engaging students as research subjects. Student perceived knowledge and understanding of research ethics were obtained from pre- and post-workshop surveys, with responses ranging from 1 (low level of understanding) to 5 (high level of understanding). RESULTS: Survey responses from 38 trainees across 4 years demonstrated marked increase in perceived knowledge and understanding of research ethics, from 64% in pre- to 96% in post-workshop responses with scores of 3 and up. Trainees noted the effectiveness of the active learning format of the workshop and relevance of the topics on their own research projects. CONCLUSION: Intentional instruction is vital to help trainees discern between good and bad science in research. The presented RCR curriculum can be adapted by other programs designed for trainees engaged in medical research and education. [ABSTRACT FROM AUTHOR]