Characterization of Comorbidities Limiting the Recruitment of Patients in Early Phase Clinical Trials

Absolute neutrophil count clinical trial eligibility criteria for pediatric oncology phase I and phase I/II trials by sponsorship

Normal absolute neutrophil count (ANC) variations, as seen with Duffy-null associated neutrophil count (DANC), are not accounted for in trial eligibility, which may contribute to racial enrollment disparities. We describe ANC eligibility for pediatric oncology phase I/II clinical trials according to primary sponsorship from 2010 to 2023 using ClinicalTrials.gov. Out of 438 trials, 20% were industry-sponsored. Total 17% of trials required ANC ≥1500 cells/μL for enrollment; however, industry-sponsored trials were significantly more likely to require ANC ≥1500 cells/μL than non-industry-sponsored trials (odds ratio 2.53, 95% confidence interval: 1.39-4.62; p < .001). These data suggest laboratory exclusion criteria are one possible mechanism for pediatric clinical trial enrollment disparities.

Precision Immuno-Oncology in NSCLC through Gender Equity Lenses

Precision immuno-oncology involves the development of personalized cancer treatments that are influenced by the unique nature of an individual's DNA, immune cells, and their tumor's molecular characterization. Biological sex influences immunity; females typically mount stronger innate and adaptive immune responses than males. Though more research is warranted, we continue to observe an enhanced benefit for females with lung cancer when treated with combination chemoimmunotherapy in contrast to the preferred approach of utilizing immunotherapy alone in men. Despite the observed sex differences in response to treatments, women remain underrepresented in oncology clinical trials, largely as a result of gender-biased misconceptions. Such exclusion has resulted in the development of less efficacious treatment guidelines and clinical recommendations and has created a knowledge gap in regard to immunotherapy-related survivorship issues such as fertility. To develop a more precise approach to care and overcome the exclusion of women from clinical trials, flexible trial schedules, multilingual communication strategies, financial, and transportation assistance for participants should be adopted. The impact of intersectionality and other determinants of health that affect the diagnosis, treatment, and outcomes in women must also be considered in order to develop a comprehensive understanding of the unique impact of immunotherapy in all women with lung cancer.

Exclusion of older adults from randomized controlled trials in rheumatoid arthritis

OBJECTIVES

To assess eligibility criteria that either explicitly or implicitly exclude older patients from randomized controlled trials (RCTs) in RA.

METHODS

Our analysis included RCTs of pharmacological interventions registered with ClinicalTrials.gov and started between 2013 and 2022. Co-primary outcomes were proportions of trials with an upper age limit and the eligibility criteria indirectly increasing risk of the exclusion of older adults.

RESULTS

A total of 143/290 (49%) trials had an upper age limit of 85 years or less. Multivariable analysis showed that the odds of an upper age limit were significantly lower in trials performed in the USA [adjusted odds ratio (aOR), 0.34; CI, 0.12-0.99; P = 0.04] and intercontinental trials (aOR, 0.4; CI, 0.18-0.87; P = 0.02). In total, 154/290 (53%) trials had at least one eligibility criterion implicitly excluding older adults. These included specific comorbidities (n = 114; 39%), compliance concerns (n = 67; 23%), and broad and vague exclusion criteria (n = 57; 20%); however, we found no significant associations between these criteria and trial characteristics. Overall, 217 (75%) trials either explicitly or implicitly excluded older patients; we also noted a trend towards increasing proportion of these trials over time. Only one trial (0.3%) enrolled solely patients aged 65 and older.

CONCLUSION

Older adults are commonly excluded from RCTs in RA based on both age limits and other eligibility criteria. This seriously limits the evidence base for the treatment of older patients in clinical practice. Given the growing prevalence of RA in older adults, relevant RCTs should be more inclusive to them.

Exclusion of older patients from randomized clinical trials in Parkinson's disease

Prevalence of Parkinson's disease (PD) increases with age. The purpose of this study was to evaluate the eligibility criteria in randomized clinical trials (RCTs) in PD, especially those limiting the enrollment of older adults. We examined RCTs of pharmacological and non-pharmacological anti-parkinsonian interventions registered with ClinicalTrials.gov and started from 2013 through 2022. Primary outcome was proportion of RCTs with an upper age limit of 85 years of age or less. Secondary outcome was proportion of RCTs with other exclusion criteria. Associations between trial characteristics and the presence of the age limits were determined using logistic regression. Our study included 420 RCTs. Two hundred thirty-nine (57%) of these had an upper age limit of 85 years of age or less. Proportion of these trials significantly increased over time. The odds of the presence of an upper age limit were significantly associated with the investigational site location, phase, and timeframe for the primary endpoint assessment. Three hundred fifty-six (85%) trials had other eligibility criteria limiting the enrollment of older patients; these often (n = 285; 68%) included cognitive impairment. Overall, 386 (92%) RCTs either explicitly excluded older adults or had criteria indirectly limiting their enrollment. Underrepresentation of older patients in clinical trials in PD considerably reduces the generalizability of their results. Some eligibility criteria should be modified to enable the investigators to assess the benefits and harms of new therapeutic interventions in older adults. This problem is important in view of rapidly growing number of older patients with PD.

Pan-cancer analyses of the associations between 109 pre-existing conditions and cancer treatment patterns across 19 adult cancers

Comorbidities present considerable challenges to cancer treatment and care. However, little is known about the effect of comorbidity on cancer treatment decisions across a wide range of cancer types and treatment modalities. Harnessing a cohort of 280,543 patients spanning 19 site-specific cancers, we explored pan-cancer frequencies of 109 comorbidities. Multinomial logistic regression was used to analyse the relationship between comorbidities and cancer treatment types, while binomial logistic regression examined the association between comorbidities and chemotherapy drug types, adjusting for demographic and clinical factors. Patients with comorbidity exhibited lower odds of receiving chemotherapy and multimodality treatment. End-stage renal disease was significantly associated with a decreased odds of receiving chemotherapy and surgery. Patients with prostate cancer who have comorbid non-acute cystitis, obstructive and reflux uropathy, urolithiasis, or hypertension were less likely to receive chemotherapy. Among patients with breast cancer, dementia, left bundle branch block, peripheral arterial disease, epilepsy, Barrett's oesophagus, ischaemic stroke, unstable angina and asthma were associated with lower odds of receiving multimodal chemotherapy, radiotherapy and surgery. Comorbidity is also consistently associated with the lower odds of receiving chemotherapy when comparing across 10 drug classes. Patients with comorbid dementia, intracerebral haemorrhage, subarachnoid haemorrhage, oesophageal varices, liver fibrosis sclerosis and cirrhosis and secondary pulmonary hypertension were less likely to receive antimetabolites. Comorbidity can influence the effectiveness and tolerability of cancer treatment and ultimately, prognosis. Multi-specialty collaborative care is essential for the management of comorbidity during cancer treatment, including prophylactic measures to manage toxicities.

Evaluation of factors associated with recruitment rates in early phase clinical trials based on the European Clinical Trials Register data

Effective participant recruitment is a critical challenge in clinical trials. Inadequate enrollment of participants can precipitate delays, escalated costs, and compromise scientific integrity. Despite its relevance, particularly during the early phases, it persists as an obstacle in the field of clinical research. The primary aim of this study was to analyze the recruitment rates of early-phase clinical trials and evaluate their potential associations with key trial characteristics. Using a descriptive and statistical analysis, a research study was conducted based on the early-phase trials registered at the European Clinical Trials Register (EU-CTR), spanning the timeframe from January 2017 to December 2021. Among the 194 trials examined, we found median recruitment rates of 68%. A more detailed exploration revealed a greater level of success in terms of recruitment achievement in pediatric trials when compared to trials involving adults, non-oncologic trials, or those also developed in non-European countries. It is important to underscore that only 69 trials out of the total managed to conclude recruitment, with the most prevalent reason for premature cessation being the presence of efficacy and safety issues or sponsor's strategy. This number can be greatly improved. Despite certain disparities observed in the information within EU-CTR, we have successfully determined the recruitment rates of the studies and established associations with some of the clinical trial characteristics analyzed. Owing to the inherent constraints of this study, further research is warranted to gain a comprehensive understanding of the intricate interplay between trial characteristics and their impact on recruitment rates in early-phase studies.

Eligibility criteria in clinical trials in breast cancer: a cohort study

BACKGROUND

Breast cancer (BC) is the most common cancer type in women. The purpose of this study was to assess the eligibility criteria in recent clinical trials in BC, especially those that can limit the enrollment of older patients as well as those with comorbidities and poor performance status.

METHODS

Data on clinical trials in BC were extracted from ClinicalTrials.gov. Co-primary outcomes were proportions of trials with different types of the eligibility criteria. Associations between trial characteristics and the presence of certain types of these criteria (binary variable) were determined with univariate and multivariate logistic regression.

RESULTS

Our analysis included 522 trials of systemic anticancer treatments started between 2020 and 2022. Upper age limits, strict exclusion criteria pertaining to comorbidities, and those referring to inadequate performance status of the patient were used in 204 (39%), 404 (77%), and 360 (69%) trials, respectively. Overall, 493 trials (94%) had at least one of these criteria. The odds of the presence of each type of the exclusion criteria were significantly associated with investigational site location and trial phase. We also showed that the odds of the upper age limits and the exclusion criteria involving the performance status were significantly higher in the cohort of recent trials compared with cohort of 309 trials started between 2010 and 2012 (39% vs 19% and 69% vs 46%, respectively; p < 0.001 for univariate and multivariate analysis in both comparisons). The proportion of trials with strict exclusion criteria was comparable between the two cohorts (p > 0.05). Only three of recent trials (1%) enrolled solely patients aged 65 or 70 and older.

CONCLUSIONS

Many recent clinical trials in BC exclude large groups of patients, especially older adults, individuals with different comorbidities, and those with poor performance status. Careful modification of some of the eligibility criteria in these trials should be considered to allow investigators to assess the benefits and harms of investigational treatments in participants with characteristics typically encountered in clinical practice.

Testing the "RCT augmentation" methodology: A trial simulation study to guide the broadening of trials eligibility criteria and inform on effectiveness

Background

Exclusion criteria that are treatment effect modifiers (TEM) decrease RCTs results generalisability and the potentials of effectiveness estimation. In "augmented RCTs", a small proportion of otherwise-excluded patients are included to allow for effectiveness estimation. In Hodgkin Lymphoma (HL) RCTs, older age and comorbidity are common exclusion criteria, while also TEM. We simulated HL RCTs augmented with age or comorbidity, and explored in each scenario the impact of augmentation on effectiveness estimation accuracy.

Methods

Simulated data with a population of HL individuals initiating drug A or B was generated. There were drug-age and drug-comorbidity interactions in the simulated data, with a greater magnitude of the former compared to the latter. Multiple augmented RCTs were simulated by randomly selecting patients with increasing proportions of older, or comorbid patients. Treatment effect size was expressed using the between-group Restricted Mean Survival Time (RMST) difference at 3 years. For each augmentation proportion, a model estimating the "real-world" treatment effect (effectiveness) was fitted and the estimation error measured (Root Mean Square Error, RMSE).

Results

In simulated RCTs including none (0%), or the real-world proportion (30%) of older patients, the interquartile range of RMST difference was 0.4-0.5 years and 0.2-0.3 years, respectively, and RMSE were 0.198 years (highest possible error) and 0.056 years (lowest), respectively. Augmenting RCTs with 5% older patients decreased estimation error substantially (RMSE = 0.076 years). Augmentation with comorbid patients proved less useful for effectiveness estimation.

Conclusion

In augmented RCTs aiming to inform the effectiveness of drugs, augmentation should concern in priority those exclusion criteria of suspected important TEM magnitude, so as to minimie the proportion of augmentation necessary for good effectiveness estimations.

Real-World Cost-Effectiveness Analysis: How Much Uncertainty Is in the Results?

Cost-effectiveness analyses of new cancer treatments in real-world settings (e.g., post-clinical trials) inform healthcare decision makers about their healthcare investments for patient populations. The results of these analyses are often, though not always, presented with statistical uncertainty. This paper identifies five ways to characterize statistical uncertainty: (1) a 95% confidence interval (CI) for the incremental cost-effectiveness ratio (ICER); (2) a 95% CI for the incremental net benefit (INB); (3) an INB by willingness-to-pay (WTP) plot; (4) a cost-effectiveness acceptability curve (CEAC); and (5) a cost-effectiveness scatterplot. It also explores their usage in 22 articles previously identified by a rapid review of real-world cost effectiveness of novel cancer treatments. Seventy-seven percent of these articles presented uncertainty results. The majority those papers (59%) used administrative data to inform their analyses while the remaining were conducted using models. Cost-effectiveness scatterplots were the most commonly used method (34.3%), with 40% indicating high levels of statistical uncertainty, suggesting the possibility of a qualitatively different result from the estimate given. Understanding the necessity for and the meaning of uncertainty in real-world cost-effectiveness analysis will strengthen knowledge translation efforts to improve patient outcomes in an efficient manner.

Survival in non-small cell lung cancer patients with versus without prior cancer

Clinical trials on cancer treatments frequently exclude patients with prior cancer, but more evidence is needed to understand their possible effects on outcomes. This study analyzed the prognostic impact of prior cancer in newly diagnosed non-small cell lung cancer (NSCLC) patients while accounting for various patient and cancer characteristics. Using population-based cancer registry data linked with administrative claims data, this retrospective cohort study examined patients aged 15-84 years diagnosed with NSCLC between 2010 and 2015 in Japan. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of all-cause mortality in patients with versus without prior cancer. The analysis was stratified according to NSCLC stage and diagnostic time intervals between prior cancers and the index NSCLC. We analyzed 9103 patients (prior cancer: 1416 [15.6%]; no prior cancer: 7687 [84.4%]). Overall, prior cancer had a non-significant mortality HR of 1.07 (95% CI: 0.97-1.17). Furthermore, prior cancer had a significantly higher mortality hazard for diagnostic time intervals of 3 years (HR: 1.23, 95% CI: 1.06-1.43) and 5 years (1.18, 1.04-1.33), but not for longer intervals. However, prior cancer in patients with more advanced NSCLC did not show a higher mortality risk for any diagnostic time interval. Smoking-related prior cancers and prior cancers with poorer prognosis were associated with poorer survival. NSCLC patients with prior cancer do not have an invariably higher risk of mortality, and should be considered for inclusion in clinical trials depending on their cancer stage.

Research Priorities for Interventions to Address Health Disparities in Lung Nodule Management: An Official American Thoracic Society Research Statement

Background: Lung nodules are common incidental findings, and timely evaluation is critical to ensure diagnosis of localized-stage and potentially curable lung cancers. Rates of guideline-concordant lung nodule evaluation are low, and the risk of delayed evaluation is higher for minoritized groups. Objectives: To summarize the existing evidence, identify knowledge gaps, and prioritize research questions related to interventions to reduce disparities in lung nodule evaluation. Methods: A multidisciplinary committee was convened to review the evidence and identify key knowledge gaps in four domains: 1) research methodology, 2) patient-level interventions, 3) clinician-level interventions, and 4) health system-level interventions. A modified Delphi approach was used to identify research priorities. Results: Key knowledge gaps included 1) a lack of standardized approaches to identify factors associated with lung nodule management disparities, 2) limited data evaluating the role of social determinants of health on disparities in lung nodule management, 3) a lack of certainty regarding the optimal strategy to improve patient-clinician communication and information transmission and/or retention, and 4) a paucity of information on the impact of patient navigators and culturally trained multidisciplinary teams. Conclusions: This statement outlines a research agenda intended to stimulate high-impact studies of interventions to mitigate disparities in lung nodule evaluation. Research questions were prioritized around the following domains: 1) need for methodologic guidelines for conducting research related to disparities in nodule management, 2) evaluating how social determinants of health influence lung nodule evaluation, 3) studying approaches to improve patient-clinician communication, and 4) evaluating the utility of patient navigators and culturally enriched multidisciplinary teams to reduce disparities.

Understanding common key indicators of successful and unsuccessful cancer drug trials using a contrast mining framework on ClinicalTrials.gov

Clinical trials are essential to the process of new drug development. As clinical trials involve significant investments of time and money, it is crucial for trial designers to carefully investigate trial settings prior to designing a trial. Utilizing trial documents from ClinicalTrials.gov, we aim to understand the common characteristics of successful and unsuccessful cancer drug trials to provide insights about what to learn and what to avoid. In this research, we first computationally classified cancer drug trials into successful and unsuccessful cases and then utilized natural language processing to extract eligibility criteria information from the trial documents. To provide explainable and potentially modifiable recommendations for new trial design, contrast mining was applied to discoverhighly contrasted patterns with a significant difference in prevalence between successful (completion with advancement to the next phase) and unsuccessful (suspended, withdrawn, or terminated) groups. Our method identified contrast patterns consisting of combinations of drug categories, eligibility criteria, study organization, and study design for nine major cancers. In addition to a literature review for the qualitative validation of mined contrast patterns, we found that contrast-pattern-based classifiers using the top 200 contrast patterns as feature representations can achieve approximately 80% F₁ score for eight out of ten cancer types in our experiments. In summary, aligning with the modernization efforts of ClinicalTrials.gov, our study demonstrates that understanding the contrast characteristics of successful and unsuccessful cancer trials may provide insights into the decision-making process for trial investigators and therefore facilitate improved cancer drug trial design.

Can we predict trial failure among older adult-specific clinical trials using trial-level factors?

INTRODUCTION

Conducting older adult-specific clinical trials can help overcome the lack of clinical evidence for older adults due to their underrepresentation in clinical trials. Understanding factors contributing to the successful completion of such trials can help trial sponsors and researchers prioritize studies and optimize study design. We aimed to develop a model that predicts trial failure among older adult-specific cancer clinical trials using trial-level factors.

MATERIALS AND METHODS

We identified phase 2-4 interventional cancer clinical trials that ended between 2008 and 2019 and had the minimum age limit of 60 years old or older using Aggregate Analysis of ClinicalTrials.gov data. We defined trial failure as closed early for reasons other than interim results or toxicity or completed with a sample of <85% of the targeted size. Candidate trial-level predictors were identified from a literature review. We evaluated eight types of machine learning algorithms to find the best model. Model fitting and testing were performed using 5-fold nested cross-validation. We evaluated the model performance using the area under receiver operating characteristic curve (AUROC).

RESULTS

Of 209 older adult-specific clinical trials, 87 were failed trials per the definition of trial failure. The model with the highest AUROC in the validation set was the least absolute shrinkage and selection operator (AUROC in the test set = 0.70; 95% confidence interval [CI]: 0.53, 0.86). Trial-level factors included in the best model were the study sponsor, the number of participating centers, the number of modalities, the level of restriction on performance score, study location, the number of arms, life expectancy restriction, and the number of target size. Among these factors, the number of centers (odds ratio [OR] = 0.83, 95% CI: 0.71, 0.94), study being in non-US only vs. US only (OR = 0.32, 95% CI: 0.12, 0.82), and life expectancy restriction (OR = 2.17, 95% CI: 1.04, 4.73) were significantly associated with the trial failure.

DISCUSSION

We identified trial-level factors predictive of trial failure among older adult-specific clinical trials and developed a prediction model that can help estimate the risk of failure before a study is conducted. The study findings could aid in the design and prioritization of future older adult-specific clinical trials.

Promise of Real-World Evidence for Patient Centricity in Gulf Cooperation Council Countries: Call to Action

Presently, Gulf Cooperation Council countries are lagging in the generation of real-world data and use of real-world evidence for patient-centered care compared with the global average. In a collaborative effort, experts from multiple domains of the healthcare environment from the Gulf Cooperation Council countries came together to present their views and recommended key action points for the generation of robust real-world data and leveraging real-world evidence in the countries. The opinions of the experts are presented, along with existing barriers to the effective generation of real-world evidence in the countries. The Gulf Cooperation Council countries are undergoing transformative changes paving the way for improved healthcare measures; however, the challenges in generating reliable, robust, accessible, and secure real-world evidence are persistent. Hence, ongoing public-private engagements, as well as collaborations between regulators, policymakers, healthcare professionals, insurance and pharmaceutical companies, and patients, are warranted. A few notable examples of real-world evidence studies highlighting the benefits of real-world evidence for gaining valuable insights into patient-centric decision making are also discussed. The actionable steps identified for successful real-world evidence generation would provide long-term, real-world evidence-based patient-centric benefits for the countries.

Implementing Modernized Eligibility Criteria in US National Cancer Institute Clinical Trials

In 2018, the Cancer Therapy Evaluation Program (CTEP) at the US National Cancer Institute published new protocol template language that focused on organ function and prior and concurrent cancers in an effort to modernize eligibility criteria for cancer treatment trials. We conducted an analysis of CTEP-supported trials to evaluate the uptake and incorporation of the new language. The analysis included evaluation of 122 protocols approved in the years 2018-2020 for inclusion of the modernized eligibility criteria and consistency with new protocol template language related to 7 major eligibility criteria. These were cardiac function, liver function, kidney function, HIV status, prior and/or concurrent malignancies, treated and/or stable brain metastasis, and new and/or progressive brain metastases. Overall, CTEP trials evaluated in this period demonstrated that eligibility criteria were implemented to a relatively high degree ranging from a low of 54.1% for prior and/or concurrent malignancies to a high of 93.4% for eligibility criteria related to HIV infection. The findings demonstrate that modernized eligibility criteria can be successfully implemented but that consistent implementation requires sustained focused effort. As a result of these findings, CTEP began a new initiative in January 2022 that incorporates a specific review of eligibility criteria for new protocols to promote and improve consistency with the modernization effort.

Rapid Review of Real-World Cost-Effectiveness Analyses of Cancer Interventions in Canada

Cost-effectiveness analysis (CE Analysis) provides evidence about the incremental gains in patient outcomes costs from new treatments and interventions in cancer care. The utilization of "real-world" data allows these analyses to better reflect differences in costs and effects for actual patient populations with comorbidities and a range of ages as opposed to randomized controlled trials, which use a restricted population. This rapid review was done through PubMed and Google Scholar in July 2022. Relevant articles were summarized and data extracted to summarize changes in costs (in 2022 CAD) and effectiveness in cancer care once funded by the Canadian government payer system. We conducted statistical analyses to examine the differences between means and medians of costs, effects, and incremental cost effectiveness ratios (ICERs). Twenty-two studies were selected for review. Of those, the majority performed a CE Analysis on cancer drugs. Real-world cancer drug studies had significantly higher costs and effects than non-drug therapies. Studies that utilized a model to project longer time-horizons saw significantly smaller ICER values for the treatments they examined. Further, differences in drug costs increased over time. This review highlights the importance of performing real-world CE Analysis on cancer treatments to better understand their costs and impacts on a general patient population.

Exclusion of older adults from clinical trials in cancer-related pain

Pain is one of the most common symptoms in cancer patients including older adults. The objective of this study was to evaluate the enrollment criteria that can limit the inclusion of older adults in clinical trials concerning cancer-related pain (CRP). The study included 356 trials registered with ClinicalTrials.gov. Our primary outcome measures were the proportion of trials that excluded patients based on upper age limits (80 years of age or less), strict organ-specific exclusion criteria, broad and imprecise criteria, and inadequate performance score. One hundred and twenty-six trials (35.4%) had upper age limits. Strict exclusion criteria were used in 95 (26.7%) trials. Broad and imprecise exclusion criteria were listed in 57 (16.2%) trials. Low performance score was used as an exclusion criterion in 4 trials (1.1%). Overall, in 241 trials (67.7%) there was either an upper age limit or at least one strict or broad and imprecise exclusion criterion, or a criterion involving the performance status. The odds of excluding older adults were significantly higher in certain neoplasm types, study objectives, intervention types, and center locations. In conclusion, considerable proportion of recent clinical trials concerning CRP either explicitly exclude older adults or create high risk of such exclusion which substantially limits the evidence base for the treatment of such patients in clinical practice. Sponsors and investigators should consider careful modification of the enrollment criteria to improve the inclusion of older individuals who make up the major proportion of cancer patients population.

Optimizing systemic therapy for advanced hepatocellular carcinoma: the key role of liver function

The number of effective systemic therapies for the treatment of advanced hepatocellular carcinoma (HCC) is rapidly increasing, and the advent of immunotherapy has changed the treatment paradigm for these patients, leading to significantly improved survival outcomes. However, many patients with HCC will continue to receive tyrosine kinase inhibitors, partly because of contraindications to immune checkpoint inhibitors. Currently, the best sequential first- and second-line systemic treatment remains elusive. Maintenance of optimal liver function is crucial, it is likely to impinge on temporary or permanent treatment discontinuation, and should also be considered when defining the treatment sequence. Hepatic decompensation, which does not always coincide with disease progression, is part of this complex dynamically evolving system, and must be promptly recognized and adequately managed to allow the patient to continue in the therapeutic course. The purpose of this review is to highlight and summarize the evidence on the efficacy and safety of systemic agents, with a focus on the impact of underlying cirrhosis, and to suggest new clinical outcomes for randomized controlled trials for advanced HCC to better assess the net health benefit in this specific setting.

Under-served groups remain underserved as eligibility criteria routinely exclude them from breast cancer trials

OBJECTIVES

Under-served groups are populations unrepresented or disengaged from medical research or services despite a disproportionately high healthcare burden. Under-served groups may be directly (age, pregnancy as examples) or indirectly excluded (provision of written information in one language only as example) from trial enrolment by strict eligibility exclusions. The purpose of our study was to assess eligibility criteria in published phase III breast cancer clinical trials to determine whether they excluded under-served groups either directly, or indirectly.

STUDY DESIGN AND SETTING

Medline was searched for phase III randomised controlled trials evaluating interventional drugs for breast cancer in high-impact journals published between January 1^st, 2010 and December 31st, 2020. 5133 eligible trials were returned and 40 selected, by simple randomization, for inclusion.

RESULTS

All 40 trials had multiple exclusions that affected recruitment of under-served groups. Clinical or scientific rationale for the recorded inclusion and exclusion criteria was under-reported in 39 of 40 trials.

CONCLUSIONS

Clinical trial eligibility criteria exclude under-served groups from breast cancer trials. Trialists should provide a justification for each eligibility criterion and funders, reviewers, ethics committees, and others should demand one. Without this under-served groups will remain just that: under-served.

Leveraging electronic health record data for clinical trial planning by assessing eligibility criteria's impact on patient count and safety

OBJECTIVE

To present an approach on using electronic health record (EHR) data that assesses how different eligibility criteria, either individually or in combination, can impact patient count and safety (exemplified by all-cause hospitalization risk) and further assist with criteria selection for prospective clinical trials.

MATERIALS AND METHODS

Trials in three disease domains - relapsed/refractory (r/r) lymphoma/leukemia; hepatitis C virus (HCV); stages 3 and 4 chronic kidney disease (CKD) - were analyzed as case studies for this approach. For each disease domain, criteria were identified and all criteria combinations were used to create EHR cohorts. Per combination, two values were derived: (1) number of eligible patients meeting the selected criteria; (2) hospitalization risk, measured as the hazard ratio between those that qualified and those that did not. From these values, k-means clustering was applied to derive which criteria combinations maximized patient counts but minimized hospitalization risk.

RESULTS

Criteria combinations that reduced hospitalization risk without substantial reductions on patient counts were as follows: for r/r lymphoma/leukemia (23 trials; 9 criteria; 623 patients), applying no infection and adequate absolute neutrophil count while forgoing no prior malignancy; for HCV (15; 7; 751), applying no human immunodeficiency virus and no hepatocellular carcinoma while forgoing no decompensated liver disease/cirrhosis; for CKD (10; 9; 23893), applying no congestive heart failure.

CONCLUSIONS

Within each disease domain, the more drastic effects were generally driven by a few criteria. Similar criteria across different disease domains introduce different changes. Although results are contingent on the trial sample and the EHR data used, this approach demonstrates how EHR data can inform the impact on safety and available patients when exploring different criteria combinations for designing clinical trials.

Key considerations and common adverse events for HIV-positive patients with cancer treated with immune checkpoint inhibitors

HIV-infected patients are more susceptible to cancer due to their immune-compromised condition and HIV infection. Chronic inflammation and immune dysregulation are the main causes of cancer development in these patients. Because of lymphopenia and an immune-compromised condition, most HIV-infected patients with cancer were not considered for cytotoxic therapies, such as chemotherapy and radiotherapy. Immune checkpoint inhibitors (ICIs) have become a game-changer in many cancer types. However, not enough prospective data is available regarding the use of ICIs in HIV-infected patients with cancer. Retrospective data from case reports/series showed that ICIs are safe in HIV-infected patients with cancer.

Trial-level factors affecting accrual and completion of oncology clinical trials: A systematic review

BACKGROUND

Cancer is the second-leading cause of death in the United States. Clinical trials translate basic science discoveries into treatments needed by cancer patients. Inadequate accrual of trial participants is one of the most significant barriers to the completion of oncology clinical trials.

OBJECTIVE

The purpose of this study was to investigate trial-level factors that affect accrual and/or completion of oncology clinical trials, identify gaps in the literature, and indicate opportunities for future research.

DESIGN

A systematic review of the literature on trial-level factors that affect accrual and/or completion of oncology clinical trials was performed. Searches in PubMed and Scopus identified 6582 studies. Based on eligibility criteria, 16 studies were selected for the review. Results were analyzed according to the following: a) background factors, b) disease-related, c) treatment-related, and d) trial design.

RESULTS

Background factors that were investigated in relation to oncology clinical trial accrual and/or completion included sponsor, number and location of participating institutions, competing trials, time of trial opening, and fast-track status. Disease-related factors included the annual incidence and type(s) of targeted cancer. Several types of treatment such as drugs, radiation and surgery were examined in the studies. Trial design factors included trial development time, eligibility criteria, randomization, sample size, trial phase, placebo use, and required protocol procedures and their timing.

CONCLUSION

With low patient participation rates in oncology clinical trials that hold promise for future treatments, it is imperative that trial-level factors affecting accrual be identified and addressed to facilitate the completion of trials.

Lupus clinical trial eligibility in a real-world setting: results from the British Isles Lupus Assessment Group-Biologics Register (BILAG-BR)

OBJECTIVE

To quantify how well phase III randomised clinical trials in both SLE and lupus nephritis (LN) represents a real-world SLE cohort.

METHODS

Literature reviews were performed of major published phase III SLE (n=12) and LN (n=6) clinical trials (ClinicalTrials.gov). Inclusion and exclusion criteria common across these trials were collated for non-renal SLE or LN trials, and applied to patients recruited to the British Isles Lupus Assessment Group-Biologics Register (BILAG-BR) starting either biological or standard-of-care (SOC) therapies.

RESULTS

We recruited 837 patients to the BILAG-BR from September 2010 to June 2018, starting either SOC (n=125, 15%) or a biological medication (n=712, 85%). Active LN, defined as a BILAG A in the renal domain occurred in 20% (n=166). Overall, 530 (63%) patients were ineligible to participate in non-renal SLE clinical trials and 72 (43%) patients with active LN would be ineligible for LN trials. The most common reasons for ineligibility from the non-renal lupus trials included active renal involvement (n=166, 20%) and low disease activity (n=114, 15%). For LN trials, the most common exclusion met was pre-existing renal impairment (n=15, 9%). Patients with fewer comorbidities were more likely to be eligible to participate in non-renal SLE trials.

CONCLUSIONS

In this national register of patients with moderate-to-severe SLE, nearly two-thirds would not be eligible for recruitment to key SLE clinical trials nor would almost half of those with active LN. Eligibility criteria may excessively constrain enrolment and thus, how we can generalise trial results in a real-world setting.

The effect of prior cancer on non-small cell lung cancer trial eligibility

Objectives

Approximately 20% of patients diagnosed with non‐small cell lung cancer (NSCLC) have a history of prior (non‐lung) cancer. Patients with prior cancer are frequently excluded from clinical trials. We aimed to assess the potential impact of prior cancer on commonly used clinical trial endpoints.

Materials and Methods

Clinical trials of systemic therapy for incurable NSCLC from clinicaltrials.gov were reviewed to determine the frequency of exclusion on the basis of prior cancer. A cohort of patients with incurable NSCLC and prior cancer, treated with first‐line systemic treatment at our institution were reviewed as a surrogate clinical trial population. A list of priori events was developed to capture the potential for prior cancer to negatively affect clinical trial conduct or endpoints. The proportions of patients that developed an outcome were assessed.

Results

Among trials registered on clinicaltrials.gov, 66% listed prior cancer in the eligibility criteria, and of these 35% excluded patients with prior cancer in the last 5 years. Of NSCLC patients treated with systemic therapy at Princess Margaret Cancer Center, 20% had prior cancer, of these, breast (20%) and prostate (19%) were the most common malignancies. Median time between prior cancer and NSCLC was 82 months. Median survival was 20 months. For patients without evidence of active prior cancer at baseline, and not on active therapy for prior cancer, no patients had evidence of a recurrence of prior cancer during the treatment and follow‐up for the NSCLC, nor died from prior cancer. However, two patients developed new primaries.

Conclusions

A history of prior cancer has a low likelihood of impacting clinical trial endpoints in patients with incurable NSCLC, if not active or requiring treatment. These findings should be validated in larger data sets.

Reporting of Study Participant Demographic Characteristics and Demographic Representation in Premarketing and Postmarketing Studies of Novel Cancer Therapeutics

IMPORTANCE

Adequate representation of demographic subgroups in premarketing and postmarketing clinical studies is necessary for understanding the safety and efficacy associated with novel cancer therapeutics.

OBJECTIVE

To characterize and compare the reporting of demographic data and the representation of individuals by sex, age, and race in premarketing and postmarketing studies used by the Food and Drug Administration (FDA) to evaluate novel cancer therapeutics.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, premarketing and postmarketing studies for novel cancer therapeutics approved by the FDA from 2012 through 2016 were identified. Study demographic information was abstracted from publicly available sources, and US cancer population demographic data was abstracted from US Cancer Statistics. Analyses were conducted from February 25 through September 21, 2020.

MAIN OUTCOMES AND MEASURES

The percentages of trials reporting sex, age, and race/ethnicity were calculated, and participation to prevalence ratios (PPRs) were calculated by dividing the percentage of study participants in each demographic group by the percentage of the US cancer population in each group. PPRs were constructed for premarketing and postmarketing studies and by cancer type. Underrepresentation was defined as PPR less than 0.8.

RESULTS

From 2012 through 2016, the FDA approved 45 cancer therapeutics. The study sample included 77 premarketing studies and 56 postmarketing studies. Postmarketing studies, compared with premarketing studies, were less likely to report patient sex (42 studies reporting [75.0%] vs 77 studies reporting [100%]; P < .001) and race (27 studies reporting [48.2%] vs 62 studies reporting [80.5%]; P < .001). Women were adequately represented in premarketing studies (mean [SD] PPR, 0.91; 95% CI, 0.90-0.91) and postmarketing studies (mean PPR, 1.00; 95% CI, 1.00-1.01). Although older adults and Black patients were underrepresented in premarketing studies (older adults: mean PPR, 0.73; 95% CI, 0.72-0.74; Black patients: mean PPR, 0.32; 95% CI, 0.31-0.32), these groups continued to be underrepresented in postmarketing studies (older adults: mean PPR, 0.75; 95% CI, 0.75-0.76; Black patients: mean PPR, 0.21; 95% CI, 0.21-0.21).

CONCLUSIONS AND RELEVANCE

This study found that older adults and Black patients were underrepresented in postmarketing studies of novel cancer therapeutics to a similar degree that they were underrepresented in premarketing studies. These findings suggest that postmarketing studies are not associated with improvements to gaps in demographic representation present at the time of FDA approval.

Hematologists' barriers and enablers to screening and recruiting patients to a chimeric antigen receptor (CAR) T cell therapy trial: a theory-informed interview study

BACKGROUND

Novel therapies often fail to reach the bedside due to low trial recruitment rates. Prior to conducting one of the first chimeric antigen receptor (CAR) T cell therapy trials in Canada, we used the Theoretical Domains Framework, a novel tool for identifying barriers and enablers to behavior change, to identify physician-related barriers and enablers to screening and recruiting patients for an early phase immunotherapy trial.

METHODS

We conducted interviews with hematologists across Canada and used a directed content analysis to identify relevant domains reflecting the key factors that may affect screening and recruitment.

RESULTS

In total, we interviewed 15 hematologists. Physicians expressed "cautious hope"; while expressing safety, feasibility, and screening criteria concerns, 14 out of 15 hematologists intended to screen for the trial (domains: knowledge, goals, beliefs about consequences, intentions). Physicians underscored the "challenging contexts," identifying resources, workload, forgetting, and patient wait times to receive CAR T cells as key practical barriers to screening (domains: environmental context and resources, memory, attention and decision-making, behavioral regulation). They also highlighted "variability in roles and procedures" that may lead to missed trial candidates (domain: social and professional role). Left unaddressed, these barriers may undermine trial recruitment.

CONCLUSIONS

This study is among the first to use the Theoretical Domains Framework from the physician perspective to identify recruitment challenges to early phase trials and demonstrates the value of this approach for identifying barriers to screening and recruitment that may not otherwise have been elicited. This approach can optimize trial procedures and may serve to inform future promising early phase cancer therapy trials.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03765177 . Registered on December 5, 2018.

The Development of Practice Recommendations for Drug-Disease Interactions by Literature Review and Expert Opinion

Background

Drug-disease interactions negatively affect the benefit/risk ratio of drugs for specific populations. In these conditions drugs should be avoided, adjusted, or accompanied by extra monitoring. The motivation for many drug-disease interactions in the Summary of Product Characteristics (SmPC) is sometimes insufficiently supported by (accessible) evidence. As a consequence the translation of SmPC to clinical practice may lead to non-specific recommendations. For the translation of this information to the real world, it is necessary to evaluate the available knowledge about drug-disease interactions, and to formulate specific recommendations for prescribers and pharmacists. The aim of this paper is to describe a standardized method how to develop practice recommendations for drug-disease interactions by literature review and expert opinion.

Methods

The development of recommendations for drug-disease interactions will follow a six-step plan involving a multidisciplinary expert panel (1). The scope of the drug-disease interaction will be specified by defining the disease and by describing relevant effects of this drug-disease interaction. Drugs possibly involved in this drug-disease interaction are selected by checking the official product information, literature, and expert opinion (2). Evidence will be collected from the official product information, guidelines, handbooks, and primary literature (3). Study characteristics and outcomes will be evaluated and presented in standardized reports, including preliminary conclusions on the clinical relevance and practice recommendations (4). The multidisciplinary expert panel will discuss the reports and will either adopt or adjust the conclusions (5). Practice recommendations will be integrated in clinical decision support systems and published (6). The results of the evaluated drug-disease interactions will remain up-to-date by screening new risk information, periodic literature review, and (re)assessments initiated by health care providers.

Actionable Recommendations

The practice recommendations will result in advices for specific DDSI. The content and considerations of these DDSIs will be published and implemented in all Clinical Decision Support Systems in the Netherlands.

Discussion

The recommendations result in professional guidance in the context of individual patient care. The professional will be supported in the decision making in concerning pharmacotherapy for the treatment of a medical problem, and the clinical risks of the proposed medication in combination with specific diseases.

Demographic Characteristics of Participants in Rheumatoid Arthritis Randomized Clinical Trials: A Systematic Review

IMPORTANCE

Racial/ethnic minority groups, women, and elderly people experience a disproportionate burden of disease in rheumatoid arthritis (RA), making it particularly important to examine drug therapies in these populations. Despite a national health agenda to improve representation of diverse populations in randomized clinical trials (RCTs), there have been few large-scale analyses examining RCT demographic characteristics within rheumatology and none focusing on RA.

OBJECTIVE

To characterize the representation of racial/ethnic minority groups, women, and elderly people through a comprehensive systematic review of RA RCTs.

DATA SOURCES

A literature search of PubMed's MEDLINE database was conducted to identify RA RCTs in adults 19 years and older published in English between January 1, 2008, and January 1, 2018.

STUDY SELECTION

Randomized double-blind RCTs examining any systemic, disease-modifying therapy were included. Secondary analyses of previously published RCTs were excluded. Of 1195 identified records, 240 articles (20.1%) met final selection criteria. The analysis focused on RCTs with at least 1 US-based site.

DATA EXTRACTION AND SYNTHESIS

Data were extracted and synthesized according to the PRISMA guidelines for systematic reviews. Studies were screened for eligibility criteria. Demographic data on the age, sex, and race/ethnicity of RCT participants were extracted. Data analysis was conducted from October 25, 2018, to March 15, 2019.

MAIN OUTCOMES AND MEASURES

Representation of race/ethnicity and sex, defined as the proportion of total participants that belonged to each racial/ethnic group or sex. Trends in proportions over time were examined and compared with US demographic data.

RESULTS

A total of 240 RCTs with 77 071 participants were included. Of 126 RCTs with at least 1 US-based site (52.5%), the enrollment of minority racial/ethnic groups was significantly lower than their representation within the US Census population (16% vs 40%; P < .001), and the enrollment of men was significantly lower than the incidence of RA in men nationally (20.4% vs 28.6%; P < .001). There was no trend toward improved representation of racial/ethnic minority groups or men over time.

CONCLUSIONS AND RELEVANCE

Given the disproportionate burden of RA among racial/ethnic minority groups, it is imperative that policy makers better incentivize the inclusion of racial/ethnic minority groups in RA RCTs.

Role of real-world evidence in informing cancer care: lessons from colorectal cancer

The term "real-world evidence" (rwe) describes the analysis of data that are collected beyond the context of clinical trials. The use and application of rwe have become increasingly common and relevant, especially in oncology, because there is growing recognition that randomized controlled trials (rcts) might not be sufficiently representative of the entire patient population that is affected by cancer, and that specific clinical research questions might be best addressed by real-world data. In this brief review, our main aim is to highlight the role of rwe in informing cancer care, particularly focusing on specific examples from colorectal cancer. Our hope is to illustrate the ways in which rwe can complement rcts in improving the understanding of cancer management and how rwe can facilitate cancer treatment decisions for real-world patients encountered in routine clinical care.