Survival Benefit Associated With Participation in Clinical Trials of Anticancer Drugs: A Systematic Review and Meta-Analysis.

Importance: Many cancer clinical investigators view clinical trials as offering better care for patients than routine clinical care. However, definitive evidence of clinical benefit from trial participation (hereafter referred to as the participation effect) has yet to emerge. Objective: To conduct a systematic review and meta-analysis of the evidence examining whether patient participation in cancer trials was associated with greater survival benefit compared with routine care. Data Sources: Studies were found through PubMed and Embase (January 1, 2000, until August 31, 2022), as well as backward and forward citation searching. Study Selection: Studies were included that compared overall survival of trial participants and routine care patients. Data Extraction and Synthesis: Data extraction and methodological quality assessment were completed by 2 independent coders using Covidence software. Data were pooled using a random-effects model and analyzed based on the quality of the comparison between trial participants and routine care patients (ie, extent to which studies controlled for bias and confounders). Main Outcomes and Measures: The hazard ratio (HR) for overall survival of trial participants vs routine care patients. Results: Thirty-nine publications were included, comprising 85 comparisons of trial participants and routine care patients. The meta-analysis revealed a statistically significant overall survival benefit for trial participants (HR, 0.76 [95% CI, 0.69-0.82]) when all studies were pooled, regardless of design or quality. However, survival benefits diminished in study subsets that matched trial participants and routine care patients for eligibility criteria (HR, 0.85 [95% CI, 0.75-0.97]) and disappeared when only high-quality studies were pooled (HR, 0.91 [95% CI, 0.80-1.05]). They also disappeared when estimates were adjusted for potential publication bias (HR, 0.94 [95% CI, 0.86-1.03]). Conclusions and Relevance: Many studies suggest a survival benefit for cancer trial participants. However, these benefits were not detected in studies using designs addressing important sources of bias and confounding. Pooled results of high-quality studies are not consistent with a beneficial effect of trial participation on its own.

The Benefits and Risks of Receiving Investigational Solid Tumor Drugs in Randomized Trials : A Systematic Review and Meta-analysis.

BACKGROUND: Many patients participate in cancer trials to access new therapies. The extent to which new treatments produce clinical benefit for trial participants is unclear. PURPOSE: To estimate the progression-free survival (PFS) and overall survival (OS) advantage of assignment to experimental groups in randomized trials for 6 solid tumors. DATA SOURCES: ClinicalTrials.gov was searched for trials of investigational drugs with results posted between 2017 and 2021. STUDY SELECTION: Investigational drugs were defined as those not yet having full approval from the U.S. Food and Drug Administration for the study indication. Trials were included if they were randomized and tested drugs or biologics. DATA EXTRACTION: Data extraction was completed by 2 independent reviewers. Data were pooled using a random-effects model. DATA SYNTHESIS: The sample included 128 trials comprising 141 comparisons of a new drug and a comparator. These comparisons included 47 050 patients. The pooled hazard ratio for PFS was 0.80 (95% CI, 0.75 to 0.85), indicating statistically significant benefit for patients in experimental groups. This corresponded to a median PFS advantage of 1.25 months (CI, 0.80 to 1.68 months). The pooled hazard ratio for OS was 0.92 (CI, 0.88 to 0.95), corresponding to a survival gain of 1.18 months (CI, 0.72 to 1.71 months). The absolute risk for a serious adverse event for comparator group patients was 29.56% (CI, 26.64% to 32.65%), with an increase in risk of 7.40% (CI, 5.66% to 9.14%) for patients in experimental groups. LIMITATIONS: Trials in this sample were heterogeneous. Comparator group interventions were assumed to reflect standard of care. CONCLUSION: Assignment to experimental groups produces statistically significant survival gains. However, the absolute survival gain is small, and toxicity is statistically significantly greater. The findings of this review provide reassuring evidence that patients are not meaningfully disadvantaged by assignment to comparator groups. PRIMARY FUNDING SOURCE: Canadian Institutes of Health Research.

The impact of feedback training on prediction of cancer clinical trial results.

INTRODUCTION: Funders must make difficult decisions about which squared treatments to prioritize for randomized trials. Earlier research suggests that experts have no ability to predict which treatments will vindicate their promise. We tested whether a brief training module could improve experts' trial predictions. METHODS: We randomized a sample of breast cancer and hematology-oncology experts to the presence or absence of a feedback training module where experts predicted outcomes for five recently completed randomized controlled trials and received feedback on accuracy. Experts then predicted primary outcome attainment for a sample of ongoing randomized controlled trials. Prediction skill was assessed by Brier scores, which measure the average deviation between their predictions and actual outcomes. Secondary outcomes were discrimination (ability to distinguish between positive and non-positive trials) and calibration (higher predictions reflecting higher probability of trials being positive). RESULTS: A total of 148 experts (46 for breast cancer, 54 for leukemia, and 48 for lymphoma) were randomized between May and December 2017 and included in the analysis (1217 forecasts for 25 trials). Feedback did not improve prediction skill (mean Brier score for control: 0.22, 95% confidence interval = 0.20-0.24 vs feedback arm: 0.21, 95% confidence interval = 0.20-0.23; p = 0.51). Control and feedback arms showed similar discrimination (area under the curve = 0.70 vs 0.73, p = 0.24) and calibration (calibration index = 0.01 vs 0.01, p = 0.81). However, experts in both arms offered predictions that were significantly more accurate than uninformative forecasts of 50% (Brier score = 0.25). DISCUSSION: A short training module did not improve predictions for cancer trial results. However, expert communities showed unexpected ability to anticipate positive trials.Pre-registration record: https://aspredicted.org/4ka6r.pdf.

Probability of Regulatory Approval Over Time: A Cohort Study of Cancer Therapies.

PURPOSE: New cancer therapies are frequently evaluated in multiple disease indications. We evaluated whether the probability of achieving US Food and Drug Administration (FDA) approval for a new cancer therapy changes with time. METHODS: We identified a cohort of anticancer drugs with a first registered efficacy trial from 2007 to 2011 on ClinicalTrials.gov. We downloaded all clinical trials for each included drug from the initiation of efficacy testing to January 11, 2021. Each trial was categorized by cancer indication and assigned to investigational trajectories on the basis of unique drug-indication pairings. We performed a univariate Cox's proportional hazards regression to assess the probability of a trajectory leading to regulatory approval over time since initiation of the first efficacy trial for a given drug. RESULTS: We included 213 drugs in our cohort, of which 37 (17.4%) received FDA approval in at least one oncology indication. In our primary analysis, we found a 15% decrease in the probability of approval for every year since initiation of the first efficacy trial (hazard ratio [HR], 0.85 [95% CI, 0.73 to 0.99]; P = .032). We found a 45% increase in the probability of approval for the first trajectory launched for a given drug in comparison with all others (HR, 0.55 [95% CI, 0.33 to 0.91]; P = .021). CONCLUSION: Drug-indication pairings pursued years after initial testing for efficacy have lowered probability of affecting care. Clinical trial investigators, sponsors, and regulatory bodies may benefit from awareness of this trend when considering both early and late trajectory trials in a drug's development.

Timing for First-in-Minor Clinical Trials of New Cancer Drugs.

OBJECTIVES: To describe the delay for first-in-minor cancer clinical trials and its relationship with the Food and Drug Administration (FDA) approval. STUDY DESIGN: We used ClinicalTrials.gov to create a sample of pediatric-relevant cancer drugs starting efficacy testing in adults from 2006 through 2011. We characterized the delay between first-in-adult efficacy trials and first-in-minor trials. We also assessed the proportion of drugs evaluated in minors that failed to gain approval, the proportions that were not evaluated in minors before receiving the FDA approval, and whether shorter delay was associated with larger effect sizes or greater probability of regulatory approval. RESULTS: Thirty-four percent of the 185 drugs in our cohort were evaluated in minors; the median delay to clinical trials was 4.16 years. Of all drugs, 17% received the FDA approval, 41% of which were never tested in minors before licensing. Of the 153 drugs not attaining approval, 78% were not evaluated in minors. Earlier testing did not significantly predict greater response rates (P = .13). Drugs not attaining regulatory approval were evaluated significantly earlier (3.0 for drugs not approved vs 5.4 years delayed testing for approved drugs, P = .019). CONCLUSIONS: New cancer drugs were typically evaluated in minors years after adult efficacy evaluation. This delay likely eliminated some drugs lacking desirable pharmacology before pediatric testing. However, some drugs that were eliminated may have had activity in pediatric indications. Approaches for prioritizing drugs for pediatric testing warrants further consideration.

Large numbers of patients are needed to obtain additional approvals for new cancer drugs: A retrospective cohort study.

Patients endure risk and uncertainty when they participate in clinical trials. We previously estimated that 12,217 patient-participants are required to bring a new cancer drug to market. However, many development efforts are aimed at extending the label of already approved drugs. Herein, we estimate the number of patients required to extend the indication of an FDA approved cancer drug. We identified all anti-cancer drugs approved by the FDA 2012 to 2015. We searched clinicaltrials.gov to identify all drug development trajectories (i.e., a series of one or more clinical trials testing a unique drug-indication pairing) launched after FDA approval for each drug. We identified which trajectories produced the following milestones: secondary FDA approvals, secondary FDA approvals achieving substantial clinical benefit in ESMO-MCBS, and recommendations in NCCN clinical practice guidelines. Using the total enrollment, we estimated the number of patients needed to reach each milestone. Forty-two drugs were approved by the FDA between 2012 and 2015, leading to 451 post-approval trajectories enrolling 129,548 patients. Fourteen secondary FDA approvals were identified, of which 4 met the ESMO-MCBS definition of substantial clinical benefit. Fourteen NCCN off-label recommendations were obtained. A total of 9253, 32,387 and 4627 patients were needed to attain an FDA approval, an approval with substantial clinical benefit on ESMO-MCBS, and an NCCN guideline recommendation, respectively. The number of patients needed to obtain a first secondary FDA approval was 16,596. Large numbers of patients are needed to extend the label of prior FDA approved drugs. Label extension after approval entails lower marginal costs for developers. However, extra knowledge available to researchers about a drug's safety and pharmacology after FDA approval does not appear to translate into reduced patient numbers required for developing new cancer applications.

Bypassing phase 2 in cancer drug development erodes the risk/benefit balance in phase 3 trials.

OBJECTIVES: Drug developers sometimes launch phase 3 (P3) trials without supporting evidence from phase 2 (P2) trials. We call this practice "P2 bypass." The aims of this study were to estimate the prevalence of P2 bypass and to compare the safety and efficacy results for P3 trials that bypassed with those that did not. STUDY DESIGN AND SETTING: We created a sample of P3 solid tumor trials registered on ClinicalTrials.gov with primary completion dates between 2013 and 2019. We then attempted to match each with a supporting P2 trial using strict and broad criteria. P3 outcomes were meta-analyzed using a random effects model with subgroup contrast between trials that bypassed and those that did not. RESULTS: 129 P3 trial arms met eligibility and nearly half involved P2 bypass. P3 trials involving P2 bypass produced significantly and nonsignificantly worse pooled efficacy estimates using broad and strict matching criteria, respectively. We did not observe significant differences in safety outcomes between P3 trials that bypassed P2 and those that did not. CONCLUSION: The risk/benefit balance of P3 trials that bypassed P2 is less favourable than for trials supported by P2.

Participant Recruitment From Low- and Middle-Income Countries for Pivotal Trials of Drugs Approved by the U.S. Food and Drug Administration : A Cross-Sectional Analysis.

BACKGROUND: Many participants in clinical trials supporting U.S. Food and Drug Administration (FDA) drug approvals are recruited from outside the United States, including from low- and middle-income countries (LMICs). Where participants are recruited for pivotal trials has implications for ethical research conduct and generalizability. OBJECTIVE: To describe LMIC recruitment for pivotal trials of newly approved drugs for cancer, neurologic disease, and cardiovascular disease. DESIGN: Cross-sectional analysis. SETTING: Pivotal trials of new cancer, cardiovascular, and neurologic drugs approved from 2012 to 2019 matched to ClinicalTrials.gov, FDA records, and publications. MEASUREMENTS: Host countries and available per country enrollments were extracted. The primary end point was the proportion of pivotal trials enrolling participants in LMICs. The secondary end point was the proportion of pivotal trial participants contributed by LMICs for each indication area. RESULTS: Data were obtained from 66 new drugs and 144 pivotal clinical trials. All cardiovascular approvals (12 drugs, 29 trials) and neurologic approvals (26 drugs, 54 trials) were analyzed, as well as a random sample of cancer approvals (28 of 85 drugs [33%]) matched to their pivotal trials (61 of 210 trials [29%]). Among the trials, 56% in cancer, 79% in cardiovascular disease, and 56% in neurology recruited from an LMIC. For multicountry trials, country-level enrollment figures were not available for 71 trials (55%). For those reporting per country enrollment, the percentage of participants recruited from LMICs was 8% for cancer trials, 36% for cardiovascular trials, and 17% for neurology trials. LIMITATIONS: The study was limited to FDA-approved drugs in 3 areas, including a sample of cancer drugs. Pivotal trials of nonapproved drugs or drugs for other indications were not captured. CONCLUSION: Most pivotal trials for FDA-approved drugs recruit from LMICs. Publications and FDA documents generally do not provide country-level data on recruitment. PRIMARY FUNDING SOURCE: None.

Diminishing clinical impact for post-approval cancer clinical trials: A retrospective cohort study.

BACKGROUND: Once a drug gets FDA approved, researchers often attempt to discover new applications in different indications. The clinical impact of such post-approval activities is uncertain. We aimed to compare the clinical impact of research efforts started after approval with those started before for cancer drugs. METHODS: We used Drugs@FDA to perform a retrospective cohort study of secondary approvals for cancer drugs that were initially FDA approved between 2005 and 2017. Clinicaltrials.gov was used to identify the beginning of each research trajectory that resulted in a secondary FDA approval. Each trajectory was classified as pre- or post-approval depending on if it was initiated before or after initial drug licensure. Clinical impact was assessed by comparing secondary approvals and NCCN off-label recommendations deriving from pre- vs. post-approval trajectories, pooled effect sizes, incidence, and level of evidence. RESULTS: We identified 77 broad secondary approvals, 60 of which had at least 6 years follow-up. Of these, 9 (15%) resulted from post-approval trajectories, a proportion that is significantly lower than would be expected if the timing of research didn't impact approval (McNemar's test p = 0.001). Compared to pre-approval trajectories, approvals resulting from post-approval trajectories were for cancers with lower mean incidence (6.11 vs 14.83, p = 0.006) and were based on pivotal trials with smaller pooled effect sizes (0.69 vs 0.57, p = 0.02) that were less likely to be randomized (38.5% vs 64.1%, p = 0.145). We identified 69 NCCN off-label recommendations. The proportion stemming from post-approval trajectories was similar to that for pre-approval (56.5% vs. 43.5%). However, recommendations from post-approval trajectories were significantly more likely to involve rare diseases (76.7% vs 51.4%, p = 0.019) and nonsignificantly less likely to be based on level 1 evidence (11.6% vs 22.9%, p = 0.309). CONCLUSION: Secondary FDA approvals are less likely to result from post-approval trajectories and tend to be less impactful compared to approvals originating from research started before first FDA licensure. However, post-approval trajectories may be as likely to lead to NCCN recommendations for off-label use. Limitations of this work include our use of indirect measures of impact and limited follow-up time for trajectories. Our study protocol was pre-registered (https://osf.io/5g3jw/).

The proportion of randomized controlled trials that inform clinical practice.

Prior studies suggest that clinical trials are often hampered by problems in design, conduct, and reporting that limit their uptake in clinical practice. We have described 'informativeness' as the ability of a trial to guide clinical, policy, or research decisions. Little is known about the proportion of initiated trials that inform clinical practice. We created a cohort of randomized interventional clinical trials in three disease areas (ischemic heart disease, diabetes mellitus, and lung cancer) that were initiated between January 1, 2009 and December 31, 2010 using ClinicalTrials.gov. We restricted inclusion to trials aimed at answering a clinical question related to the treatment or prevention of disease. Our primary outcome was the proportion of clinical trials fulfilling four conditions of informativeness: importance of the clinical question, trial design, feasibility, and reporting of results. Our study included 125 clinical trials. The proportion meeting four conditions for informativeness was 26.4% (95% CI 18.9-35.0). Sixty-seven percent of participants were enrolled in informative trials. The proportion of informative trials did not differ significantly between our three disease areas. Our results suggest that the majority of randomized interventional trials designed to guide clinical practice possess features that may compromise their ability to do so. This highlights opportunities to improve the scientific vetting of clinical research.

Success rates for US and Canadian anticancer drug development efforts in pediatric oncology.

BACKGROUND: Approximately 5% of adult cancer interventions put into clinical testing attain regulatory approval. Little is known about corresponding rates for pediatric cancer. METHODS: Our primary outcomes were the proportion of interventions graduating to the next trial phase, randomized trials, and/or clinical practice. We created a saturation sample of clinical trials by searching ClinicalTrials.gov for all pediatric anticancer trials in the United States or Canada. Trial characteristics were extracted automatically from ClinicalTrials.gov records, and cancer indication/drug class categorization, biomarker enrichment, and Food and Drug Administration (FDA) approval status at time of recruitment were double-extracted from each record. Regulatory approval status and labeling modifications for each intervention were determined by searching Drugs@FDA and the New Pediatric Labeling Information Database. RESULTS: Five hundred eighty-nine pediatric trials launched between 1987 and 2019 were captured. The overall probability of graduation was 17.0%; 18.9% of interventions graduated from phase 1 to phase 2 trials, and 1.6% of interventions graduated from phase 2 to phase 3 trials. The proportion of interventions advancing from phase 1 to FDA approval was 3.6%, and 1.9% of interventions tested in phase 1 advanced to a randomized phase 2 trial. Only biomarker enrichment was significantly predictive of graduation from phase 1 to phase 2 trials (p = .011). CONCLUSION: The proportion of interventions advancing from phase 1 testing to FDA approval was similar to estimates for adult oncology. Our findings highlight the challenges for current paradigms of pediatric anticancer drug development.

Interventions for physician prescribers of opioids for chronic non-cancer pain: protocol for an overview of systematic reviews.

INTRODUCTION: Interventions targeting behaviours of physician prescribers of opioids for chronic non-cancer pain have been introduced to combat the opioid crisis. Systematic reviews have evaluated effects of specific interventions (eg, prescriber education, prescription drug monitoring programmes) on patient and population health outcomes and prescriber behaviour. Integration of findings across intervention types is needed to better understand the effects of prescriber-targeted interventions. METHODS AND ANALYSIS: We will conduct an overview of systematic reviews. Eligible systematic reviews will include primary studies that evaluated any intervention targeting the behaviours of physician prescribers of opioids for chronic non-cancer pain in an outpatient or mixed setting, compared with no intervention, usual practice or another active or control intervention. Eligible outcomes will pertain to the intervention effect on patient and population health or opioid prescribing behaviour. We will search MEDLINE, Embase and PsycInfo via Ovid; the Cochrane Database of Systematic Reviews and Epistemonikos from inception. We will also hand search reference lists for additional publications. Screening and data extraction will be conducted independently by two reviewers, with disagreements resolved by consensus or consultation with a third reviewer. The risk of bias of included systematic reviews will be assessed in duplicate by two reviewers using the Risk of Bias in Systematic Reviews tool. Results will be synthesised narratively by intervention type and grouped by outcome. To assist with result interpretation, outcomes will be labelled as intended or unintended according to intervention objectives, and as positive, negative, evidence of no effect or inconclusive evidence according to effect on the population (for patient and population health outcomes) or intervention objectives (for prescriber outcomes). ETHICS AND DISSEMINATION: As the proposed study will use published data, ethics approval is not required. Dissemination of results will be achieved through publication of a manuscript in a peer-reviewed journal and conference presentations. PROSPERO REGISTRATION NUMBER: CRD42020156815.

Ethical Considerations for Phase I Trials in Oncology.

Phase I trials often represent the first occasion where new cancer strategies are tested in patients. Various developments in cancer biology, methodology, regulation, and medical ethics have altered the ethical landscape of such trials. We provide a narrative review of contemporary ethical challenges in design, conduct, and reporting of phase I cancer trials and outline recommendations for addressing each. We organized our review around four topics, supplementing the first three with scoping reviews: (1) benefit/risk, (2) research biopsies, (3) therapeutic misconception and misestimation, and (4) reporting. The main ethical challenges of conducting phase I trials stem from three issues. First, phase I trials often involve higher research burden and scientific uncertainty compared with other cancer trials. Second, many patients arrive at phase I trials at a transitional point in their illness trajectory where they have exhausted standard survival-extending options. Third, phase I trial results play a major role in informing downstream drug development and regulatory decisions. Together, these issues create distinct pressures for study design, ethical review, informed consent, and reporting. Developments in methodology, regulation, cancer biology, and ethical awareness have helped mitigate some of these challenges, while introducing others. We conclude our review with a series of recommendations regarding trial design, ethical review, consent, and reporting. We also outline several unresolved questions that, if addressed, would strengthen the ethical foundation of phase I cancer trials.

Is preclinical research in cancer biology reproducible enough?

The Reproducibility Project: Cancer Biology (RPCB) was established to provide evidence about reproducibility in basic and preclinical cancer research, and to identify the factors that influence reproducibility more generally. In this commentary we address some of the scientific, ethical and policy implications of the project. We liken the basic and preclinical cancer research enterprise to a vast 'diagnostic machine' that is used to determine which clinical hypotheses should be advanced for further development, including clinical trials. The results of the RPCB suggest that this diagnostic machine currently recommends advancing many findings that are not reproducible. While concerning, we believe that more work needs to be done to evaluate the performance of the diagnostic machine. Specifically, we believe three questions remain unanswered: how often does the diagnostic machine correctly recommend against advancing real effects to clinical testing?; what are the relative costs to society of false positive and false negatives?; and how well do scientists and others interpret the outputs of the machine?

Patient Participation in Clinical Trials of Oncology Drugs and Biologics Preceding Approval by the US Food and Drug Administration.

Importance: Several studies have estimated the financial inputs for successful drug development. Such analyses do not capture the large investment that patient study participants commit to drug development. Objective: To estimate the volume of patients required to achieve a first US Food and Drug Administration (FDA) approval for a new anticancer drug or biologic therapy. Design, Setting, and Participants: This cohort study included a random sample of prelicense oncology drugs and biologics with a trial site in the United States that were launched into clinical efficacy testing between January 1, 2006, and December 31, 2010. Drugs and biologics were identified using ClinicalTrials.gov registration records. Total patient enrollment was captured over an 8-year span, and each intervention was classified based on whether it received FDA approval and was deemed as having intermediate or substantial value according to the American Society of Clinical Oncology Value Framework (ASCO-VF) score. Secondarily, the association between patient numbers and intervention characteristics was tested. Data were analyzed in February 2020. Main Outcomes and Measure: The prespecified primary outcome was the number of patients enrolled in prelicense trials per FDA approval. Results: A total of 120 drugs and biologics were included in our study, with 84 (70.0%) targeted agents, 20 (16.7%) immunotherapies, and 71 (59.2%) novel agents. A total of 13 drugs and biologics (10.8%; 95% CI, 5.3%-16.8%) in our sample gained FDA approval within 8 years, of which 1 (7.7%) was deemed of intermediate value and 3 (23.1%) were deemed of substantial value using ASCO-VF scoring. Overall, 158 810 patients were enrolled in 1335 trials testing these drugs and biologics, 47 913 (30.2%) in trials that led to FDA approval and 110 897 (69.8%) in trials that did not. An estimated 12 217 (95% CI, 7970-22 215) patient study participants contributed to prelicense trials per FDA approval. The estimated number of patients needed to produce a single FDA-approved drug or biologic of intermediate or substantial ASCO-VF clinical value was 39 703 (95% CI, 19 391-177 991). Conclusions and Relevance: The results of this cohort study make visible the substantial patient investment required for prelicense oncology drug development. Such analyses can be used to devise policies that maximize the clinical impact of research on a per-patient basis.

Systematic review and narrative review lead experts to different cancer trial predictions: a randomized trial.

OBJECTIVES: The objective of the study was to assess the impact of narrative review (NR) vs. systematic review (SR) on expert assessments of a clinical trial. STUDY DESIGN AND SETTING: Experts in colon and rectal surgery were randomized to read an NR or SR for an ongoing clinical trial involving surgery for colorectal cancer. Experts from the United States and Canada completed online or paper surveys between December 2018 and June 2019. After reading the NR or SR, experts predicted the trial's outcome and evaluated the trial under a hypothetical ethical review. RESULTS: Experts who read the NR (n = 55) compared with those who read the SR (n = 56) were more likely to predict a higher absolute risk reduction, 58% vs. 33%, P = 0.018, mean predictions 10.6% vs. 6.6%, mean difference 4.0% [95% confidence interval: 0.3%, 7.8%]. Experts who read the NR were more likely to evaluate the trial more favorably under a hypothetical ethical review, 48% vs. 26%, P = 0.039, 20.0% vs. 8.9% "strongly in favor" of trial being pursued. CONCLUSION: An NR and an SR for the same trial led to different judgments of likely outcomes and ethical appropriateness. These differences point to a potential source of unaddressed bias in ethical review.

The proportion of North American cancer trials that evaluate novel targets.

Major advances in cancer care often emerge from the development of novel targets. We randomly sampled 10% of cancer trials on clinicaltrials.gov with start dates 2013-2016 to determine the proportion of trials and research subjects directed at evaluating novel targets. We found that 87 of 378 trials (23.0%) enrolling 9225 of 44,525 patients (20.7%) tested interventions that are directed towards novel targets. 146 of 378 trials (38.6%) enrolling 19,132 of 44,525 patients (43.0%) investigated treatments that were not FDA approved but utilized a previously studied target for treating cancer. Combined, 233 of 378 trials (61.6%) enrolling 28,357 of 44,525 patients (63.9%) investigated treatments that were not FDA approved. Furthermore, 36 of 378 trials (9.5%) enrolling 6592 of 44,525 patients (14.8%) investigated FDA approved anticancer drugs in their approved indication and combination while 109 of 378 trials (28.8%) enrolling 9576 of 44,525 patients (21.5%) investigated FDA approved anticancer drugs outside of their approved indication or combination. Logistic regression found that phase 1 trials were significantly more likely to test novel target interventions than phase 2 and 3 trials (p value = 0.00197 and 0.00130 respectively). Industry sponsored trials were also significantly more likely to involve novel target interventions than non-industry trials (p value <0.001). In conclusion, most cancer trials involve unapproved treatments, but a majority of these treatments are well-characterized or involve a previously studied target to treat cancer.

Can Oncologists Predict the Efficacy of Treatments in Randomized Trials?

BACKGROUND: Decisions about trial funding, ethical approval, or clinical practice guideline recommendations require expert judgments about the potential efficacy of new treatments. We tested whether individual and aggregated expert opinion of oncologists could predict reliably the efficacy of cancer treatments tested in randomized controlled trials. MATERIALS AND METHODS: An international sample of 137 oncologists specializing in genitourinary, lung, and colorectal cancer provided forecasts on primary outcome attainment for five active randomized cancer trials within their subspecialty; skill was assessed using Brier scores (BS), which measure the average squared deviation between forecasts and outcomes. RESULTS: A total of 40% of trials in our sample reported positive primary outcomes. Experts generally anticipated this overall frequency (mean forecast, 34%). Individual experts on average outperformed random predictions (mean BS = 0.29 [95% confidence interval (CI), 0.28-0.33] vs. 0.33) but underperformed prediction algorithms that always guessed 50% (BS = 0.25) or that were trained on base rates (BS = 0.19). Aggregating forecasts improved accuracy (BS = 0.25; 95% CI, 0.16-0.36]). Neither individual experts nor aggregated predictions showed appreciable discrimination between positive and nonpositive trials (area under the curve of a receiver operating characteristic curve, 0.52 and 0.43, respectively). CONCLUSION: These findings are based on a limited sample of trials. However, they reinforce the importance of basing research and policy decisions on the results of randomized trials rather than expert opinion or low-level evidence. IMPLICATIONS FOR PRACTICE: Predictions of oncologists, either individually or in the aggregate, did not anticipate reliably outcomes for randomized trials in cancer. These findings suggest that pooled expert opinion about treatment efficacy is no substitute for randomized trials. They also underscore the challenges of using expert opinion to prioritize interventions for clinical trials or to make recommendations in clinical practice guidelines.

Clinical development success rates and social value of pediatric Phase 1 trials in oncology.

OBJECTIVES: Drug development trials must fulfill social value requirement but no estimates of value provided by pediatric Phase 1 trials in oncology exist. These trials involve a particularly vulnerable population. Our objective was to assess of surrogates of social value of Phase 1 trials performed in pediatric oncology: rates of approval of tested interventions, transition to further phases of testing and citation in subsequent primary research reports. METHODS: We performed an analysis on a subset of eligible trials included in a previous meta-analysis. That study systematically searched EMBASE and PubMed for small sample size, non-randomized, dose escalation pediatric cancer Phase 1 studies of any malignancy, assessing chemotherapy and/or targeted therapy and looked at risk and benefit. The current analysis assessed all studies in that review published between January 1st 2004 and December 31st 2013 for predictors of social value. This time range allowed for at least five years of subsequent development activity. Sources of data included FDA and EMA medicine databases (for approval), ClinicalTrials.gov and EU Clinical Trials Register (for transition) and Google Scholar (for citation). RESULTS: One hundred thirty-nine trials enrolling 3814 patients met the eligibility criteria. Seven trials (5%) led to drugs being registered for pediatric use in therapy of cancer. Fifty-two (37%) transitioned to later phases of pediatric oncology trials according to ClinicalTrials.gov and/or EU Register. Over 90% of trials were cited by at least one subsequent primary research report or systematic review. Most of the citations were preclinical studies. CONCLUSIONS: Our analysis shows that treatments tested in pediatric Phase 1 trials in oncology have low rates of regulatory approval. However, a large proportion of Phase 1 trials inform further testing and development of tested interventions.