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Record W3137427440 · doi:10.1001/jamaoncol.2021.0379

Evolution of the Randomized Clinical Trial in the Era of Precision Oncology

2021· article· en· W3137427440 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJAMA Oncology · 2021
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsQueen's UniversityNOSM UniversityKingston Health Sciences CentreThunder Bay Regional Health Sciences Centre
Fundersnot available
KeywordsMedicineRandomized controlled trialInternal medicineSurrogate endpointBreast cancerOncologyClinical endpointColorectal cancerCohortLung cancerCancer

Abstract

fetched live from OpenAlex

IMPORTANCE: The randomized clinical trial (RCT) in oncology has evolved since its widespread adoption in the 1970s. In recent years, concerns have emerged regarding the use of putative surrogate end points, such as progression-free survival (PFS), and marginal effect sizes. OBJECTIVE: To describe contemporary trends in oncology RCTs and compare these findings with earlier eras of RCT design and output. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study of systemic therapy RCTs in breast, colorectal, and non-small cell lung cancer published in 7 major journals between 2010 and 2020. This strategy replicates prior work and allows for comparison of trends with RCTs published between 1995 to 2004 and 2005 to 2009. MAIN OUTCOMES AND MEASURES: Data on RCT design, funding, results, and reporting were extracted from the published RCT report. Findings from the current period (2010-2020) were compared with data from RCTs published from 1995 to 2004 and 2005 to 2009. Descriptive and bivariate statistics were used to analyze temporal trends. RESULTS: The cohort included 298 RCTs (132 [44%] breast, 111 [37%] non-small cell lung cancer, 55 [19%] colorectal cancer). Experimental treatment included molecular inhibitor (171 of 298 [57%]), cytotoxic (83 of 298 [28%]), hormone (15 of 298 [5%]), and immune (24 of 298 [8%]) therapies. Sixty-nine percent (206 of 298) of RCTs were of palliative intent. The most common primary end point is now PFS; this has increased substantially over time (from 0% [0 of 167] to 18% [25 of 137] to 42% [125 of 298]; P < .001). Of 298 RCTs, 265 (89%) are now funded by industry (previously 95 of 167 [57%] and 107 of 137 [78%]; P < .001). Fifty-eight percent (173 of 298) of trials met their primary end point. Among positive trials, median improvement in overall survival and PFS was 3.4 and 2.9 months, respectively. More than one-third (117 of 298 [39%]) of reports used a professional medical writer; this increased substantially during the study period (from 3 of 27 [11%] in 2010 to 12 of 18 [67%] in 2020; P < .001). CONCLUSIONS AND RELEVANCE: This cohort study suggests that contemporary oncology RCTs now largely measure putative surrogate end points and are almost exclusively funded by the pharmaceutical industry. The increasing role of medical writers warrants attention. To demonstrate that new cancer treatments are high value, the oncology community needs to consider the extent to which study end points and target effect size provide meaningful benefit to patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.053
metaresearch head score (Gemma)0.639
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0530.639
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.506
GPT teacher head0.621
Teacher spread0.115 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it