Design, reporting, and disparities of advanced non–small cell lung cancer phase 3 clinical trials in the era of immunotherapy.
Bibliographic record
Abstract
e13616 Background: Lung cancer remains the main cause of cancer-related mortality globally, with non-small cell (NSCLC) accounting for the majority of cases. The advent of immunotherapy (IO) has expanded treatment options for advanced NSCLC. However, there are no bibliometric studies exploring NSCLC IO-based trials. We aimed to provide a systematic and comprehensive analysis of the design, reporting, population, and disparities of phase 3 trials investigating IO for advanced NSCLC. Methods: MEDLINE search was performed (last decade) for phase 3 trials reporting on patients with advanced (stage IIIA or higher) NSCLC. We assessed relationships between study outcomes, funding transparency, conflict of interest, journal impact factor (IF), region, gender of the first and last authors, population size, and ethnicity. Results: From 2012 to 2022, 2556 articles were screened and 81 were included. Overall survival (OS), followed by progression/disease-free survival (PFS) and overall/objective response (ORR) were the most commonly reported primary endpoints, representing 54%, 44%, and 15% respectively. The majority of the studies ( > 97%) had a funding sources statement and declared COI. Male first and last authorship represented 84% and 74% of studies, respectively. In 62% of trials reporting the patient’s ethnicity, white was the most common (65%). Regarding the source of funding, 74% of trials reported industry-only, 8% academia-only, 11% combined, 4% no funding received and 2.5% were not transparent. 98% of trials were from high-income countries (HIC), being the US (37%) and China (26%) the most reported. The mean number of authors with declared COI was 10.55 [0-25] and the mean total number of authors was 21.3 [5-76]. Publications journals' mean IF was 57.7 [2.1-202.7]. COI declaration was associated with publication in a journal with a higher IF compared to studies with no declared COI (p < 0.05). The journal IF was significantly higher in the US publications compared to China (p < 0.01). Trials assessing OS and PFS as their primary outcome were published with a higher IF in relation to assessing ORR only (p < 0.05). There was a significant association between the first and last authors' gender (p < 0.05), with a higher likelihood of matching genders (OR = 4,5 [1,3-14,4]). There was no association between the proportion of COI among authors, source of funding, and first author’s gender with journal IF. Conclusions: Phase 3 trials exploring IO for advanced NSCLC are majorly done in HIC, report industry funding and COI, and have males as the first and last authors. PFS is the primary outcome of almost 50% of the trials. We identified that among the primary outcomes studied, declaration of COI and author’s geographic affiliation may influence the publication’s IF. Sustained efforts are required to guarantee impartial reporting of clinical trial results and inclusive representation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.342 | 0.609 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.020 | 0.025 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".