Abstract A003: Unfinished Stories: Consequences of Melanoma Clinical Trial Discontinuation and Non-Publication
Bibliographic record
Abstract
Abstract Background: Melanoma is a major cause of skin cancer-related death, and clinical trials are essential for advancing melanoma treatment options. However, many trials either are teminated prematurly or are never published, eaving critical data unreported. These “unfinished stories”, hinder scientific progress, waste resources, and limit informed clinical decision-making. Therefore, understanding how many and what factors predict unpublished or discontinued melanoma trials is key to improving the transparency of research and advancing best care for patients. Objective: To identify the extent, characteristics, and variables related to Discontinuation and Non-Publication melanoma clinical investigations. Methods: We systematically searched ClinicalTrials.gov for Melanoma studies up to March 1, 2025. Studies completed within the past 24 months were excluded to account for potential delays in the peer review process. Publication status was identified using NCT numbers. Data on participant gender, age, study design, funding source, type of intervention, sample size, and trial location were collected and analyzed. Multiple logistic regression was used to identify factors associated with trial discontinuation or non-publication. All statistical analyses were conducted using Jamovi version 2.6.24. Results: In total, there were 2,144 trials, with 712 (33.2%) published, 1,215 (56.7%) non-published, and 217 (10.1%) unknown. Of the discontinued trials (516, 24.1%), just 59 (11.4%) were published. Non-publication status was noted to be significant among trials of genetic interventions (OR = 0.104, 95% CI: 0.027-0.401, p=0.001), procedural interventions (OR = 0.262, 95% CI: 0.121-0.567, p<0.001), and in a multicenter trial (OR = 0.185, 95% CI: 0.123-0.278, p<0.001). Also, a study was considerably more probable to be discontinuation if smaller-sized (≤500 participants, p<0.001) or earlier (Phase 1/2, p<0.001). Conclusions: The high frequency of Discontinuation and Non-Publication trials record highlights the importance of efforts toward completing and/or fully publication melanoma clinical investigations, particularly those for genetic and/or procedural treatments and/or smaller trials. Citation Format: Hadeer Hafez, Abdelrahman Hagag, Mohamed Mohamed, Mohamed rakab, Ismail Zakaria. Ismail, Aya Jamal. Elkenani, Nada Elmetwally. Ahmed, Abdelrahman M. Hafez, Doaa Mashaly, Ali Tarek. Lasheen, Mohamed Abdelsalam. Unfinished Stories: Consequences of Melanoma Clinical Trial Discontinuation and Non-Publication [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr A003.
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.
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 | 0.252 | 0.642 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.010 | 0.018 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".