Supplementary Material for: Cisplatin-Based versus Carboplatin-Based Chemotherapy for Extrapulmonary Neuroendocrine Carcinomas: A Real-World Study
Bibliographic record
Abstract
Objective: This study aimed to assess the survival differences between cisplatin/etoposide versus carboplatin/etoposide chemotherapy regimens in the management of patients with extrapulmonary neuroendocrine carcinomas (NECs). Methods: Administrative cancer care databases in the province of Alberta, Canada, were reviewed, and patients with extrapulmonary NECs (including those with small cell and large cell neuroendocrine carcinomas) who were treated with either cisplatin/etoposide or carboplatin/etoposide, 2004–2019, were reviewed. Kaplan-Meier survival estimates were used to compare the survival outcomes according to the type of platinum agent, and multivariable Cox regression analysis was used to assess the impact of the type of platinum agent on overall survival outcomes. Results: A total of 263 eligible patients were included in this analysis. These include 176 patients who received cisplatin/etoposide and 87 patients who received carboplatin/etoposide. Using Kaplan-Meier survival estimates, patients treated with cisplatin had better overall survival compared to patients treated with carboplatin (p = 0.005). Multivariable Cox regression analysis suggested that the following factors were associated with worse overall survival: higher Charlson comorbidity index (HR: 1.17; 95% CI: 1.05–1.30), gastrointestinal primary site (HR: 1.55; 95% CI: 1.12–2.14), stage IV disease (HR: 1.75; 95% CI: 1.28–2.38), and use of carboplatin (HR: 1.40; 95% CI: 1.02–1.92). Conclusions: The current study suggested that cisplatin/etoposide might be associated with better overall survival compared to carboplatin/etoposide among patients with extrapulmonary NECs. It is unclear if this is related to differences in inherent responsiveness to the 2 platinum agents or due to differences in comorbidity burden between the 2 treatment groups.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.395 | 0.036 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".