A meta-analysis of trials of etoposide plus platinum agent versus irinotecan/topotecan plus platinum agent in first-line therapy of extensive stage small cell lung cancer (ES SCLC).
Bibliographic record
Abstract
e20019 Background: Etoposide plus a platinum agent (EP) represents the standard treatment of ES SCLC. A trial conducted in Japan demonstrated improved overall survival (OS) for irinotecan and cisplatin (IP), but subsequent trials could not consistently replicate these findings. Genotypic differences may explain these findings. These trials have not undergone systematic analysis. Methods: We conducted a systematic review and metaanalysis of randomized trials (RCT) comparing etoposide plus a platinum agent (EP) with irinotecan (IP) or topotecan (TP) plus a platinum agent. A literature search was undertaken of Cochrane Database, MEDLINE and Embase from 1996 to June 2016 to identify RCTs addressing this question. Data were extracted by one author and checked independently, then synthesized using RevMan software using a random effects model. Outcomes of interest were OS, quality of life (QoL) and toxicity. Results: Three RCTs compared TP and EP. There was no difference in OS (HR 0.97, 95%CI 0.87 – 1.07). Eight RCTs compared IP and EP, although only 7 had data that could be combined. IP significantly improved OS compared with EP (HR 0.84, 95%CI 0.74 – 0.95). The estimated improvement in 12 month OS is 6.4%. There was evidence of statistical heterogeneity. After removal of the trial by Noda et al, there was still a significant improvement in OS (HR 0.88, 95%CI 0.79 – 0.98). IP was associated with less grade 3/4 neutropenia, febrile neutropenia, anemia, thrombocytopenia, but more diarrhea. QoL was assessed in 2 trials and no differences observed. Conclusions: IP results in modest improvements in OS in comparison with EP. IP is associated with less hematological toxicity but more diarrhea and should be considered an acceptable alternative to EP in the first-line treatment of ES SCLC. [Table: see text]
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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 | 0.024 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.058 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".