Risk of second primary cancers in cancer patients treated with cisplatin: a systematic review and meta-analysis of randomized studies
Bibliographic record
Abstract
BACKGROUND: Case reports, retrospective analyses, and observational studies have linked the use of cisplatin to increased risk of second cancers, especially life-threatening secondary leukemia. We therefore performed a systematic review and meta-analysis to evaluate the risk of second cancers associated with receipt of cisplatin-based chemotherapy in randomized controlled trials (RCTs). METHODS: We searched MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, trial registers, conference proceedings, review articles, and reference lists of trial publications for all relevant RCTs comparing cisplatin- versus non-cisplatin-containing chemotherapy with data on second cancers. We extracted data about study characteristics and second cancers, especially leukemia/ myelodysplasia. The primary and secondary outcomes were the odds ratios (ORs) for all second cancers and for secondary leukemia/ myelodysplasia, respectively. RESULTS: We identified 28 eligible trials with 7403 patients. Second cancers were reported in 143 patients, including 75 patients in the cisplatin arm and 68 in the non-cisplatin arm (raw event rates of 1.91 and 1.96%, respectively). The pooled OR for risk of all second cancers associated with cisplatin-based chemotherapy was 0.95 (95% confidence interval (CI): 0.67-1.33, P = 0.76). Secondary leukemia/ myelodysplasia was reported in 14 patients on cisplatin arms and in 6 patients on non-cisplatin arms of 11 eligible RCTs with 2629 patients (raw event rates of 1.09 and 0.45%, respectively; pooled OR = 2.34, 95%CI 0.97-5.65, P = 0.06). CONCLUSION: Cisplatin was not associated with a significantly increased risk of second cancers compared with non-cisplatin-based chemotherapy. There is a non-significant trend to increased risk of leukemia/ myelodysplasia and the absolute risk was low. The concern about risk of second cancers should not influence decisions to use an efficacious regimen containing cisplatin.
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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 | 0.020 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.047 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".