Most eligible candidates for primary tumor resection among metastatic colorectal cancer patients: a SEER-based population analysis
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed a predictive model to identify metastatic colorectal cancer (mCRC) patients who benefit most from primary tumor resection (PTR). The model accurately predicts eligibility, aiding clinical decision-making for improved patient outcomes.
Area Of Science
- Oncology
- Surgical Oncology
- Biostatistics
Background
- Primary tumor resection (PTR) offers survival benefits for select metastatic colorectal cancer (mCRC) patients.
- Identifying optimal candidates for PTR remains a clinical challenge.
Purpose Of The Study
- To develop and validate a predictive model for identifying mCRC patients most likely to benefit from PTR.
- To improve patient selection for PTR and enhance treatment efficacy.
Main Methods
- Propensity score matching (PSM) balanced baseline characteristics between surgical and non-surgical groups.
- Multivariate Cox analysis identified prognostic factors; logistic regression built the predictive model.
- Model validation included calibration curves, ROC analysis (AUC), and decision curve analysis (DCA).
Main Results
- A total of 11,763 mCRC patients were analyzed; 8,808 underwent PTR.
- PSM showed significantly improved median cancer-specific survival (CSS) in the surgical group (29 months vs. 16 months).
- The validated predictive model, incorporating 10 covariates, demonstrated good accuracy (AUC 0.727 training, 0.742 validation).
Conclusions
- A robust predictive model was successfully constructed and validated for PTR in mCRC.
- The model accurately identifies patients likely to benefit from PTR, supporting clinical decision-making.
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