ArticleBMC gastroenterology2023
Risk prediction of second primary malignancies in patients after rectal cancer: analysis based on SEER Program.
Article in BMC gastroenterology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 1 citations in OpenAlex.
- Deep learning-based predictive models for assessing the impact of clinical factors and second primary malignancy on survival in patients with colorectal cancer.European journal of medical research · 2025Article
- Prognostic significance of chemotherapy response score in predicting outcomes for high-grade serous ovarian carcinoma patients undergoing neoadjuvant chemotherapy.Translational cancer research · 2025Article
- Development and validation of survival prediction nomograms for patients with early-stage rectal cancer: a population-based study.Translational cancer research · 2025Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundThis study will focus on exploring the clinical characteristics of rectal cancer (RC) patients with Second Primary Malignancies (SPMs) and constructing a prognostic nomogram to provide clinical treatment decisions.
methodsWe determined the association between risk factors and overall survival (OS) while establishing a nomogram to forecast the further OS status of these patients via Cox regression analysis. Finally, we evaluated the performance of the prognostic nomogram to predict further OS status.
resultsNine parameters were identified to establish the prognostic nomogram in this study, and, the C-index of the training set and validation set was 0.691 (95%CI, 0.662-0.720) and 0.731 (95%CI, 0.676-0.786), respectively. The calibration curve showed a high agreement between the predicted and actual results, and the receiver operating characteristic (ROC) curves verified the superiority of our model for clinical usefulness. In addition, the nomogram classification could more precisely differentiate risk subgroups and improved the discrimination of SPMs' prognosis.
conclusionsWe systematically explored the clinical characteristics of SPMs after RC and constructed a satisfactory nomogram.
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