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Background Oral squamous cell carcinoma (OSCC) is the dominant histologic type of oral cancer. Locally advanced OSCC remains a major therapeutic challenge. Our study aimed to develop and validate nomograms predicting survival prognosis in patients with locally advanced oral squamous cell carcinoma (OSCC) after curative resection. Methods A total of 269 consecutive patients with primary OSCC who received curative resection between September 2007 and March 2020 were retrospectively enrolled in our study. Patients were randomly assigned to the training cohort (n = 201) or the validation cohort (n = 68). Multivariate Cox regression analyses were conducted to determine independent prognostic factors for overall survival (OS) and cancer specific survival (CSS) in the training set, which were used to develop nomogram models estimating 3-, and 5-year OS and CSS. We also evaluated the nomograms using concordance indices (c-index), calibration curves, and decision curve analyses (DCA), and compared those with the AJCC 8th staging system. The results were externally validated in the validation cohort. Results Age, Kaplan-Feinstein (KFI) index, pT, the number of positive nodes and systemic inflammatory index (SII) were significant prognostic predictors for OS and CSS. The OS nomogram had c-index values of 0.712 in the training set and 0.697 in the validation set, while the CSS nomogram exhibited c-index values of 0.709 in the training set and 0.675 in the validation set. These data were superior to those of AJCC 8th staging system, suggesting high discriminative ability of the nomograms. Calibration curves exhibited good agreement between observed and predicted survival. DCA curves indicated the nomograms were with potential clinical usefulness. These results were validated in the validation set. Conclusions The novel nomograms incorporating clinically available characteristics for OS and CSS prediction were developed in the locally advanced OSCC patients after curative surgery. Validation revealed good discrimination and calibration, indicating the clinical utility of the nomograms in the individualized prognosis prediction of locally advanced OSCC after curative surgery.

Background: Oral squamous cell carcinoma (OSCC), the dominant histologic type of oral cancer. Locally advanced OSCC remains a major therapeutic challenge. Our study aimed to develop and validate nomograms predicting survival prognosis in patients with locally advanced oral squamous cell carcinoma (OSCC) after curative resection. Methods: A total of 269 consecutive patients with primary OSCC who received curative resection between September 2007 and March 2020 were retrospectively enrolled in our study. Patients were randomly assigned to the training cohort (n=201) or the validation cohort (n=68). Multivariate Cox regression analyses were conducted to determine independent prognostic factors for overall survival (OS) and cancer specific survival (CSS) in the training set, which were used for the construction of nomogram models estimating 3-, and 5-year OS and CSS. We also evaluated the nomograms using concordance indices (c-index), calibration curves, and decision curve analyses (DCA), and compared those with the AJCC 8th staging system. The results were externally validated in the validation cohort.Results: Age, Kaplan-Feinstein (KFI) index, pT, the number of positive nodes and systemic inflammatory index (SII) were significant prognostic predictors for OS and CSS. The OS nomogram had c-index values of 0.712 in the training set and 0.697 in the validation set, while the CSS nomograms had c-index values of 0.709 in the training set and 0.675 in the validation set. These data were superior to those of AJCC 8th staging system, suggesting high discriminative ability of the nomograms. Calibration curves exhibited good agreement between observed and predicted survival. DCA curves indicated the nomograms were with potential clinical usefulness. These results were validated in the validation set.Conclusions: The novel nomograms incorporating clinically available characteristics for OS and CSS prediction were developed in the locally advanced OSCC patients after curative surgery. Validation revealed good discrimination and calibration, indicating the clinical utility of the nomograms in the individualized prognosis prediction of locally advanced OSCC after curative surgery.

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Background: The prognosis of patients with small cell lung cancer (SCLC) is poor. We aim to figure out the survival rate of SCLC and construct a nomogram survival prediction for SCLC patients in Shandong. Methods: We collected the clinical data of 2219 SCLC patients in various tumor hospitals and general hospitals in fifteen cities in Shandong province from 2010-2014, and the data were randomly divided into a training set and a validation set according to 7:3. We used univariate and multivariate to determine the independent prognostic factors of SCLC, and developed a prognostic nomogram model based on these factors. The predictive discriminatory and accuracy performance of this model was evaluated by the area under the receiver operator characteristic (ROC) curve (AUC), and calibration curves. Results: The overall 5-year survival rate of Shandong SCLC patients was 14.27% with the median survival time being 15.77 months. Multivariate analysis showed that region, sex, age, year of diagnosis, TNM stage (assigned according to the AJCC 8th edition), and treatment type (surgery, chemotherapy, and radiotherapy) were independent prognostic factors and were included in the prognostic nomogram model. The AUC of the training set was 0.724, 0.710, and 0.704 for 1-year, 3-year, and 5-year; the AUC of the validation set was 0.678, 0.670, and 0.683 for 1-year, 3-year, and 5-year. The calibration curves of the prediction are consistent with the ideal curve. Conclusion: We construct a nomogram prognostic model to predict SCLC prognosis with certain discrimination which can provide both clinicians and patients with an effective tool for predicting outcomes and guiding treatment decisions.