Prognostic Nomogram for Overall Survival in Small Cell Lung Cancer Patients Treated with Chemotherapy: A SEER-Based Retrospective Cohort Study.
Small cell lung cancer (SCLC) is known for its rapid clinical progression and poor prognosis. In this study, we sought to establish a prognostic nomogram among SCLC patients who received chemotherapy.
We obtained 4971 SCLC patients' clinical information from the Surveillance, Epidemiology, and End Results (SEER) database for the period between 2004 and 2015. Patients were divided into training and validation sets. Two nomograms were established based on limited stage (LS) and extensive stage (ES) SCLC patients to predict 1-, 2-, and 3-year overall survival (OS) incorporating superior parameters from multivariate Cox regression. Receiver-operating characteristic curves (ROCs) were applied to assess the discrimination ability of the nomogram while the calibration plots were applied to verify the model. Kaplan-Meier method was applied to find survival curves. Decision curve analysis (DCA) was applied to compare OS between the nomograms and 7th American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging system.
Four and six clinical parameters were identified as significant prognostic factors for LS-SCLC and ES-SCLC patient's OS, respectively. The ROC curves indicated satisfactory discrimination capacity of the nomogram, with 1-, 2-, and 3-year area under curve (AUC) values of 0.89, 0.81, and 0.79 in LS-SCLC patients and 0.71, 0.66, and 0.66 in ES-SCLC patients, respectively. Calibration curves indicated that the nomogram showed good agreement with actual observations in survival rate probability. The survival curves among the LS-SCLC and ES-SCLC cohorts were consistent with the high-risk group having a worse prognosis than the low-risk group. Moreover, ROC and DCA curves showed our nomograms had more benefits than the 7th AJCC-TNM staging system.
We established two nomograms that can present individual predictions of OS among LS-SCLC and ES-SCLC patients who received chemotherapy. These proposed nomograms may aid clinicians in treatment strategy and design of clinical trials.
Liang M
，Chen M
，Singh S
，Singh S
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Prognostic nomogram for overall survival in upper urinary tract urothelial carcinoma (UTUC) patients treated with chemotherapy: a SEER-based retrospective cohort study.
To establish a prognostic nomogram among UTUC patients who received chemotherapy.
1195 UTUC patients who received chemotherapy were extracted from the Surveillance, Epidemiology, and End Results (SEER) database for the period between 2004 and 2015. Patients were randomly divided into a training and a validation set. Nomogram was constructed to predict 1-, 3-, and 5-year overall survival (OS) in those patients. Receiver-operating characteristic curves (ROCs), calibration plots, and Decision curve analysis (DCA) were applied to assess and compare the discrimination, accuracy, and practicability of the nomogram with 8th American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging system.
Six clinical parameters were identified as independent prognostic factors for UTUC patients' OS, including age, marital status, TNM stage, and surgical methods of the primary site. The ROC curves showed a satisfactory discrimination capacity of the nomogram, with 1-, 3-, and 5-year area under curve (AUC) values of 0.789, 0.772, and 0.763 in the training set and 0.772, 0.822, and 0.814 in the validation set, respectively. Calibration curves indicated a good agreement between actual observation and nomogram prediction. ROC and DCA curves showed our nomograms exhibited larger benefits than the 8th AJCC-TNM staging system.
A prognostic nomogram was established and validated to present individual predictions of OS among chemotherapeutic UTUC patients. This nomogram may assist clinicians in accurate survival prognostication, treatment decision-making, and design of future clinical trials.
Tian C
，Liu J
，An L
，Hong Y
，Xu Q
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Construction of a prognostic model for extensive-stage small cell lung cancer patients undergoing immune therapy in northernmost China and prediction of treatment efficacy based on response status at different time points.
Recently, the emergence of immune checkpoint inhibitors has significantly improved the survival of patients with extensive-stage small cell lung cancer. However, not all patients can benefit from immunotherapy; therefore, there is an urgent need for precise predictive markers to screen the population for the benefit of immunotherapy. However, single markers have limited predictive accuracy, so a comprehensive predictive model is needed to better enable precision immunotherapy. The aim of this study was to establish a prognostic model for immunotherapy in ES-SCLC patients using basic clinical characteristics and peripheral hematological indices of the patients, which would provide a strategy for the clinical realization of precision immunotherapy and improve the prognosis of small cell lung cancer patients.
This research retrospectively collected data from ES-SCLC patients treated with PD-1/PD-L1 inhibitors between March 1, 2019, and October 31, 2022, at Harbin Medical University Cancer Hospital. The study data was randomly split into training and validation sets in a 7:3 ratio. Variables associated with patients' overall survival were screened and modeled by univariate and multivariate Cox regression analyses. Models were presented visually via Nomogram plots. Model discrimination was evaluated by Harrell's C index, tROC, and tAUC. The calibration of the model was assessed by calibration curves. In addition, the clinical utility of the model was assessed using a DCA curve. After calculating the total risk score of patients in the training set, patients were stratified by risk using percentile partitioning. The Kaplan-Meier method was used to plot OS and PFS survival curves for different risk groups and response statuses at different milestone time points. Differences in survival time groups were compared using the chi-square test. Statistical analysis software included R 4.1.2 and SPSS 26.
This study included a total of 113 ES-SCLC patients who received immunotherapy, including 79 in the training set and 34 in the validation set. Six variables associated with poorer OS in patients were screened by Cox regression analysis: liver metastasis (P = 0.001), bone metastasis (P = 0.013), NLR < 2.14 (P = 0.005), LIPI assessed as poor (P < 0.001), PNI < 51.03 (P = 0.002), and LDH ≥ 146.5 (P = 0.037). A prognostic model for immunotherapy in ES-SCLC patients was constructed based on the above variables. The Harrell's C-index in the training and validation sets of the model was 0.85 (95% CI 0.76-0.93) and 0.88 (95% CI 0.76-0.99), respectively; the AUC values corresponding to 12, 18, and 24 months in the tROC curves of the training set were 0.745, 0.848, and 0.819 in the training set and 0.858, 0.904 and 0.828 in the validation set; the tAUC curves show that the overall tAUC is > 0.7 and does not fluctuate much over time in both the training and validation sets. The calibration plot demonstrated the good calibration of the model, and the DCA curve indicated that the model had practical clinical applications. Patients in the training set were categorized into low, intermediate, and high risk groups based on their predicted risk scores in the Nomogram graphs. In the training set, 52 patients (66%) died with a median OS of 15.0 months and a median PFS of 7.8 months. Compared with the high-risk group (median OS: 12.3 months), the median OS was significantly longer in the intermediate-risk group (median OS: 24.5 months, HR = 0.47, P = 0.038) and the low-risk group (median OS not reached, HR = 0.14, P = 0.007). And, the median PFS was also significantly prolonged in the intermediate-risk group (median PFS: 12.7 months, HR = 0.45, P = 0.026) and low-risk group (median PFS not reached, HR = 0.12, P = 0.004) compared with the high-risk group (median PFS: 6.2 months). Similar results were obtained in the validation set. In addition, we observed that in real-world ES-SCLC patients, at 6 weeks after immunotherapy, the median OS was significantly longer in responders than in non-responders (median OS: 19.5 months vs. 11.9 months, P = 0.033). Similar results were obtained at 12 weeks (median OS: 20.7 months vs 11.9 months, P = 0.044) and 20 weeks (median OS: 20.7 months vs 11.7 months, P = 0.015). Finally, we found that in the real world, ES-SCLC patients without liver metastasis (P = 0.002), bone metastasis (P = 0.001) and a total number of metastatic organs < 2 (P = 0.002) are more likely to become long-term survivors after receiving immunotherapy.
This study constructed a new prognostic model based on basic patient clinical characteristics and peripheral blood indices, which can be a good predictor of the prognosis of immunotherapy in ES-SCLC patients; in the real world, the response status at milestone time points (6, 12, and 20 weeks) can be a good indicator of long-term survival in ES-SCLC patients receiving immunotherapy.
Dang J
，Xu G
，Guo G
，Zhang H
，Shang L
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ResearchGate
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钛学术
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