Nomograms to predict overall and cancer-specific survival in patients with penile cancer

A Clinical Nomogram for Predicting Overall Survival in Patients With T1/T2 Penile Squamous Cell Carcinoma

BACKGROUND

To evaluate the overall survival (OS) and construct a nomogram to predict the OS of patients with penile squamous cell carcinoma (PSCC).

METHODS

This retrospective study analyzed data of patients with PSCC from the First Affiliated Hospital of Soochow University between 2012 and 2022. R software was used to explore factors influencing OS in PSCC. Kaplan-Meier method and log-rank test were employed for OS estimation. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify these factors. A nomogram was created to identify the independent prognostic factors. The model was evaluated by concordance index, receiver operating characteristic (ROC) curves, and calibration plots.

RESULTS

A total of 159 patients with T1/T2 PSCC were included in the analysis. Patients with T2/N2 stage, older age, larger tumor size, high preoperative systemic immune-inflammation index (SII), and poor preoperative nutrition had a higher incidence of poor OS. Age, T/N stage, tumor size, and SII were identified as independent prognostic indicators. A prognostic nomogram was formulated, and its predictive accuracy for estimating OS in PSCC patients was validated through ROC curves and calibration plots.

CONCLUSION

The nomograms, based on age, T/N stage, tumor size, and high preoperative SII, provide a valuable tool for predicting 1-, 2-, and 3-year OS in patients with T1/T2 PSCC without distant metastases.

Developing and validating a nomogram for penile cancer survival: A comprehensive study based on SEER and Chinese data

OBJECTIVE

The primary aim of this study was to create a nomogram for predicting survival outcomes in penile cancer patients, utilizing data from the Surveillance, Epidemiology, and End Results (SEER) and a Chinese organization.

METHODS

Our study involved a cohort of 5744 patients diagnosed with penile cancer from the SEER database, spanning from 2004 to 2019. In addition, 103 patients with penile cancer from Sun Yat-sen Memorial Hospital of Sun Yat-sen University were included during the same period. Based on the results of regression analysis, a nomogram is constructed and validated internally and externally. The predictive performance of the model was evaluated by concordance index (c-index), area under the curve, decision curve analysis, and calibration curve, in internal and external datasets. Finally, the prediction efficiency is compared with the TNM staging model.

RESULTS

A total of 3154 penile patients were randomly divided into the training group and the internal validation group at a ratio of 2:1. Nine independent risk factors were identified, including age, race, marital status, tumor grade, histology, TNM stage, and the surgical approach. Based on these factors, a nomogram was constructed to predict OS. The nomogram demonstrated relatively better consistency, predictive accuracy, and clinical relevance, with a c-index over 0.73 (in the training cohort, the validation cohort, and externally validation cohort.) These evaluation indexes are far better than the TNM staging system.

CONCLUSION

Penile cancer, often overlooked in research, has lacked detailed investigative focus and guidelines. This study stands as the first to validate penile cancer prognosis using extensive data from the SEER database, supplemented by data from our own institution. Our findings equip surgeons with an essential tool to predict the prognosis of penile cancer better suited than TNM, thereby enhancing clinical decision-making processes.

Machine learning-based overall and cancer-specific survival prediction of M0 penile squamous cell carcinoma：A population-based retrospective study

Background

Penile cancer is a rare tumor and few studies have focused on the prognosis of M0 penile squamous cell carcinoma (PSCC). This retrospective study aimed to identify independent prognostic factors and construct predictive models for the overall survival (OS) and cancer-specific survival (CSS) of patients with M0 PSCC.

Methods

Data was extracted from the Surveillance, Epidemiology, and End Results database for patients diagnosed with malignant penile cancer. Eligible patients with M0 PSCC were selected according to predetermined inclusion and exclusion criteria. These patients were then divided into a training set, a validation set, and a test set. Univariate and multivariate COX regression analyses were initially performed to identify independent prognostic factors for OS and CSS in M0 PSCC patients. Subsequently, traditional and machine learning prognostic models, including random survival forest (RSF), COX, gradient boosting, and component-wise gradient boosting modelling, were constructed using the scikit-survival framework. The performance of each model was assessed by calculating time-dependent area under curve (AUC), C-index, and integrated Brier score (IBS), ultimately identifying the model with the highest performance. Finally, the Shapley additive explanation (SHAP) value, feature importance, and cumulative rates analyses were used to further estimate the selected model.

Results

A total of 2, 446 patients were included in our study. Cox regression analyses demonstrated that age, N stage, and tumor size were predictors of OS, while the N stage, tumor size, surgery, and residential area were predictors of CSS. The RSF and COX models had a higher time-independent AUC and C-index, and lower IBS value than other models in OS and CSS prediction. Feature importance analysis revealed the N stage as a common significant feature for predicting M0 PSCC patients' survival. The SHAP and cumulative rate analyses demonstrated that the selected models can effectively evaluate the prognosis of M0 PSCC patients.

Conclusion

In M0 PSCC patients, age, N stage, and tumor size were predictors of OS. In addition, the N stage, tumor size, surgery, and residential area were predictors of CSS. The machine learning-based RSF and COX models effectively predicted the prognosis of M0 PSCC patients.

Real-world treatment outcomes of patients with penile cancer in the Kyushu-Okinawa area of Japan in the pre-guideline era

OBJECTIVES

To understand the real-world outcomes for patients with penile cancer in the Kyushu-Okinawa area before the introduction of practice guidelines in Japan.

METHODS

We retrospectively collected medical information on patients with penile squamous cell carcinoma and penile intraepithelial neoplasia at 12 university hospitals and their affiliated hospitals in the Kyushu-Okinawa area from January 2009 to December 2020. Patients with unknown clinical stage were excluded. Patient background characteristics and survival, as well as pretreatment factors involved in survival, were investigated.

RESULTS

A total of 196 patients were included. Patients with clinical stage 0, I, IIA, IIB, IIIA, IIIB and IV comprised 9.7, 26.0, 22.4, 2.6, 10.7, 14.3 and 14.3%, respectively. The median follow-up was 26 months, and the mean 5-year overall survival and cancer-specific survival rates were 74.3 and 79.8%, respectively. On univariate analysis, tumor diameter ≥ 30 mm, penile shaft tumor, Eastern Cooperative Oncology Group performance status ≥ 1, cT ≥ 3, cN ≥ 2 and cM1 were associated with significantly poorer cancer-specific survival. On multivariate analysis, pretreatment factors of cN ≥ 2 (hazard ratio, 32.5; 95% confidence interval, 5.08-208; P = 0.0002), Eastern Cooperative Oncology Group performance status ≥ 1 (4.42; 1.79-10.9; P = 0.0012) and cT ≥ 3 (3.34; 1.11-10.1; P = 0.0319) were identified as independent prognostic factors.

CONCLUSIONS

The study revealed basic data for future penile cancer treatment and research, including survival rates according to clinical stages, and identified cN ≥ 2, Eastern Cooperative Oncology Group performance status ≥ 1 and cT ≥ 3 at initial diagnosis as independent prognostic factors. Evidence for penile cancer in Japan is particularly scarce, and future large-scale prospective studies are warranted.