Previously submitted to: JMIR Dermatology (no longer under consideration since Mar 20, 2025)
Date Submitted: Jun 27, 2024
Open Peer Review Period: Jul 19, 2024 - Sep 13, 2024
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A nomogram for predicting survival in patients with lower limb melanoma: A study based on the Surveillance, Epidemiology, and End Results database
ABSTRACT
Background:
The aim of this study was to develop and validate a nomogram for predicting cancer-specific survival (CSS) in individuals suffering from lower limb melanoma (LLM) at 3-, 5-, and 8-year intervals following diagnosis.
Objective:
The aim of this study was to develop and validate a nomogram for predicting cancer-specific survival (CSS) in individuals suffering from lower limb melanoma (LLM) at 3-, 5-, and 8-year intervals following diagnosis.
Methods:
Patient data pertaining to lower limb melanoma (LLM) cases were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. By employing a random selection process, a training cohort consisting of 70% of the patient population and a validation cohort comprising 30% of the patients were established. Utilizing a backward stepwise Cox regression model, independent prognostic factors were identified. These factors were subsequently integrated into the nomogram, enabling the prediction of cancer-specific survival (CSS) rates at 3-, 5-, and 8-year intervals after diagnosis. The nomogram's performance was evaluated through various metrics, including the concordance index (C-index), the area under the time-dependent receiver operating characteristic curve (AUC), the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration curves, and decision-curve analysis (DCA).
Results:
This study involved a comprehensive cohort comprising 12,580 patients diagnosed with lower limb melanoma (LLM). Through an analysis of the Cox regression model within the training cohort, a total of nine prognostic factors were identified, namely age, RNP (regional node positive), sex, race, AJCC (American Joint Committee on Cancer) stage, surgical status, chemotherapy status, radiation status, and income status. Subsequently, a nomogram was developed and subjected to rigorous internal and external validation procedures. The nomogram demonstrated excellent discriminatory abilities, as reflected by significantly high C-index and AUC values. Calibration curves provided further confirmation of the nomogram's reliability. Notably, the nomogram exhibited superior performance compared to the AJCC model, as evidenced by improved NRI and IDI values. The decision-curve analysis (DCA) curves further validated the clinical utility of the nomogram, underscoring its practical relevance in prognostication for patients with LLM.
Conclusions:
The current investigation has effectively developed and validated an initial nomogram for prognosticating outcomes in patients with lower limb melanoma (LLM). The nomogram's impressive performance and practical applicability highlight its potential usefulness within clinical settings. However, it is important to note that additional external validation is necessary to further substantiate its reliability and generalizability.
Citation
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