Nomograms for preoperative prediction of prognosis in patients with oral cavity squamous cell carcinoma

Abstract

BACKGROUND: This study sought to develop prognostic tools that will accurately predict overall and cancer-related mortality and risk of recurrence in individual patients with oral cancer based on host and tumor characteristics. These tools would take into account numerous prognosticators beyond those covered by the traditional TNM (tumor-node-metastasis) staging system. METHODS: Demographic, host, and tumor characteristics of 1617 patients with cancer of the oral cavity, who were treated primarily with surgery at a single-institution tertiary care cancer center between 1985 and 2009, were reviewed from a preexisting database. Recurrent disease was recorded in 509 patients (456 locoregional and 116 distant); 328 patients died of cancer-related causes, and 542 died of other causes. The median follow-up was 42 months (range, 1-300 months). The following variables were analyzed as predictors of prognosis: age, sex, race, alcohol and tobacco use, oral cavity subsite, invasion of other structures, comorbidity, tumor size, and clinical nodal status. The stepdown method was used to select the statistically most influential predictors for inclusion in the final nomogram for each outcome of interest. RESULTS: The most influential predictors of both recurrence and cancer-specific mortality probability (CSMP) were tumor size, nodal status, subsite, and bone invasion. Nomograms were generated for prediction of overall survival (OS), CSMP, and locoregional recurrence-free probability (LRRFP). The nomograms were internally validated with an overfit-corrected predictive discrimination metric (concordance index) for OS of 67%, CSMP of 66%, and LRRFP of 60%. CONCLUSIONS: Nomograms have been developed that can reasonably estimate OS, CSMP, and LRRFP based on specific tumor and host characteristics in patients with oral cancer. Cancer 2014;120:214-21.

Cancer-Specific Mortality and Competing Mortality in Patients with Head and Neck Squamous Cell Carcinoma: A Competing Risk Analysis

“…11,19,[22][23][24][25][26][27] For head and neck cancer, competing risk nomograms for oral cavity squamous cell carcinoma and salivary glands cancer have been recently developed. 28,29 However, both study cohorts were collected from a single institution, and models may not be relevant to risk prediction in general populations. Population-based competing risk nomograms for HNSCC are lacking.…”

Nomogram based on albumin and neutrophil-to-lymphocyte ratio for predicting the prognosis of patients with oral cavity squamous cell carcinoma

“…Nomograms have been used in several cancers as adjuncts in prognostic determination 8,47–49 . They can be tools to determine patient prognosis in addition to TNM classification, the current gold standard.…”

“…The prognosis for overall survival (OS) and risk of recurrence depends on both tumor-specific factors such as tumor size, nodal status, distant metastasis, extranodal extension (ENE) and bone invasion as well as patient-specific factors such as age, smoking, race, comorbidities and sex 2–6 . Although the TNM classification is important for predicting clinical outcomes and to serve as a guide for ablative and reconstructive treatment, OS vary greatly, even in patients at the same disease stage 7,8 . Recent reports have suggested that patient prognosis is associated with certain molecular biomarkers involved in angiogenesis, cell mutation, proliferation and differentiation.…”

Individualized risk prediction of outcomes for oral cavity cancer patients

“…Differences between calculators are determined by what factors are included in the equations, how they are included, as well as the quality and relevance of the datasets from which they were derived. Comorbidities, which are an important factor in determining overall survival (24), are included in three of the calculators, and MSK was the only calculator to use the Washington University Head and Neck Comorbidity Index (WUHNCI) (16, 24). …”