Prognostic Scoring for Salivary Gland Malignancy

Overview

Prognostic Research for Salivary Gland Cancer

Prognostic research for patients with salivary gland carcinoma relates specific prognostic factors to specific oncologic outcomes. Outcomes generally studied are “overall survival” (death from any cause as the central event); “disease specific survival” (death due to tumor – reflects the best obtainable treatment result of all possible treatment given); and “disease control” (freedom of tumor recurrence: local, regional, at distance, or a combination of these, reflecting treatment result following initial therapy). Even recently published research frequently remains limited to prognostic factor identification.

Specific Focus: Development, National and International External Validation, and Clinical Application of a Prognostic Scoring System for Disease Control

The 10-year disease specific survival (DSS) rates for patients with parotid carcinoma treated in major centers range from 47% to 69%. This range reflects the population specific distribution of stage, percentage of high-grade tumors, treatment period and regimens, patient inclusion criteria and follow-up quality. These “group” DSS figures are too general to counsel any specific patient. A unique patient features a unique set of prognostic factors (patient-, tumor- and treatment-related, clinical, pathologic, and increasingly molecular biologic factors) that jointly imply a better or worse outcome than the whole group's prognosis. The focus of this short chapter is on recent research efforts that summarize important prognostic factors and their respective weights into a unique individual patient's prognosis.

Research Echelons in Prognostic Research

Research echelons are (1) univariate and multivariate identification of prognostic factors; (2) summarizing the identified factors into a user-friendly score or nomogram, and (3) preferably repeated external validation (proving applicability outside the source population). Studies that are higher on the echelon ladder imply an increased research effort but also increased clinical usefulness. Several studies have now reached this third level.

Univariate and Multivariate Survival Analyses for Patients With Parotid Carcinoma

As opposed to univariate Kaplan–Meier analysis, Cox proportional hazards multivariate analysis corrects the impact of one prognostic factor for the effect of other factors, and increases clinical usability. Cox based models incorporate: (1) patient factors (age, gender, pain, and comorbidity); (2) tumor factors (histologic type, grade, stage, skin and soft tissue invasion, facial nerve involvement and perineural growth, molecular biologic factors); and (3) treatment factors (resection margins and adjuvant radiotherapy), and are presented as a table listing the factors, the accompanying hazard ratios (HR) that reflect their respective weight, and p -values/confidence intervals (CI). Sadly, most clinicians seeking to counsel their patient fail to intuitively amalgamate this tabulated information into a concrete patient-specific prognosis.

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