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Prediction model to estimate overall survival benefit of postoperative radiotherapy for resected major salivary gland cancers.
Jacobs, Corbin D; Barak, Ian; Jung, Sin-Ho; Rocke, Daniel J; Kahmke, Russel R; Suneja, Gita; Mowery, Yvonne M.
Afiliação
  • Jacobs CD; Cancer Care Northwest, Spokane Valley, WA, USA. Electronic address: Corbin.Jacobs@ccnw.net.
  • Barak I; Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA. Electronic address: ian.barak@iqvia.com.
  • Jung SH; Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA. Electronic address: Sinho.Jung@duke.edu.
  • Rocke DJ; Department of Head and Neck Surgery & Communication Sciences, Duke University Medical Center, Durham, NC, USA. Electronic address: Daniel.Rocke@duke.edu.
  • Kahmke RR; Department of Head and Neck Surgery & Communication Sciences, Duke University Medical Center, Durham, NC, USA. Electronic address: Russel.Kahmke@duke.edu.
  • Suneja G; Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA. Electronic address: Gita.Suneja@hci.utah.edu.
  • Mowery YM; Department of Head and Neck Surgery & Communication Sciences, Duke University Medical Center, Durham, NC, USA; Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA. Electronic address: Yvonne.Mowery@duke.edu.
Oral Oncol ; 132: 105955, 2022 09.
Article em En | MEDLINE | ID: mdl-35752134
ABSTRACT

OBJECTIVES:

To develop and validate a prediction model to estimate overall survival (OS) with and without postoperative radiotherapy (PORT) for resected major salivary gland (SG) cancers. MATERIALS AND

METHODS:

Adults in the National Cancer Database diagnosed with invasive non-metastatic major SG cancer between 2004 and 2015 were identified. Exclusion criteria included prior malignancy, pT1N0 or unknown stage, no or unknown surgery, and neoadjuvant therapy. Cox proportional hazards models evaluated the effect of covariates on OS. A multivariate regression model was utilized to predict 2-, 5-, and 10-year OS. Internal cross-validation was performed using 50-50 hold-out and Harrell's concordance index.

RESULTS:

18,400 subjects met inclusion criteria, including 9,721 (53%) who received PORT. Distribution of SG involvement was 86% parotid, 13% submandibular, and 1% sublingual. Median follow-up for living subjects was 4.9 years. PORT was significantly associated with improved OS for the following subgroups by log-rank test pT3 (p < 0.001), pT4 (p < 0.001), high grade (p < 0.001), node-positive (p < 0.001), and positive margin (p < 0.001). The following variables were incorporated into a multivariate model age, sex, Charlson-Deyo comorbidity score, involved SG, pathologic T-stage, grade, margin status, ratio of nodal positivity, and PORT. The resulting model based on data from 6,138 subjects demonstrated good accuracy in predicting OS, with Harrell's concordance index of 0.73 (log-rank p < 0.001).

CONCLUSION:

This cross-validated prediction model estimates 2-, 5-, and 10-year differences in OS based on receipt of PORT for resected major SG cancers using readily available clinicopathologic features. Clinicians can utilize this tool to aid personalized adjuvant therapy decisions.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias das Glândulas Salivares Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias das Glândulas Salivares Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article