Regression Derived Staging Model to Predict Overall and Disease Specific Survival in Patients With Major Salivary Gland Carcinomas With Independent External Validation
PURPOSE: The current American Joint Cancer Committee (AJCC) staging system for salivary gland tumors does not include histology and grade in its classification despite their proven prognostic importance. We planned to analyze if a modified staging system integrating these two factors into the staging improves prognostic performance and then validate it externally.
MATERIALS AND METHODS: From SEER database (2000-2018), patients with major salivary gland carcinoma who underwent surgical resection between 2004 and 2015 were analyzed. Histologies were recoded into two groups based on grade and type of histology into "Low Aggression" and "High aggression" groups. Cox proportional hazards model was used to identify predictor variables for overall survival and disease-specific survival and models were generated based on least absolute shrinkage and selection operator regression. Model performance was evaluated by Akaike Information Criterion, concordance index and calibration plot. The best model chosen was externally validated from our hospital database of patients who underwent surgery for salivary gland tumor between January 1, 2012 to December 31, 2019.
RESULTS: Six thousand two hundred forty-six patients were analyzed with a median follow up of 58 months. Age > 65 years, male sex, metastatic disease, Histological Stratification, Grade of tumor, AJCC stage and Primary Site were the significant factors influencing overall survival and disease-specific survival. By least absolute shrinkage and selection operator regression method, Correlation analysis and Interaction testing by multiple regression, AJCC stage and Histological Risk stratification were used for generating four models, out of which the best model was selected by Akaike Information Criterion, C index and calibration plot. This model was then externally validated in our hospital database of 269 patients.
CONCLUSION: We propose an externally validated modified salivary gland staging system that incorporates histology and grade of tumor for improved hazard discrimination among patient subgroups.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:8 |
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| Enthalten in: |
JCO global oncology - 8(2022) vom: 10. Aug., Seite e2200150 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Ramalingam, Natarajan [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 22.08.2022 Date Revised 13.10.2022 published: Print Citation Status MEDLINE |
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| doi: |
10.1200/GO.22.00150 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM344998746 |
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| 100 | 1 | |a Ramalingam, Natarajan |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Regression Derived Staging Model to Predict Overall and Disease Specific Survival in Patients With Major Salivary Gland Carcinomas With Independent External Validation |
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| 500 | |a Date Completed 22.08.2022 | ||
| 500 | |a Date Revised 13.10.2022 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a PURPOSE: The current American Joint Cancer Committee (AJCC) staging system for salivary gland tumors does not include histology and grade in its classification despite their proven prognostic importance. We planned to analyze if a modified staging system integrating these two factors into the staging improves prognostic performance and then validate it externally | ||
| 520 | |a MATERIALS AND METHODS: From SEER database (2000-2018), patients with major salivary gland carcinoma who underwent surgical resection between 2004 and 2015 were analyzed. Histologies were recoded into two groups based on grade and type of histology into "Low Aggression" and "High aggression" groups. Cox proportional hazards model was used to identify predictor variables for overall survival and disease-specific survival and models were generated based on least absolute shrinkage and selection operator regression. Model performance was evaluated by Akaike Information Criterion, concordance index and calibration plot. The best model chosen was externally validated from our hospital database of patients who underwent surgery for salivary gland tumor between January 1, 2012 to December 31, 2019 | ||
| 520 | |a RESULTS: Six thousand two hundred forty-six patients were analyzed with a median follow up of 58 months. Age > 65 years, male sex, metastatic disease, Histological Stratification, Grade of tumor, AJCC stage and Primary Site were the significant factors influencing overall survival and disease-specific survival. By least absolute shrinkage and selection operator regression method, Correlation analysis and Interaction testing by multiple regression, AJCC stage and Histological Risk stratification were used for generating four models, out of which the best model was selected by Akaike Information Criterion, C index and calibration plot. This model was then externally validated in our hospital database of 269 patients | ||
| 520 | |a CONCLUSION: We propose an externally validated modified salivary gland staging system that incorporates histology and grade of tumor for improved hazard discrimination among patient subgroups | ||
| 650 | 4 | |a Journal Article | |
| 700 | 1 | |a Thiagarajan, Shivakumar |e verfasserin |4 aut | |
| 700 | 1 | |a Chidambaranathan, Nithyanand |e verfasserin |4 aut | |
| 700 | 1 | |a Singh, Arjun Gurmeet |e verfasserin |4 aut | |
| 700 | 1 | |a Chaukar, Devendra |e verfasserin |4 aut | |
| 700 | 1 | |a Chaturvedi, Pankaj |e verfasserin |4 aut | |
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| 773 | 1 | 8 | |g volume:8 |g year:2022 |g day:10 |g month:08 |g pages:e2200150 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1200/GO.22.00150 |3 Volltext |
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