Development and External Validation of Integrated Machine Learning-Based Prognostic Model in Oropharyngeal Head and Neck Cancer Using the Systemic Inflammatory Response Index
<b>Importance:</b> Patient with head and neck cancer of the oropharynx (HNC-OROP) undergo curative-intent definitive or post-operative radiation therapy. The systemic inflammation response index (SIRI) has independent prognostic capacity in HNC-OROP. We hypothesized that the use of SIRI may produce a parsimonious model of HNC-OROP outcomes. <b>Objective:</b> We aimed to investigate the prognostic utility of systemic inflammatory response index (SIRI) in oropharyngeal head and neck cancer patients who underwent radiation therapy. Design, Setting, and Participants: Random survival forest (RSF) machine learning was used to model survival in 568 oropharyngeal cancer patients in this retrospective cohort study. SIRI was calculated via pre-treatment bloodwork. Model validation was performed in an external cohort of 421 oropharyngeal cancer patients. <b>Exposures:</b> Exposure was curative-intent definitive or post-operative radiation therapy for head and neck cancer of the oropharynx (HNC-OROP). <b>Results:</b> This is a retrospective study with 568 and 421 patients in the Roswell Park and external Ohio State University cohorts. We evaluated full and reduced RSF models and a robust decision tree model. The C-index of the models was 0.758 (RSF full), 0.725 (RSF reduced), and 0.702 (decision tree). The incorporation of SIRI (with performance status and smoking history) into a machine learning model identified three risk-groups that significantly stratified overall survival (<i>p</i> < 0.0001). These findings were validated in the external validation cohort (<i>p</i> = 0.0019). Progression-free survival was also significantly different for the three groups in the validation cohort (<i>p</i> = 0.0025). <b>Conclusions and Relevance:</b> An integrated machine learning model using SIRI, performance status, and smoking history was successfully developed and externally validated in oropharyngeal head and neck cancer patients.
Authors
- Song Yao
- Vishal Gupta (ORCID: https://orcid.org/0000-0001-5630-6672)
- Sung Jun (ORCID: https://orcid.org/0000-0002-0838-3996)
- Han Yu (ORCID: https://orcid.org/0000-0001-6160-173X)
- Elizabeth A. Repasky (ORCID: https://orcid.org/0000-0002-9554-4152)
- Kimberly Wooten
- Ryan McSpadden (ORCID: https://orcid.org/0000-0002-6249-6772)
- Michael R. Markiewicz (ORCID: https://orcid.org/0000-0003-2039-4396)
- Mark Farrugia (ORCID: https://orcid.org/0000-0002-0261-0334)
- Dukagjin M. Blakaj (ORCID: https://orcid.org/0000-0002-1718-9642)
- Elizabeth Bouchard (ORCID: https://orcid.org/0000-0003-3570-4609)
- Guangwei Yuan
- Wesley L. Hicks (ORCID: https://orcid.org/0000-0003-2916-5231)
- Neil D. Almeida (ORCID: https://orcid.org/0000-0002-7884-6394)
- Simeng Zhu (ORCID: https://orcid.org/0000-0003-0850-6690)
- Moni Abraham Kuriakose (ORCID: https://orcid.org/0000-0003-4229-752X)
- Mukund Seshadri (ORCID: https://orcid.org/0000-0001-8729-9532)
- Anurag K. Singh (ORCID: https://orcid.org/0000-0002-6703-5115)
- Grace Wang (ORCID: https://orcid.org/0000-0002-1392-1218)
- Andrew Koempel (ORCID: https://orcid.org/0009-0002-7191-6457)
Institutions
- Roswell Park Comprehensive Cancer Center (US)
- The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute (US)
- University at Buffalo, State University of New York (US)
Publication Details
- Journal
- Cancers
- Published
- 2025-11-28
- DOI
- https://doi.org/10.3390/cancers17233820
- Primary Topic
- Inflammatory Biomarkers in Disease Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00