Nai-Ming Cheng1, Yu-Hua Dean Fang2, Din-Li Tsan3, Li-Yu Lee4, Joseph Tung-Chieh Chang5, Hung-Ming Wang6, Shu-Hang Ng7, Chun-Ta Liao8, Lan-Yan Yang9, Tzu-Chen Yen10. 1. Nuclear Medicine and Molecular Imaging Centre, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan; Nuclear Medicine, Chang Gung Memorial Hospital, Keelung, Taiwan. 2. Biomedical Engineering, National Cheng Kung University, Tainan City, Taiwan. 3. Radiation Oncology, Chang Gung Memorial Hospital, Keelung, Taiwan. 4. Pathology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan. 5. Radiation Oncology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan. 6. Hematology/Oncology, Internal Medicine, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan. 7. Diagnostic Radiology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan. 8. Otolaryngology, Head & Neck Surgery, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan. 9. Biostatistics Unit, Clinical Trial Centre, Chang Gung Memorial Hospital, Taoyuan City, Taiwan. 10. Nuclear Medicine and Molecular Imaging Centre, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan City, Taiwan. Electronic address: yen1110@cgmh.org.tw.
Abstract
OBJECTIVES: Human papillomavirus-negative oropharyngeal squamous cell carcinoma (OPSCC) has unfavorable survival outcomes. Two outcomes have been identified based on smoking history and tumor stage. We investigate the prognostic role of pre-treatment positron emission tomography (PET) in high-risk OPSCC. MATERIALS AND METHODS: We enrolled 147 M0 OPSCC patients with p16-negative staining and a history of heavy smoking (>10 pack-years) or T4 disease. All patients completed primary chemoradiotherapy, and 42% maximum standard uptake values (SUVmax) were used as the threshold for primary tumor. Patients were classified into training and validation cohorts with a ratio of 1:1.5 according to the PET date. Heterogeneity and irregularity indices were obtained. PET parameters with significant impact on progression-free survival (PFS) in receiver operating characteristic curves and univariate Cox models were identified and included in recursive partitioning analysis (RPA) for constructing a prognostic model. The RPA-based prognostic model was further tested in the validation cohort using multivariate Cox models. RESULTS: Fifty-eight and 89 patients were in the training and validation groups, respectively. Heterogeneity parameter, SUV-entropy (derived from histogram analysis), and irregularity index, and asphericity were significantly associated with PFS. The RPA model revealed that patients with both high SUV-entropy and high asphericity experienced the worst PFS. Results were confirmed in the validation group. The overall concordance index for PFS of the model was 0.75, which was higher than the clinical stages, performance status, SUVmax, and metabolic tumor volume of PET. CONCLUSIONS: PET prognostic model provided useful prediction of PFS for patients with high-risk OPSCC.
OBJECTIVES: Human papillomavirus-negative oropharyngeal squamous cell carcinoma (OPSCC) has unfavorable survival outcomes. Two outcomes have been identified based on smoking history and tumor stage. We investigate the prognostic role of pre-treatment positron emission tomography (PET) in high-risk OPSCC. MATERIALS AND METHODS: We enrolled 147 M0 OPSCC patients with p16-negative staining and a history of heavy smoking (>10 pack-years) or T4 disease. All patients completed primary chemoradiotherapy, and 42% maximum standard uptake values (SUVmax) were used as the threshold for primary tumor. Patients were classified into training and validation cohorts with a ratio of 1:1.5 according to the PET date. Heterogeneity and irregularity indices were obtained. PET parameters with significant impact on progression-free survival (PFS) in receiver operating characteristic curves and univariate Cox models were identified and included in recursive partitioning analysis (RPA) for constructing a prognostic model. The RPA-based prognostic model was further tested in the validation cohort using multivariate Cox models. RESULTS: Fifty-eight and 89 patients were in the training and validation groups, respectively. Heterogeneity parameter, SUV-entropy (derived from histogram analysis), and irregularity index, and asphericity were significantly associated with PFS. The RPA model revealed that patients with both high SUV-entropy and high asphericity experienced the worst PFS. Results were confirmed in the validation group. The overall concordance index for PFS of the model was 0.75, which was higher than the clinical stages, performance status, SUVmax, and metabolic tumor volume of PET. CONCLUSIONS: PET prognostic model provided useful prediction of PFS for patients with high-risk OPSCC.
Authors: Marius E Mayerhoefer; Christopher C Riedl; Anita Kumar; Peter Gibbs; Michael Weber; Ilan Tal; Juliana Schilksy; Heiko Schöder Journal: Eur J Nucl Med Mol Imaging Date: 2019-07-08 Impact factor: 9.236
Authors: Catharina Silvia Lisson; Christoph Gerhard Lisson; Sherin Achilles; Marc Fabian Mezger; Daniel Wolf; Stefan Andreas Schmidt; Wolfgang M Thaiss; Johannes Bloehdorn; Ambros J Beer; Stephan Stilgenbauer; Meinrad Beer; Michael Götz Journal: Cancers (Basel) Date: 2022-01-13 Impact factor: 6.639