Novel algorithm for assigning risk/disease-directed treatment (DDT) choice in locally advanced primary squamous cell carcinoma head and neck (SCCHN): Using pretreatment data only
e18070Background: Locally advanced primary SCCHN, DDT options (radiotherapy (RTx) or concurrent Chemoradiotherapy (CRTx)) is performed only following surgery (National Comprehensive Cancer Network [NCCN] Guidelines). A novel 2-step exclusion algorithm was developed, based only on N classification an...
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          | Published in | Journal of clinical oncology Vol. 40; no. 16_suppl; p. e18070 | 
|---|---|
| Main Authors | , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
            American Society of Clinical Oncology
    
        01.06.2022
     | 
| Online Access | Get full text | 
| ISSN | 0732-183X 1527-7755  | 
| DOI | 10.1200/JCO.2022.40.16_suppl.e18070 | 
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| Abstract | e18070Background: Locally advanced primary SCCHN, DDT options (radiotherapy (RTx) or concurrent Chemoradiotherapy (CRTx)) is performed only following surgery (National Comprehensive Cancer Network [NCCN] Guidelines). A novel 2-step exclusion algorithm was developed, based only on N classification and imaging (CT; MRI +/- PET) to detect clinical features only from screening/entry findings. The algorithm was developed using the IT-MATTERS SCCHN pivotal study (Clinical trials.gov NCT01265849) data to identify treatment naïve lower risk (LR) for recurrence subjects receiving neoadjuvant immunotherapy prior to surgery to optimize long-term overall survival (OS). Methods: SCCHN patients are routinely examined and imaged at entry/screening to establish TNM classification and disease stage. Imaging is performed using CT, MRI, and/or PET-CT/PET-MRI per NCCN Guidelines. These imaging techniques can reliably detect extracapsular cervical lymph node spread before surgery, allowing the algorithm to be constructed and validated. Algorithm rules target CRTx bound ("High-Risk") patients leaving RTx bound ("Low-Risk") locally advanced primary disease patients at entry. The 2-step exclusions are: (1) exclude all N2 leaving only those with N0-N1, (2) further exclude those exhibiting extra capsular spread (PET-CT or PET-MRI). We retained those determined by study physicians to receive CRTx for the algorithm validation exercise only. The n = 923 pivotal study intent to treat (ITT) population was used to validate the algorithm. Results: Overall algorithm coverage was 99.9% (922/923 ITT except one missing N case) with 24.6% having N2 and 75.3% N0/N1. Among algorithm exclusions, 81.3% (282/347) were High-Risk; among algorithm inclusions, 60.6% (349/576) were Low-Risk. Algorithm validation: Among all Low-Risk cases in the study (n = 380), 91.8% (349/380) met the algorithm criteria; among all High-Risk cases, 60.4% (282/467) were correctly excluded by the algorithm. Remaining were physician choice. Overall, algorithm alone predicted 74.5% (631/847) risk group (combined low and high) accurately. Significant OS advantage (2-sided log rank p = 0.0376) to Immunotherapy regimen + standard of care (SOC) surgery + RTx vs SOC alone was seen for Low-Risk cases selected only by the 2-step algorithm. Conclusions: The algorithm provided near perfect (99.9%) ITT population coverage, achieved near 75% overall accuracy, with 91.8% accurate predictive value for the low-risk group demonstrating significant OS. Thus, risk group can be inferred at screening consistent with clinical practice and NCCN Guidelines. The algorithm can be used to help identify low risk SCCHN patients at entry to receive neoadjuvant immunotherapy before surgery. | 
    
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| AbstractList | e18070
Background: Locally advanced primary SCCHN, DDT options (radiotherapy (RTx) or concurrent Chemoradiotherapy (CRTx)) is performed only following surgery (National Comprehensive Cancer Network [NCCN] Guidelines). A novel 2-step exclusion algorithm was developed, based only on N classification and imaging (CT; MRI +/- PET) to detect clinical features only from screening/entry findings. The algorithm was developed using the IT-MATTERS SCCHN pivotal study (Clinical trials.gov NCT01265849) data to identify treatment naïve lower risk (LR) for recurrence subjects receiving neoadjuvant immunotherapy prior to surgery to optimize long-term overall survival (OS). Methods: SCCHN patients are routinely examined and imaged at entry/screening to establish TNM classification and disease stage. Imaging is performed using CT, MRI, and/or PET-CT/PET-MRI per NCCN Guidelines. These imaging techniques can reliably detect extracapsular cervical lymph node spread before surgery, allowing the algorithm to be constructed and validated. Algorithm rules target CRTx bound (“High-Risk”) patients leaving RTx bound (“Low-Risk”) locally advanced primary disease patients at entry. The 2-step exclusions are: (1) exclude all N2 leaving only those with N0-N1, (2) further exclude those exhibiting extra capsular spread (PET-CT or PET-MRI). We retained those determined by study physicians to receive CRTx for the algorithm validation exercise only. The n = 923 pivotal study intent to treat (ITT) population was used to validate the algorithm. Results: Overall algorithm coverage was 99.9% (922/923 ITT except one missing N case) with 24.6% having N2 and 75.3% N0/N1. Among algorithm exclusions, 81.3% (282/347) were High-Risk; among algorithm inclusions, 60.6% (349/576) were Low-Risk. Algorithm validation: Among all Low-Risk cases in the study (n = 380), 91.8% (349/380) met the algorithm criteria; among all High-Risk cases, 60.4% (282/467) were correctly excluded by the algorithm. Remaining were physician choice. Overall, algorithm alone predicted 74.5% (631/847) risk group (combined low and high) accurately. Significant OS advantage (2-sided log rank p = 0.0376) to Immunotherapy regimen + standard of care (SOC) surgery + RTx vs SOC alone was seen for Low-Risk cases selected only by the 2-step algorithm. Conclusions: The algorithm provided near perfect (99.9%) ITT population coverage, achieved near 75% overall accuracy, with 91.8% accurate predictive value for the low-risk group demonstrating significant OS. Thus, risk group can be inferred at screening consistent with clinical practice and NCCN Guidelines. The algorithm can be used to help identify low risk SCCHN patients at entry to receive neoadjuvant immunotherapy before surgery. e18070Background: Locally advanced primary SCCHN, DDT options (radiotherapy (RTx) or concurrent Chemoradiotherapy (CRTx)) is performed only following surgery (National Comprehensive Cancer Network [NCCN] Guidelines). A novel 2-step exclusion algorithm was developed, based only on N classification and imaging (CT; MRI +/- PET) to detect clinical features only from screening/entry findings. The algorithm was developed using the IT-MATTERS SCCHN pivotal study (Clinical trials.gov NCT01265849) data to identify treatment naïve lower risk (LR) for recurrence subjects receiving neoadjuvant immunotherapy prior to surgery to optimize long-term overall survival (OS). Methods: SCCHN patients are routinely examined and imaged at entry/screening to establish TNM classification and disease stage. Imaging is performed using CT, MRI, and/or PET-CT/PET-MRI per NCCN Guidelines. These imaging techniques can reliably detect extracapsular cervical lymph node spread before surgery, allowing the algorithm to be constructed and validated. Algorithm rules target CRTx bound ("High-Risk") patients leaving RTx bound ("Low-Risk") locally advanced primary disease patients at entry. The 2-step exclusions are: (1) exclude all N2 leaving only those with N0-N1, (2) further exclude those exhibiting extra capsular spread (PET-CT or PET-MRI). We retained those determined by study physicians to receive CRTx for the algorithm validation exercise only. The n = 923 pivotal study intent to treat (ITT) population was used to validate the algorithm. Results: Overall algorithm coverage was 99.9% (922/923 ITT except one missing N case) with 24.6% having N2 and 75.3% N0/N1. Among algorithm exclusions, 81.3% (282/347) were High-Risk; among algorithm inclusions, 60.6% (349/576) were Low-Risk. Algorithm validation: Among all Low-Risk cases in the study (n = 380), 91.8% (349/380) met the algorithm criteria; among all High-Risk cases, 60.4% (282/467) were correctly excluded by the algorithm. Remaining were physician choice. Overall, algorithm alone predicted 74.5% (631/847) risk group (combined low and high) accurately. Significant OS advantage (2-sided log rank p = 0.0376) to Immunotherapy regimen + standard of care (SOC) surgery + RTx vs SOC alone was seen for Low-Risk cases selected only by the 2-step algorithm. Conclusions: The algorithm provided near perfect (99.9%) ITT population coverage, achieved near 75% overall accuracy, with 91.8% accurate predictive value for the low-risk group demonstrating significant OS. Thus, risk group can be inferred at screening consistent with clinical practice and NCCN Guidelines. The algorithm can be used to help identify low risk SCCHN patients at entry to receive neoadjuvant immunotherapy before surgery.  | 
    
| Author | Markovic, Dusan Talor, Eyal Lavin, Philip T  | 
    
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| Title | Novel algorithm for assigning risk/disease-directed treatment (DDT) choice in locally advanced primary squamous cell carcinoma head and neck (SCCHN): Using pretreatment data only | 
    
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