Pre-treatment tumor-specific growth rate as a temporal biomarker that predicts treatment failure and improves risk stratification for oropharyngeal cancer. Issue 11 (November 2015)

• Record Type: Journal Article
• Authors: Murphy, Colin T.; Devarajan, Karthik; Wang, Lora S.; Mehra, Ranee; Ridge, John A.; Fundakowski, Christopher; Galloway, Thomas J.
• Is Part Of: Oral oncology. Volume 51:Issue 11(2015:Nov.)
• Page Start: 1034
• Page End: 1040
• Publication Date: 2015-11
• Subjects: TSGR tumor-specific growth rate -- RT radiation therapy -- CRT chemoradiation -- HPV human papillomavirus -- CPE concordance probability estimate; Head and neck cancer -- Oropharynx cancer -- Growth rate -- p16 -- HPV -- Radiation -- Chemoradiation; Mouth -- Cancer -- Periodicals; Mouth -- Tumors -- Periodicals; Mouth Diseases -- Periodicals; Mouth Neoplasms -- Periodicals; Bouche -- Cancer -- Périodiques; Bouche -- Tumeurs -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9943105
• DOI: 10.1016/j.oraloncology.2015.09.001
• Languages: English
• ISSNs: 1368-8375

Abstract

Abstract : Highlights: Serial imaging permits estimates of tumor-specific growth rate (TSGR) for OPC. Faster TSGR correlates well with p16 status, T-stage and smoking. TSGR predicts outcomes for oropharyngeal cancer (OPC) in the HPV era. TSGR calculation may improve identification of de-escalation candidates. Summary: Purpose: To assess the relationship between tumor-specific growth rate (TSGR) and oropharyngeal cancer (OPC) outcomes in the HPV era. Methods/materials: Primary tumor volume differences between a diagnostic and secondary scan separated ⩾ 7 days without interval treatment were used to estimate TSGR, defined as percent volume growth/day derived from primary tumor volume doubling time for 85 OPC patients with known p16 status and smoking pack-years managed with (chemo)radiation. Variables were analyzed using Kruskal–Wallis or Fisher's exact test as appropriate. Log-rank tests and Cox proportional models analyzed endpoints. Using concordance probability estimates (CPE), TSGR was incorporated into RTOG 0129 risk grouping (0129RG) to assess whether TSGR could improve prognostic accuracy. Results: Median time between scans was 35 days (range 8–314). Median follow up was 26 months (range 1–76). The 0129RG classification was: 56% low, 25% intermediate, and 19% high risk. Median TSGR was 0.74%/day (range 0.01–4.25) and increased with 0129RG low (0.41%), intermediate (0.57%) and high (1.23%) risk, respectively ( p = 0.015). TSGR independently predicted for TF (TSGR: HR (95%CI) = 2.79, 1.67–4.65, p < 0.001) in the Cox model. On CPE, prognostic accuracy for TF, disease-free survival and overall survival was improved when 0129RG was combined with TSGR. Dichotomizing 0129RG by median TSGR yielded no observed recurrences in low risk patients with TSGR < 0.74% and demonstrated significant difference for intermediate risk (8% vs. 50% for TSGR < 0.74% vs. ⩾ 0.74%, respectively, p < 0.001). Conclusion: Tumor-specific growth rate correlates with increasing 0129RG and predicts treatment failure, potentially improving the prognostic strength and risk stratification of established 0129 risk groups.