Abstract
OBJECTIVE: To investigate the prognostic value of pretreatment human papillomavirus (HPV) viral load for cervical cancer, and to develop nomograms based on HPV load and other clinicopathological factors for long-term survival. METHODS: We conducted a prospective study on cervical squamous cell carcinoma (SCC) patients diagnosed between January 2003 and December 2008. Cervical samples were tested for HPV viral load by the Hybrid Capture II (HCII) assay before treatment and 6 months after treatment. Clinical characteristics and follow-up information were also collected. A multivariable Cox proportional hazards model was used to adjust covariates in both the radical hysterectomy (RH) treatment group and concurrent chemoradiotherapy (CCRT) treatment group to identify relevant covariates, and then nomograms were constructed and used for internal validation. RESULTS: A total of 520 SCC patients enrolled in this study with a median follow-up of 127 months, 360 patients received RH, whereas 160 patients received CCRT. The median HPV viral load in RH and CCRT groups was 356.10 and 294.29, respectively. Tumor size was positively correlated with high pretreatment HPV load in both groups. In CCRT group, the advanced International Federation of Gynecology and Obstetrics (FIGO) stage and enlarged retroperitoneal lymph node status determined by computed tomography (LNSCT) were correlated with low HPV load group. Initial HPV viral load, FIGO stage and lymph node metastasis were prognostic factors for RH group, whereas HPV viral load, squamous cell carcinoma antigen (SCC-Ag) level and LNSCT were identified as prognostic factors for CCRT group. Nomograms incorporating these predictors for 10-year progression-free survival (PFS) were constructed [concordance index (C-index): 0.756, 0.749]. CONCLUSIONS: A low pretreatment HPV viral load is an independent prognostic factor for poor prognosis of cervical SCC and is related to other clinicopathological factors. The survival nomogram based on HPV viral load could predict the long-term prognosis.