Construction of refined staging classification systems integrating FIGO/T-categories and corpus uterine invasion for non-metastatic cervical cancer.

BACKGROUND: To investigate the prognostic value of corpus uterine invasion (CUI) in cervical cancer (CC), and determine the necessity to incorporate it for staging. METHODS: A total of 809 cases of biopsy-proven, non-metastatic CC were identified from an academic cancer center. Recursive partitioning analysis (RPA) method was used to develop the refined staging systems with respect to overall survival (OS). Internal validation was performed by using calibration curve with 1000 bootstrap resampling. Performances of the RPA-refined stages were compared against the conventional FIGO 2018 and 9th edition TNM-stage classifications by the receiver operating characteristic curve (ROC) and decision curve analysis (DCA). RESULTS: We identified that CUI was independently prognostic for death and relapse in our cohort. RPA modeling using a two-tiered stratification by CUI (positive and negative) and FIGO/T-categories divided CC into three risk groupings (FIGO I'-III'/T1'-3'), with 5-year OS of 90.8%, 82.1%, and 68.5% for proposed FIGO stage I'-III', respectively (p ≤ 0.003 for all pairwise comparisons), and 89.7%, 78.8%, and 68.0% for proposed T1'-3', respectively (p < 0.001 for all pairwise comparisons). The RPA-refined staging systems were well validated with RPA-predicted OS rates showed optimal agreement with actual observed survivals. Additionally, the RPA-refined stages outperformed the conventional FIGO/TNM-stage with significantly higher accuracy of survival prediction (AUC: RPA-FIGO vs. FIGO, 0.663 [95% CI 0.629-0.695] vs. 0.638 [0.604-0.671], p = 0.047; RPA-T vs. T, 0.661 [0.627-0.694] vs. 0.627 [0.592-0.660], p = 0.036). CONCLUSION: CUI affects the survival outcomes in patients with CC. Disease extended to corpus uterine should be classified as stage III/T3.

Clinical utility of pretreatment serum squamous cell carcinoma antigen for prognostication and decision-making in patients with early-stage cervical cancer.

Background: To investigate the prognostic role of pretreatment squamous cell carcinoma antigen (SCCA) in early-stage cervical cancer (CC). Methods: We enrolled 487 cases of pathology-proven early-stage [International Federation of Gynecology and Obstetrics (FIGO) I/II] squamous or adenosquamous CC that were treated from 2012 to 2015. Restricted cubic splines (RCS) with a full Cox regression model were used to evaluate the association between SCCA levels and survival outcomes. Recursive partitioning analysis (RPA) was used to construct a risk stratification model for overall survival (OS). The performance of the RPA-based model was assessed using a receiver operating characteristic (ROC) curve. Results: RCS analysis revealed an association between SCCA and OS and disease-free survival (DFS); SCCA ⩾2.5 ng/mL was robust for risk discrimination in our cohort. SCCA had an interaction effect with FIGO classification: Patients with FIGO I and SCCA ⩾2.5 ng/mL overlapped with those with FIGO II and SCCA < 2.5 ng/mL for OS [hazard ratio, 1.04 (95% confidence interval (CI): 0.49-2.24), p = 0.903] and DFS [1.05 (0.56-1.98), p = 0.876]. RPA modeling incorporating SCCA (<2.5 ng/mL and ⩾2.5 ng/mL) and FIGO classification divided CC into three prognostic groups: RPA I, FIGO stage I, and SCCA < 2.5 ng/mL; RPA II, FIGO stage I, and SCCA ⩾ 2.5 ng/mL, or FIGO stage II and SCCA < 2.5 ng/mL; and RPA III, FIGO stage II, and SCCA ⩾ 2.5 ng/mL; with 5-year OS of 94.0%, 85.1%, and 73.5%, respectively (p < 0.001). ROC analysis confirmed that the RPA model outperformed the FIGO 2018 stage with significantly improved accuracy for survival prediction [area under the curve: RPA versus FIGO, 0.663 (95% CI: 0.619-0.705] versus 0.621 (0.576-0.664), p = 0.045]. Importantly, the RPA groupings were associated with the efficacy of treatment regimens. Surgery followed by adjuvant treatment had a higher OS (p < 0.01) and DFS (p = 0.024) than other treatments for RPA III, whereas outcomes were comparable among treatment regimens for RPA I-II. Conclusion: Herein, the role of SCCA for prognostication was confirmed, and a robust clinicomolecular risk stratification system that outperforms conventional FIGO classification in early-stage squamous and adenosquamous CC was presented. The model correlated with the efficacy of different treatment regimes.

Development of a risk classification system combining TN-categories and circulating EBV DNA for non-metastatic NPC in 10,149 endemic cases.

BACKGROUND: The objective of this study was to construct a risk classification system integrating cell-free Epstein-Barr virus (cfEBV) DNA with T- and N- categories for better prognostication in nasopharyngeal carcinoma (NPC). METHODS: Clinical records of 10,149 biopsy-proven, non-metastatic NPC were identified from two cancer centers; this comprised a training (N = 9,259) and two validation cohorts (N = 890; including one randomized controlled phase 3 trial cohort). Adjusted hazard ratio (AHR) method using a two-tiered stratification by cfEBV DNA and TN-categories was applied to generate the risk model. Primary clinical endpoint was overall survival (OS). Performances of the models were compared against American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) 8th edition TNM-stage classification and two published recursive partitioning analysis (RPA) models, and were validated in the validation cohorts. RESULTS: We chose a cfEBV DNA cutoff of ⩾2,000 copies for optimal risk discretization of OS, disease-free survival (DFS) and distant metastasis-free survival (DMFS) in the training cohort. AHR modeling method divided NPC into six risk groups with significantly disparate survival (p < 0.001 for all): AHR1, T1N0; AHR2A, T1N1/T2-3N0 cfEBV DNA < 2,000 (EBVlow); AHR2B, T1N1/T2-3N0 cfEBV DNA ⩾ 2,000 (EBVhigh) and T1-2N2/T2-3N1 EBVlow; AHR3, T1-2N2/T2-3N1 EBVhigh and T3N2/T4N0 EBVlow; AHR4, T3N2/T4 N0-1 EBVhigh and T1-3N3/T4N1-3 EBVlow; AHR5, T1-3N3/T4 N2-3 EBVhigh. Our AHR model outperformed the published RPA models and TNM stage with better hazard consistency (1.35 versus 3.98-12.67), hazard discrimination (5.29 versus 6.69-13.35), explained variation (0.248 versus 0.164-0.225), balance (0.385 versus 0.438-0.749) and C-index (0.707 versus 0.662-0.700). In addition, our AHR model was superior to the TNM stage for risk stratification of OS in two validation cohorts (p < 0.001 for both). CONCLUSION: Herein, we developed and validated a risk classification system that combines the AJCC/UICC 8th edition TN-stage classification and cfEBV DNA for non-metastatic NPC. Our new clinicomolecular model provides improved OS prediction over the current staging system.

Circulating Epstein-Barr virus DNA level post induction chemotherapy contributes to prognostication in advanced-stage nasopharyngeal carcinoma.

BACKGROUND: To investigate the value of post-induction chemotherapy (IC) cell-free Epstein-Barr virus DNA (cfEBV DNApostIC) for prognostication in locally advanced nasopharyngeal carcinoma (LA-NPC). METHODS: A total of 910 histologically proven LA-NPC undergoing radical IC + concurrent chemo-radiotherapy (CCRT) or targeted radiotherapy (CTRT) or both (CTCRT) were involved. The concentration of cfEBV DNA was measured by quantitative polymerase chain reaction pre-IC (cfEBV DNApreIC) and at IC completion. CfEBV DNApostIC was classified as undetectable (0 copy/ml) and detectable (>0 copy/ml). Recursive partitioning analysis (RPA) with respect to the overall survival (OS) was applied to construct a risk stratification system incorporating cfEBV DNApostIC and critical risk factors. RESULTS: We observed that 660 (72.5%) and 250 (27.5%) patients had cfEBV DNApostIC undetectable and detectable respectively. CfEBV DNApostIC positive was associated with a significant inferior 5-year OS (76.2% versus 85.9%), metastasis-free survival (DMFS, 71.7% versus 86.4%) and disease-free survival (DFS, 57.7% versus 80.1%) than cfEBV DNApostIC negative (P < 0.001 for all). Additionally, cfEBV DNApostIC was independently significant for OS (hazard ratio [HR] 1.90, 95% CI 1.40-2.59), DMFS (1.99, 1.45-2.71) and DFS (2.38, 1.86-3.06) in multivariate analyses (P < 0.001 for all). RPA modelling yielded three distinct risk groups: low-risk (N0-1 and undetectable cfEBV DNApostIC or N2-3 and pre-treatment cfEBV DNA [cfEBV DNApreIC] <7000), median-risk (N0-1 and detectable cfEBV DNApostIC or N2-3 and cfEBV DNApreIC ≥7000 with undetectable cfEBV DNApostIC) and high-risk (N2-3 and cfEBV DNApreIC ≥7000 with detectable cfEBV DNApostIC), with 5-year OS of 88.1%, 79.2% and 66.9%, respectively. Our risk stratification outperformed TNM classification for predicting death (AUC, 0.631 versus 0.562; P = 0.012) and distant metastasis (0.659 versus 0.562; P = 0.004). CONCLUSIONS: CfEBV DNApostIC represents an effective indicator of prognostication in LA-NPC. We developed a risk classification system that provides improved OS prediction over the current staging system by combining cfEBV DNApostIC, cfEBV DNApreIC and N-stage classification in LA-NPC.

The Efficacy and Safety of PD-1/PD-L1 Inhibitors in Combination with Conventional Therapies for Advanced Solid Tumors: A Meta-Analysis.

OBJECTIVES: To evaluate the efficacy of immuno-oncology combinational therapy (IOCT) versus monotherapy with programmed cell death 1 (PD-1) or PD-ligand 1 (PD-L1) inhibitors or conventional therapies, i.e., non-IOCT, in patients with advanced solid tumors. METHODS: We systematically searched the PubMed, Embase, and Cochrane Library databases from January 2015 to October 2018 for eligible studies. We included randomized trials of IOCT with available hazard ratios (HR) for death. The random effects model was used to calculate pooled HR for death; heterogeneity was assessed using I 2 statistics. The main outcome measure was overall survival (OS). RESULTS: After screening 483 relevant articles, we identified twelve trials comprising 5388 patients for quantitative analysis. IOCT-treated patients had significantly higher tumor response rate (relative risk (RR): 2.51, 95% confidence interval (CI): 1.82-3.47), prolonged progression-free survival (HR 0.62, 95% CI: 0.53-0.74), and OS (HR 0.69, 95% CI: 0.61-0.78), compared with non-IOCT-treated patients. Sensitivity analyses also demonstrated the OS advantage of IOCT across different combination modalities, intervention agents, malignancy types, and PD-L1 expression (all P < 0.05). Notably, there were higher odds of high-grade (grade ≥ 3) adverse events with IOCT (RR: 1.81, 95% CI: 1.13-2.90), but the risk of treatment-related death (RR: 1.16, 95% CI: 0.84-1.60) was not increased compared with non-IOCT. CONCLUSIONS: IOCT is a preferable treatment option over PD-1/PD-L1 inhibitor monotherapy and conventional therapy for patients with advanced solid tumors. However, we should note the increased incidence rate of high-grade AEs in IOCT.

Evaluation of objective response, disease control and progression-free survival as surrogate end-points for overall survival in anti-programmed death-1 and anti-programmed death ligand 1 trials.

BACKGROUND: We aimed to assess whether the Response Evaluation Criteria in Solid Tumors (RECIST) criteria-based objective response rate (ORR), disease control rate (DCR) and progression-free survival (PFS) could be valid surrogate end-points for overall survival (OS) in anti-programmed death-1 (PD-1)/programmed death ligand 1 (PD-L1) trials. METHODS: We systematically reviewed phase 2 and phase 3 trials of anti-PD-1/PD-L1 drug trials of advanced or recurrent solid tumours that reported OS and at least one of the RECIST criteria-based end-points. We used Spearman rank correlation to evaluate the strength of the association between these end-points and OS and a linear regression model, weighted by the sample size, to assess the association between the treatment effect on these end-points and OS. We also performed sensitivity analyses and a leave-one-out cross-validation approach to evaluate the robustness of our findings. RESULTS: Forty-three qualifying trails comprising 15,088 patients were eligible. PFS showed good correlation with OS (squared Spearman rank correlation coefficient [rs2] = 0.54; P < 0.001), while ORR and DCR illustrated moderate association with OS (rs2 = 0.29 and 0.28, respectively; both P < 0.001). The correlation was moderate between the treatment effects on PFS and OS (coefficient of determination [R2] = 0.37, P < 0.001) and poor among ORR, DCR and OS (R2 = 0.10 and 0.08, respectively); these were confirmed by sensitivity analyses (all R2 < 0.75) and the leave-one-out cross-validation approach. CONCLUSIONS: No RECIST criteria-based end-points could be a valid surrogate for OS. At present, we proposed to set OS as the primary end-point in anti-PD-1/PD-L1 drug trials of advanced or recurrent solid tumours.