An Exploratory Study of Refining TNM-8 M1 Categories and Prognostic Subgroups Using Plasma EBV DNA for Previously Untreated De Novo Metastatic Nasopharyngeal Carcinoma.

(1) Background: NPC patients with de novo distant metastasis appears to be a heterogeneous group who demonstrate a wide range of survival, as suggested by growing evidence. Nevertheless, the current 8th edition of TNM staging (TNM-8) grouping all these patients into the M1 category is not able to identify their survival differences. We sought to identify any anatomic and non-anatomic subgroups in this study. (2) Methods: Sixty-nine patients with treatment-naive de novo M1 NPC (training cohort) were prospectively recruited from 2007 to 2018. We performed univariable and multivariable analyses (UVA and MVA) to explore anatomic distant metastasis factors, which were significantly prognostic of overall survival (OS). Recursive partitioning analysis (RPA) with the incorporation of significant factors from MVA was then performed to derive a new set of RPA stage groups with OS segregation (Set 1 Anatomic-RPA stage groups); another run of MVA was performed with the addition of pre-treatment plasma EBV DNA. A second-round RPA with significant prognostic factors of OS identified in this round of MVA was performed again to derive another set of stage groups (Set 2 Prognostic-RPA stage groups). Both sets were then validated externally with an independent validation cohort of 67 patients with distant relapses of their initially non-metastatic NPC (rM1) after radical treatment. The performance of models in survival segregation was evaluated by the Akaike information criterion (AIC) and concordance index (C-index) under 1000 bootstrapping samples for the validation cohort; (3) Results: The 3-year OS and median follow-up in the training cohort were 36.0% and 17.8 months, respectively. Co-existence of liver-bone metastases was the only significant prognostic factor of OS in the first round UVA and MVA. Set 1 RPA based on anatomic factors that subdivide the M1 category into two groups: M1a (absence of co-existing liver-bone metastases; median OS 28.1 months) and M1b (co-existing liver-bone metastases; median OS 19.2 months, p = 0.023). When pre-treatment plasma EBV DNA was also added, it became the only significant prognostic factor in UVA (p = 0.001) and MVA (p = 0.015), while co-existing liver-bone metastases was only significant in UVA. Set 2 RPA with the incorporation of pre-treatment plasma EBV DNA yielded good segregation (M1a: EBV DNA ≤ 2500 copies/mL and M1b: EBV DNA > 2500 copies/mL; median OS 44.2 and 19.7 months, respectively, p < 0.001). Set 2 Prognostic-RPA groups (AIC: 228.1 [95% CI: 194.8−251.8] is superior to Set 1 Anatomic-RPA groups (AIC: 278.5 [254.6−301.2]) in the OS prediction (p < 0.001). Set 2 RPA groups (C-index 0.59 [95% CI: 0.54−0.67]) also performed better prediction agreement in the validation cohort (vs. Set 1: C-index 0.47 [95% CI: 0.41−0.53]) (p < 0.001); (4) Conclusions: Our Anatomic-RPA stage groups yielded good segregation for de novo M1 NPC, and prognostication was further improved by incorporating plasma EBV DNA. These new RPA stage groups for M1 NPC can be applied to countries/regions regardless of whether reliable and sensitive plasma EBV DNA assays are available or not.

Refining TNM-8 M1 categories with anatomic subgroups for previously untreated de novo metastatic nasopharyngeal carcinoma.

PURPOSE: To propose a refined M1 classification in de novo metastatic nasopharyngeal carcinoma (NPC) based on pooled data from two academic institutions. METHODS: Previously untreated de novo M1 NPC patients prospectively treated at The University of Hong Kong (N = 69) and Fujian Cancer Hospital (N = 114) between 2007 and 2016 were recruited and randomized in a 2:1 ratio to generate training (N = 120) and validation (N = 63) cohorts, respectively. Multivariable analysis (MVA) was performed for the training and validation cohorts to identify anatomic prognostic factors for overall survival (OS). Recursive partitioning analysis (RPA) was performed which incorporated the anatomic prognostic factors identified in the MVA to derive Anatomic-RPA groups which stratified OS in the training cohort, and were then validated in the validation cohort. RESULTS: Median follow-up for the training and validation cohorts was 27.2 and 30.2 months with 3-year OS of 51.6% and 51.1%, respectively. MVA revealed that co-existing liver-bone metastases was the only factor prognostic for OS in both the training and validation cohorts. Anatomic-RPA separated M1 disease into M1a (no co-existing liver-bone metastases) and M1b (co-existing liver-bone metastases) with median OS 39.5 and 23.7 months, respectively (p = 0.004) in the training cohort. RPA for the validation cohort also confirmed good segregation with co-existing liver-bone metastases with median OS 47.7 and 16.0 months, respectively (p = 0.008). CONCLUSION: Our proposal to subdivide de novo M1 NPC into M1a (no co-existing liver-bone metastases) vs. M1b (co-existing liver-bone metastases) provides better OS segregation.

Proton range monitoring using 13N peak for proton therapy applications.

The Monte Carlo method is employed in this study to simulate the proton irradiation of a water-gel phantom. Positron-emitting radionuclides such as 11C, 15O, and 13N are scored using the Particle and Heavy Ion Transport Code System Monte Carlo code package. Previously, it was reported that as a result of 16O(p,2p2n)13N nuclear reaction, whose threshold energy is relatively low (5.660 MeV), a 13N peak is formed near the actual Bragg peak. Considering the generated 13N peak, we obtain offset distance values between the 13N peak and the actual Bragg peak for various incident proton energies ranging from 45 to 250 MeV, with an energy interval of 5 MeV. The offset distances fluctuate between 1.0 and 2.0 mm. For example, the offset distances between the 13N peak and the Bragg peak are 2.0, 2.0, and 1.0 mm for incident proton energies of 80, 160, and 240 MeV, respectively. These slight fluctuations for different incident proton energies are due to the relatively stable energy-dependent cross-section data for the 16O(p,2p2n)13N nuclear reaction. Hence, we develop an open-source computer program that performs linear and non-linear interpolations of offset distance data against the incident proton energy, which further reduces the energy interval from 5 to 0.1 MeV. In addition, we perform spectral analysis to reconstruct the 13N Bragg peak, and the results are consistent with those predicted from Monte Carlo computations. Hence, the results are used to generate three-dimensional scatter plots of the 13N radionuclide distribution in the modeled phantom. The obtained results and the developed methodologies will facilitate future investigations into proton range monitoring for therapeutic applications.

The addition of pretreatment plasma Epstein-Barr virus DNA into the eighth edition of nasopharyngeal cancer TNM stage classification.

The eighth edition of the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) stage classification (TNM) for nasopharyngeal carcinoma (NPC) was launched. It remains unknown if incorporation of nonanatomic factors into the stage classification would better predict survival. We prospectively recruited 518 patients with nonmetastatic NPC treated with radical intensity-modulated radiation therapy ± chemotherapy based on the eighth edition TNM. Recursive partitioning analysis (RPA) incorporating pretreatment plasma Epstein-Barr virus (EBV) DNA derived new stage groups. Multivariable analyses to calculate adjusted hazard ratios (AHRs) derived another set of stage groups. Five-year progression-free survival (PFS), overall survival (OS) and cancer-specific survival (CSS) were: Stage I (PFS 100%, OS 90%, CSS 100%), II (PFS 88%, OS 84%, CSS 95%), III (PFS 84%, OS 84%, CSS 90%) and IVA (PFS 71%, OS 75%, CSS 80%) (p < 0.001, p = 0.066 and p = 0.002, respectively). RPA derived four new stages: RPA-I (T1-T4 N0-N2 & EBV DNA <500 copies per mL; PFS 94%, OS 89%, CSS 96%), RPA-II (T1-T4 N0-N2 & EBV DNA ≥500 copies per mL; PFS 80%, OS 83%, CSS 89%), RPA-III (T1-T2 N3; PFS 64%, OS 83%, CSS 83%) and RPA-IVA (T3-T4 N3; PFS 63%, OS 60% and CSS 68%) (all with p < 0.001). AHR using covariate adjustment also yielded a valid classification (I: T1-T2 N0-N2; II: T3-T4 N0-N2 or T1-T2 N3 and III: T3-T4 N3) (all with p < 0.001). However, RPA stages better predicted survival for PS and CSS after bootstrapping replications. Our RPA-based stage groups revealed better survival prediction compared to the eighth edition TNM and the AHR stage groups.