Subpopulation treatment effect pattern plot analysis: a prognostic model for distant recurrence-free survival to estimate delayed adjuvant chemotherapy initiation effect in triple-negative breast cancer

• Autores: Morante, Z, Ferreyra, Y, Pinto, JA, Valdivieso, N, Castañeda, C, Vidaurre, T, Valencia, G, Rioja, P, Fuentes, H, Cotrina, JM, Neciosup, S, Gomez, HL
• Formato: artículo
• Fecha de Publicación: 2023
• Institución: Instituto Nacional de Enfermedades Neoplásicas
• Repositorio: INEN-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.inen.sld.pe:20.500.14703/244
• Enlace del recurso: https: //doi.org/10.3389/fonc.2023.1193927; https://hdl.handle.net/20.500.14703/244
• Nivel de acceso: acceso abierto
• Materia: adjuvant chemotherapy; breast cancer; prognostic factor analysis; subpopulation treatment effect pattern plot; triple negative breast cancer; https://purl.org/pe-repo/ocde/ford#3.02.21

Introduction: Triple-negative breast cancer (TNBC) is a heterogeneous disease associated with a poor prognosis. Delaying in time to start adjuvant chemotherapy (TTC) has been related to an increased risk of distant recurrence-free survival (DRFS). We aimed to develop a prognostic model to estimate the effects of delayed TTC among TNBC risk subgroups. Materials and methods: We analyzed 687 TNBC patients who received adjuvant chemotherapy at the Instituto Nacional de Enfermedades Neoplasicas (Lima, Peru). Database was randomly divided to create a discovery set (n=344) and a validation set (n=343). Univariate and multivariate Cox regression models were performed to identify prognostic factors for DRFS. Risk stratification was implemented through two models developed based on proportional hazard ratios from significant clinicopathological characteristics. Subpopulation treatment effect pattern plot (STEPP) analysis was performed to determine the best prognostic cut-off points for stratifying TNBC subgroups according to risk scores and estimate Kaplan-Meier differences in 10-year DRFS comparing TTC (≤30 vs.>30 days). Results: In univariate analysis, patients aged ≥70 years (HR=4.65; 95% CI: 2.32-9.34; p=<0.001), those at stages pT3-T4 (HR=3.28; 95% CI: 1.57-6.83; p=0.002), and pN2-N3 (HR=3.00; 95% CI: 1.90-4.76; p=<0.001) were notably associated with higher risk. STEPP analysis defined three risk subgroups for each model. Model N°01 categorized patients into low (score: 0–31), intermediate (score:32–64), and high-risk (score: 65–100) cohorts; meanwhile, Model N°02: low (score: 0–26), intermediate (score: 27–55), and high (score: 56–100). Kaplan-Meier plots showed that in the discovery set, patients with TTC>30 days experienced a 17.5% decrease in 10-year DRFS rate (95%CI=6.7-28.3), and the impact was more remarkable in patients who belong to the high-risk subgroup (53.3% decrease in 10 years-DRFS rate). Similar results were found in the validation set. Conclusions: We developed two prognostic models based on age, pT, and pN to select the best one to classify TNBC. For Model N°02, delayed adjuvant chemotherapy conferred a higher risk of relapse in patients ≥70 years and who were characterized by pT3/T4 and pN2/N3. Thus, more efforts should be considered to avoid delayed TTC in TNBC patients, especially those in high-risk subgroups.