Triple-negative breast cancer (TNBC) is a heterogeneous and complex disease characterized by the absence of estrogen receptors (ER), progesterone receptors (PR), and HER2 amplification (1, 2). TNBC could be classified into six different subtypes regarding transcriptional profiling: two basal-like (BL1 and BL2), an immunomodulatory (IM), a mesenchymal (M), a mesenchymal stem-like (MSL), and a luminal AR (LAR) subtype (3).

TNBC represents 10%-20% of all BCs worldwide (4, 5), which amounts to nearly 200,000 cases each year (6). A high prevalence of TNBC has been reported among Hispanic, Afro-American, premenopausal, or carriers of BRCA gene mutations (7, 8). In Latin America, the incidence of TNBC has been described in several countries, such as Mexico (23.1%), Venezuela (24.6%), Brazil (27%), and Peru (21.3%) (9, 10). TNBC patients from these countries usually face socioeconomic barriers to timely access to specialized cancer treatment (1, 11, 12).

TNBC also exhibits a higher probability of early tumor relapse, metastases, and death than patients with other BC subtypes (13, 14). Despite advances in BC treatments, including targeted therapies and immunotherapies, the management of TNBC remains particularly challenging. Unlike hormone receptor-positive or HER2-positive subtypes, TNBC lacks well-defined molecular targets for therapy, limiting the treatment options mainly to chemotherapy (5).

For TNBC patients, treatment mainly consists of surgery and chemotherapy (15). Adjuvant chemotherapy is the standard of care for this BC subtype because it helps to reduce the risk of a distant recurrence and improves overall survival (OS) (16, 17). Yu et al. (2013) reported that the 5-year OS for TNBC patients receiving adjuvant chemotherapy was 85% compared to 76% in those who did not (HR=0.65; 95% CI=0.52-0.81; p<0.001) (18).

In recent years, delayed initiation of adjuvant chemotherapy (TTC) has been associated with a worse prognosis (5). Among TNBC patients, TTC > 4 weeks has been associated with an 89% increase in the risk of recurrence (95% CI= 1.09-3.27; p=0.024) and a 2.49 times increase in the risk of death (95%CI= 1.30-4.76; p=0.006) compared to those with TTC ≤ 4 weeks (18).

Considering the limited access to treatment and irregular outcomes for TNBC patients, conducting studies to select patients who promptly need adjuvant chemotherapy is essential. A Subpopulation Treatment Effect Pattern Plot (STEPP) analysis is an alternative approach to estimating interactions between treatment and a continuous covariate of interest (19). Kaplan-Meier plots provided by this method allow defining cut-off points to identify subpopulations that may respond differently to a treatment. By stratifying patients into risk groups, STEPP can provide insights into personalized treatment decisions, helping optimize the benefit-risk balance for each patient.

In this current study, we aimed to develop a simple and easy-to-use prognostic model based on clinical characteristics to evaluate the effect of TTC on relapse risk among TNBC subgroups.

We developed a prognostic model using clinicopathological characteristics to estimate the individual patient’s risk of distant recurrence and to identify risk subgroups. The relationship between a delay in TTC and a worse prognosis in TNBC has been shown in previous studies (18, 20, 25). However, heterogeneity among TNBC patients requires individual decisions for treatments. The prognostic model developed in this study is based on clinicopathological characteristics that can be easily found in the clinical records of patients with TNBC, such as age, pT, and pN.

The classification of risk subgroups using prognostic models and the STEPP methodology has been developed for clinical trials and treatments for breast cancer (26, 27). For example, among premenopausal women with HR-positive/HER2-negative early breast cancer, a prognostic model based on clinicopathological characteristics was used to identify high-risk subgroups of recurrence. STEPP analysis demonstrated that high-risk patients experienced an absolute decrease of 5% for 8-year distant recurrence–free interval (DRFI) and 5-year breast cancer–free interval (BCFI) when treated with exemestane+OFS vs. tamoxifen+OFS/ (21, 22). It should be remarked that STEPP is an exploratory tool (28). It means that its application is not limited to clinical trials but rather to determining specific cut-points in the range of values of the covariate of interest (29). Thus, STEPP methodology is an alternative approach to identify interactions between treatment and covariates, define risk subgroups based on a continuous covariate (e.g., risk score/composite risk value), and evaluate the treatment effect (28).

In the discovery set for Model N°01, three significant risk subgroups for distant recurrence were identified: Low (score: 0 – 31), intermediate (score: 32 – 64), and high risk (score: 65 – 100). Regarding Model N°02, three significant risk subgroups were also presented: Low (score: 0 – 26), intermediate (score: 27 – 55), and high risk (score: 56 – 100). Subsequently, the classification of these subgroups was corroborated in the validation set for each model. Our discovery and validation sets showed that the effect in 10-year DRFS of adjuvant chemotherapy initiation >30 days compared to ≤30 days depending on the risk score. According to the TTC, patients classified as low or intermediate risk appeared to have the same effect in 10-year DRFS.In contrast, patients classified as high risk and who start chemotherapy >30 days appear to have a more significant decrease in 10-year DRFS compared to those who began earlier.

In previous studies, no relationship had been found between TTC and worse outcomes when all types of breast cancer were included in the cohort (30, 31). A Kaplan-Meier analysis showed no patterns in delaying the start of chemotherapy for more than four weeks, which indicates no significantly increased hazard ratio in the overall survival (32). Other studies supported that chemotherapy more than 12 weeks from surgery remained significantly associated with inferior survival (33, 34). Meanwhile, another one concluded that a delay of 120 days from diagnosis to chemotherapy was associated with worse outcomes (HR=1.29; 95%CI:1.22–1.37; P<0.001) (35). As has been described, there is no explicit agreement on the ideal time range for TTC so that patients with breast cancer have better outcomes.

However, studies with TNBC patients suggest that 30 days is a meaningful indicator of the quality of cancer care. A recent study reported that adjuvant chemotherapy initiation after 30 days was shown to be associated with a decrease in 10-overall survival in TNBC patients (33). An evaluation of 6827 patients, including TNBC patients and those with HER2+ treated with trastuzumab, showed that patients who started chemotherapy 61 days after surgery had worse survival compared to those who started treatment in the first 30 days after surgery (25). In this context, it appears necessary to make efforts so TNBC patients can start their adjuvant therapies as soon as possible.

Although there has been increased awareness and efforts for health education and promotion in the Latin American region, access to specialized cancer centers and coverage of drug health insurance is limited (36, 37),. This situation hinders the first contact with the health service and the initiation of treatment, which is why the process takes about seven months in countries such as Brazil and Mexico (38). Likewise, a study of Colombian patients associated a higher socioeconomic and educational level with a decreased time to diagnosis and treatment (39).

Regarding adjuvant treatment, the proportion of locally advanced breast cancer (LABC) patients that initiate adjuvant chemotherapy after eight weeks is higher in public hospitals in countries of Latin America such as Bolivia (52.0%), Peru (40.0%), Colombia (25.0%) and Mexico (12.5%), compared to private hospitals in Chile (20.0%) and Peru (20.0%) (40). Furthermore, South America was the region with the most extended approval period for the Adjuvant Treatment Optimization Trial of Lapatinib and Trastuzumab (on average 236 days), while Europe and North America were the fastest (26 days) (41).

The COVID-19 pandemic has highlighted structural problems and inequities in the healthcare system. A multicenter descriptive study showed that, during the pandemic, 51.6% of Peruvian cancer patients experienced a delay in their therapy, 42.5% had their treatment rescheduled, and 30.6% were unable to see a specialist after their diagnosis (42). In Brazil, the trend appears to be similar: 40% of patients reported a delay in cancer treatment or changes in treatment strategy (43–45).

Due to previously mentioned barriers, only 27.5% of Peruvian patients with TNBC had a TTC ≤ 30 days (20). Proper segmentation of patients with TNBC will allow the risk of patients to be evaluated and a treatment strategy that fits their condition. The current study allows physicians to estimate individual risk based on age, pT, and pN to suggest who should urgently start adjuvant chemotherapy.

In conclusion, we developed two predictive models based on age, pT, and pN. Model N°02 was the best one to classify TNBC patients’ candidates for adjuvant chemotherapy into three subgroups: Low (score: 0 – 26), intermediate (score: 27 – 55), and high risk (score: 56 – 100). High-risk patients with TNBC who started their treatment >30 days experienced a decrease from 75.0% to 21.6% in 10-year DRFS, compared to those who started<30 days. This trend was confirmed in the validation cohort (58.8% to 36.1%). Thus, we suggest using our model to bring additional efforts to high-risk patients with TNBC to avoid increasing their relapse probabilities.

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.

The study was approved by the Ethics Review Board of the Instituto Nacional de Enfermedades Neoplasicas (INEN 22-03) and conducted in compliance with all relevant ethical guidelines.

Conception and design: HG, YF, JP, ZM. Administrative support: ZM, YF. Collection and assembly of data: ZM. Data analysis and interpretation: ZM, YF, JP, HG. Manuscript writing: All authors. Final approval of manuscript: All authors. Accountable for all aspects of the work: All authors. All authors contributed to the article and approved the submitted version.