ABSTRACT
Background
The role of carboplatin in neoadjuvant chemotherapy for triple‐negative breast cancer (TNBC) remains controversial, particularly in settings where access to immunotherapy is limited. This study evaluated the real‐world impact of adding carboplatin to neoadjuvant chemotherapy on pathological complete response (pCR) and survival outcomes in patients with TNBC.
Methods
This retrospective multicenter study included patients with nonmetastatic TNBC treated with neoadjuvant anthracycline‐ and taxane‐based chemotherapy between 2018 and 2023 at three oncology centers in Turkey. Patients were grouped according to receipt of platinum‐containing therapy. Survival outcomes were estimated using the Kaplan–Meier method and compared with the log‐rank test. Cox regression analyses were performed to evaluate factors associated with survival. Propensity score matching was also performed as a supportive analysis.
Results
A total of 142 patients were included, of whom 45 (32.2%) received platinum‐containing neoadjuvant chemotherapy. Overall, 80 patients (56.3%) achieved pCR. The pCR rate was significantly higher in the platinum group than in the non‐platinum group (68.9% vs. 50.5%, p = 0.031). After a median follow‐up of 57 months, 24 deaths and 33 DFS events were observed. Median OS and DFS were not reached. The 60‐month OS rate was 96.0% in the platinum group and 73.9% in the non‐platinum group (log‐rank p = 0.027), whereas the 60‐month DFS rates were 86.1% and 67.6%, respectively (log‐rank p = 0.139). Patients who achieved pCR had significantly better OS and DFS than those with residual disease. In the propensity score‐matched cohort, non‐platinum treatment remained associated with inferior OS and DFS.
Conclusions
In this multicenter real‐world cohort, carboplatin was associated with a higher pCR rate and numerically favorable survival outcomes. These findings may be clinically relevant where immunotherapy is not readily accessible but should be considered hypothesis‐generating and require prospective validation.
Keywords: carboplatin, neoadjuvant chemotherapy, overall survival, pathological complete response, triple‐negative breast cancer
1. Introduction
Breast cancer is the most diagnosed malignancy and the leading cause of cancer‐related mortality worldwide [1]. Triple‐negative breast cancer (TNBC), defined by the absence of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2) expression, accounts for approximately 15%–20% of all breast cancer cases. TNBC remains a major clinical challenge due to its aggressive biology and limited therapeutic options compared with hormone receptor‐positive or HER2‐positive breast cancer [2].
Triple‐negative breast cancer is highly sensitive to cytotoxic chemotherapy; however, treatment options remain limited. Neoadjuvant chemotherapy (ChT) is widely accepted as the standard treatment for early‐stage TNBC, particularly in tumors larger than 2 cm. Neoadjuvant ChT allows early assessment of tumor response, reduces surgical morbidity, and improves survival by enabling treatment of residual disease [3, 4]. Pathological complete response (pCR) following neoadjuvant ChT has been shown to predict survival benefits in TNBC [5], with a stronger prognostic value than in hormone receptor–positive breast cancer. Conventional neoadjuvant regimens consisting of anthracycline, cyclophosphamide, and taxane achieve pCR rates of approximately 35%–45% [6].
Platinum agents, such as cisplatin and carboplatin, induce DNA damage by causing DNA strand breaks, leading to tumor cell apoptosis [7]. Several studies evaluating the addition of platinum agents to neoadjuvant therapy in TNBC have demonstrated increased pCR rates and improvements in disease‐free and event‐free survival. However, their impact on long‐term survival outcomes remains unclear. Although platinum‐containing regimens are commonly used for stage II–III disease in clinical practice, they have not yet become standard therapy [8, 9].
Currently, the standard of care for neoadjuvant treatment of TNBC includes immunotherapy combined with platinum‐containing, anthracycline‐ and taxane‐based chemotherapy. The KEYNOTE‐522 trial demonstrated a survival benefit with the addition of pembrolizumab to chemotherapy, with platinum agents used in both study arms [10]. However, due to reimbursement issues and financial toxicity, access to immunotherapy is limited in many countries. Therefore, optimizing neoadjuvant treatment strategies in the absence of immunotherapy remains essential.
In routine practice, carboplatin is frequently added to neoadjuvant chemotherapy to improve response rates. However, given the conflicting data in the literature and concerns regarding increased hematologic toxicity, this study aimed to present real‐world data on the effect of carboplatin on pCR and overall survival (OS) in patients with TNBC receiving neoadjuvant treatment, compared with those who did not receive carboplatin.
2. Materials and Methods
2.1. Study Design and Data Source
This retrospective, multicenter, observational study reviewed the medical records of patients with triple‐negative breast cancer (TNBC) who received neoadjuvant chemotherapy between 2018 and 2023. The study was conducted at three medical oncology centers in Turkey: Dokuz Eylül University Medical Oncology Clinic, İzmir City Hospital Medical Oncology Clinic, and Marmara University Medical Oncology Clinic. Patients with estrogen receptor (ER) and/or progesterone receptor (PR) expression between 1% and 10% were also included because their biological behavior was considered similar to that of TNBC and they were managed clinically using treatment approaches similar to those used for TNBC.
2.2. Inclusion and Exclusion Criteria
Patients were eligible if they were aged 18 years or older, had a diagnosis of nonmetastatic TNBC, had a primary tumor size of at least 2 cm and/or positive axillary lymph nodes at presentation, received neoadjuvant chemotherapy, underwent surgery after neoadjuvant treatment, and had at least 1 year of follow‐up. Patients with synchronous breast cancer, another active malignancy, incomplete clinical data, or loss to follow‐up were excluded. Patients who received neoadjuvant immunotherapy were not included in the analysis because immunotherapy was not routinely reimbursed during the study period.
2.3. Neoadjuvant Chemotherapy
Treatment regimens were administered according to institutional practice and national reimbursement policies. In general, patients received anthracycline‐ and taxane‐based neoadjuvant chemotherapy, with or without carboplatin. Anthracycline treatment consisted of either dose‐dense anthracycline plus cyclophosphamide administered every 2 weeks for four cycles or a standard 3‐weekly anthracycline and cyclophosphamide regimen. This was followed by taxane‐based therapy with docetaxel or paclitaxel, either alone or in combination with platinum. Administration schedules of taxanes and platinum agents were recorded.
The decision to add carboplatin was made at the discretion of the treating physician and was influenced by clinical tumor burden, nodal involvement, patient fitness, age, and institutional treatment preference. Because treatment allocation was non‐randomized, confounding by indication was considered a potential source of bias.
Only one patient received pembrolizumab during the study period; this patient was excluded from the analysis. Tumor response to neoadjuvant chemotherapy was evaluated radiologically according to RECIST version 1.1. For patients who did not complete the planned treatment, the reasons for discontinuation and the number of completed cycles were recorded. Patients were classified into two groups according to receipt of platinum‐containing neoadjuvant chemotherapy.
2.4. Definitions of Endpoints
The primary endpoint was pathological complete response (pCR), defined as the absence of residual invasive tumor in the breast and ipsilateral axillary lymph nodes (ypT0/Tis ypN0). The presence of ductal carcinoma in situ alone did not preclude classification as pCR.
Residual cancer burden (RCB) was assessed by breast pathologists at the participating centers or calculated using the MD Anderson Cancer Center online RCB calculator. RCB was recorded both as a continuous variable and as a categorical variable: RCB‐0, RCB‐I, RCB‐II, and RCB‐III. For exploratory analyses, patients with RCB‐0 or RCB‐I were considered good responders, whereas those with RCB‐II or RCB‐III were classified as other responders.
Overall survival (OS) was defined as the time from initial diagnosis to death from any cause or last follow‐up. Disease‐free survival (DFS) was defined as the time from surgery after completion of neoadjuvant therapy to recurrence or death.
2.5. Statistical Analysis
Descriptive statistics were used to summarize baseline clinicopathologic and treatment‐related characteristics. Continuous variables were reported as median and interquartile range (IQR), and categorical variables were presented as number and percentage. Comparisons between categorical variables were performed using the chi‐square test or Fisher's exact test, as appropriate. Analyses were performed using complete‐case data; no multiple imputation was applied.
Survival outcomes were estimated using the Kaplan–Meier method and compared with the log‐rank test. Patients were stratified according to receipt of platinum‐containing neoadjuvant chemotherapy and according to pathological response.
Cox proportional hazards regression models were used to evaluate factors associated with OS and DFS. Univariable analyses were first performed for pretreatment clinicopathologic variables, including age, histological grade, HER2 status, clinical tumor stage, clinical nodal stage, multifocality, bilaterality, and receipt of neoadjuvant platinum. Variables considered clinically relevant and/or statistically significant in univariable analyses were entered into multivariable models.
Treatment‐related toxicity data were reviewed retrospectively from medical records. Because adverse‐event grading and treatment‐modification records were not uniformly documented across participating centers, toxicity data were summarized descriptively when available and were not considered sufficiently robust for definitive comparative safety modeling.
To reduce overadjustment and limit potential multicollinearity, pretreatment clinical variables and post‐treatment pathological response variables were evaluated separately. In particular, pCR and RCB were not entered simultaneously into the same multivariable model because they reflect overlapping information regarding treatment response. The proportional hazards assumption was assessed using Schoenfeld residuals. All statistical tests were two‐sided, and a p‐value of < 0.05 was considered statistically significant. Statistical analyses were performed using R software (R Foundation for Statistical Computing, Vienna, Austria).
2.6. Propensity Score Matching Analysis
To reduce baseline imbalances between patients who received platinum and those who did not, propensity score matching was performed using a logistic regression model. The propensity score included age, ECOG performance status, clinical T stage, clinical N stage, ER status, PR status, HER2 status, and tumor grade. One‐to‐one nearest‐neighbor matching without replacement was applied using a caliper width of 0.2 on the logit of the propensity score.
Covariate balance before and after matching was assessed using standardized mean differences. OS and DFS were analyzed in the matched cohort using the Kaplan–Meier method and compared with the log‐rank test. Cox proportional hazards models stratified by matched pairs were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Because of the retrospective observational design, the matched analysis was considered supportive rather than definitive, and residual confounding from unmeasured variables could not be excluded.
3. Results
3.1. Patient Characteristics
Between January 2018 and December 2023, 149 patients diagnosed with TNBC who received neoadjuvant treatment were screened for inclusion. After excluding 5 patients with missing medical record data, 1 patient who received pembrolizumab, and 1 patient who was found to be HER2‐positive after treatment, a total of 142 patients were included in the final analysis.
The median age of the patients was 56 years (IQR: 48.75–65). All patients were women. At diagnosis, 83.1% had clinical stage T2 or higher disease, 84.1% had clinical stage N1 or higher disease, and 85.9% had grade 2 or higher tumors. Additional baseline patient characteristics are summarized in Table 1.
TABLE 1.
Sociodemographic and clinicopathologic features of patients.
| Variables | Platinum (+) (n = 45) | Platinum (−) (n = 97) | Total (n = 142) | p | SMD |
|---|---|---|---|---|---|
| Age, median (percentiles, 25–75), year | 52 (48.50–62) | 57 (48–66) | 56 (48.75–65) | 0.472 | 0.152 |
| ECOG PS, n (%) | |||||
| 0 | 43 (95.6%) | 93 (95.8%) | 136 (95.8%) | 1.00 | 0.177 |
| 1 | 2 (4.4%) | 4 (4.2%) | 6 (4.2%) | ||
| Histological subtype, n (%) | |||||
| Invasive breast carcinoma | 35 (77.8%) | 74 (76.3%) | 109 (76.8%) | 0.580 | |
| Invasive lobulary carcinoma | 6 (13.4%) | 12 (12.4%) | 18 (12.7%) | ||
| Mix carcinoma | 2 (4.4%) | 4 (4.1%) | 6 (4.2%) | ||
| Other | 2 (4.4%) | 7 (7.2%) | 9 (6.3%) | ||
| Primary tumor direction, n (%) | |||||
| Right breast | 22 (48.9%) | 50 (51.5%) | 72 (50.7%) | 0.146 | 0.354 |
| Left breast | 21 (46.7%) | 47 (48.5%) | 68 (47.9%) | ||
| Bilateral | 2 (4.4%) | — | 2 (1.4%) | ||
| Multifocality, n (%) | |||||
| No | 41 (91.1%) | 86 (88.7%) | 127 (89.4%) | 1.000 | |
| Yes | 4 (8.9%) | 7 (7.2%) | 11 (7.7%) | ||
| Missing | — | 4 (4.1%) | 4 (2.8%) | ||
| cT stage, n (%) | |||||
| TX | — | 2 (2.1%) | 2 (1.4%) | 0.461 | 0.412 |
| T1 | 10 (22.2%) | 12 (12.4%) | 22 (15.5%) | ||
| T2 | 28 (62.2%) | 54 (55.7%) | 82 (57.7%) | ||
| T3 | 4 (8.9%) | 18 (18.6%) | 22 (15.5%) | ||
| T4 | 3 (6.7%) | 11 (11.3%) | 14 (9.9%) | ||
| cN stage, n (%) | |||||
| N0 | 9 (20%) | 11 (11.3%) | 20 (14.1%) | 0.248 | 0.545 |
| N1 | 24 (53.3%) | 43 (44.3%) | 67 (47.2%) | ||
| N2 | 11 (24.4%) | 35 (36.1%) | 46 (32.4%) | ||
| N3 | — | 7 (7.2%) | 7 (4.9%) | ||
| Nx | 1 (2.2%) | 1 (1%) | 2 (1.4%) | ||
| Tumor Grade, n (%) | |||||
| Grade 1 | 1 (2.2%) | 1 (1%) | 2 (1.4%) | 0.686 | 0.169 |
| Grade 2 | 6 (13.3%) | 19 (19.6%) | 25 (17.6%) | ||
| Grade 3 | 28 (62.2%) | 69 (71.1%) | 97 (68.3%) | ||
| Missing | 10 (22.2%) | 8 (8.2%) | 18 (12.7%) | ||
| ER positivity, n (%) | |||||
| 0 | 38 (84.4%) | 85 (87.6%) | 123 (86.6%) | 0.604 | |
| 1%–10% | 7 (15.6%) | 12 (12.4%) | 19 (13.4%) | ||
| PR positivity, n (%) | |||||
| 0 | 45 (100%) | 94 (96.9%) | 139 (97.9%) | 0.233 | |
| 1%–10% | — | 3 (3.1%) | 3 (2.1%) | ||
| HER2 positivity a , n (%) | |||||
| 0 | 41 (91.1%) | 78 (80.4%) | 119 (83.8%) | 0.402 | 0.291 |
| +1 | 2 (4.4%) | 9 (9.3%) | 11 (7.7%) | ||
| +2 | 2 (4.4%) | 10 (10.3%) | 12 (8.5%) | ||
| BRCA status | |||||
| BRCA1 | 5 (11.6%) | 7 (7.4%) | 12 (8.8%) | ||
| BRCA2 | 2 (4.7%) | 1 (1.1%) | 3 (2.2%) | ||
| Other | 1 (2.3%) | 2 (2.1%) | 3 (2.2%) | ||
| No mutation | 11 (25.6%) | 16 (17%) | 27 (19.7%) | ||
| Missing | 24 (55.8%) | 68 (72.3%) | 92 (67.2%) |
Abbreviations: ER, Estrogen Receptor; HER2, Human Epidermal Growth Factor Receptor2; PR, Progesterone Receptor; SMD, standartized mean difference.
HER2 was evaluated here by immunohistochemical methods and those who were + 2 positive were shown to be HER2 negative by in situ hybridization (ISH) method.
3.2. Treatment and Surgery Type
All patients received anthracycline‐ and taxane‐based chemotherapy in the neoadjuvant setting, except for one patient who did not receive an anthracycline and two patients who did not receive a taxane. A total of 45 patients (32.2%) received platinum‐containing chemotherapy during the neoadjuvant period.
Breast‐conserving surgery was performed in 77 patients (54.2%), while mastectomy was performed in 60 patients (42.4%). Treatment‐related characteristics are summarized in Table 2.
TABLE 2.
Chemotherapies received in the neoadjuvant period and types of surgery performed after neoadjuvant treatment.
| Variables | Total (n = 142) |
|---|---|
| Anthracycline regime type, n (%) | |
| No anthracycline | 1 (0.7%) |
| Dose dens AC/EC | 127 (89.4%) |
| AC/EC (q21d) | 12 (9.9%) |
| Taxane‐based regime type, n (%) | |
| Paclitaxel weekly | 81 (57%) |
| Paclitaxel +carboplatin weekly | 39 (27.5%) |
| Paclitaxel+carboplatin (q21d) | 6 (4.2%) |
| Dosetaxel | 14 (9.9%) |
| No taxane | 2 (1.4%) |
| Primary breast surgery type, n (%) | |
| Breast conserving surgery | 77 (54.2%) |
| Mastectomy | 60 (42.4%) |
| Unknown | 5 (3.5%) |
| Axillary surgery type, n (%) | |
| Sentinel Lymph Node Biopsy | 89 (62.7%) |
| Axillary dissection | 44 (31%) |
| No Axillary surgery | 3 (2.1%) |
| Unknown | 6 (4.2%) |
| Neoadjuvant platinum, n (%) | |
| No | 95 (67.9%) |
| Yes | 45 (32.1%) |
Abbreviations: AC, doxorubicine plus cyclophosphamide; EC, Epirubicine plus cyclophosphamide.
Following surgery, 80 patients (56.3%) achieved pCR (defined as ypT0/TisN0), whereas 62 patients (43.7%) had residual invasive disease. Axillary lymph nodes were negative in 100 patients (70.4%). Adjuvant chemotherapy was administered to 45 patients (31.7%). Additional pathological and treatment‐related characteristics are summarized in Table 3.
TABLE 3.
Pathologic features of tumor after breast surgery, RCB classification and adjuvant chemotherapy received.
| Variables | Platinum (+) (n = 45) | Platinum (−) (n = 97) | Total (n = 142) |
|---|---|---|---|
| ypT stage, n (%) | |||
| ypTis | 5 (11.2%) | 5 (5.2%) | 10 (7%) |
| ypT0 | 25 (55.6%) | 45 (46.3%) | 70 (49.3%) |
| ypT1 | 7 (15.6%) | 16 (16.4%) | 23 (16.2%) |
| ypT2 | 8 (17.6%) | 22 (22.7%) | 30 (21.1%) |
| ypT3 | — | 8 (8.2%) | 8 (5.6%) |
| ypT4 | — | 1 (1%) | 1 (0.7%) |
| ypN stage, n (%) | |||
| ypN0 | 37 (82.2%) | 63 (64.9%) | 100 (70.4%) |
| ypN1 | 5 (11.1%) | 22 (22.7%) | 27 (19%) |
| ypN2 | 3 (6.7%) | 7 (7.2%) | 10 (7%) |
| ypN3 | — | 5 (5.2%) | 5 (3.6%) |
| Residual Cancer Burden (RCB) classification, n (%) | |||
| RCB‐0 | 27 (60%) | 39 (40.2%) | 66 (47,1%) |
| RCB‐1 | 9 (20%) | 30 (30.9%) | 39 (26.7%) |
| RCB‐2 | 7 (15.6%) | 9 (9.3%) | 16 (11.3%) |
| RCB‐3 | 2 (4.4%) | 19 (19.6%) | 21 (14.8%) |
| Residual adjuvant treatment | |||
| No | 30 (66.7%) | 66 (68%) | 96 (68.3%) |
| Capecitabine | 15 (33.3%) | 26 (26.8%) | 41 (28.9%) |
| Other | — | 5 (5.2%) | 5 (2.8%) |
| pCR status | |||
| pCR | 31 (68.9%) | 49 (50.5%) | 80 (56.3%) |
| no pCR | 14 (31.1%) | 48 (49.5%) | 62 (44.7%) |
Information regarding BRCA1, BRCA2, PALB2, and other DNA repair gene mutations was available for 45 patients (32.8%). No pathogenic mutation was detected in 27 patients (19.7%). BRCA1 mutations were identified in 12 patients (8.8%), BRCA2 mutations in 3 patients (2.2%), PALB2 mutations in 1patient (0.7%), and other mutations in 2 patients (1.5%).
Treatment‐related toxicity and treatment‐delivery data were incompletely documented across centers. Therefore, no formal comparative toxicity analysis was performed. Where available, treatment interruptions and treatment completion patterns were reviewed descriptively; however, these data were not sufficiently complete to support robust between‐group comparisons.
3.3. Efficacy
Clinical radiologic response was assessed according to RECIST version 1.1; however, pathological response was the primary endpoint of the study. Therefore, detailed RECIST response categories are not presented, and all efficacy analyses are based on pCR and RCB.
Pathological complete response (ypT0/TisN0) was achieved in 80 patients (56.3%). According to the RCB classification, RCB‐0 was observed in 66 patients (47.1%), RCB‐I in 39 patients (26.7%), RCB‐II in 16 patients (11.3%), and RCB‐III in 21 patients (14.8%).
The pCR rate was significantly higher in patients who received platinum‐based neoadjuvant chemotherapy than in those who did not (68.9% vs. 50.5%, p = 0.031). The median follow‐up duration was 57 months (95% confidence interval [95% CI], 50.99–63.03). Median OS was not reached. The OS rates for the entire cohort at 12, 24, 36, 48, and 60 months were 94.2%, 92%, 91.8%, 91.2%, and 90.3%, respectively. While the median OS in the non‐pCR arm was 49.2 months (95% CI 41.2–59.3 months), the median OS could not be estimated in the pCR arm. At 60 months, the OS rate in the pCR arm was 90%, and this difference was statistically significant (p = 0.014). In the non‐pCR arm, the median DFS was 24.2 months (95% CI 16.5–34 months), whereas the median DFS could not be estimated in the pCR arm. At 60 months, the DFS rate in the pCR arm was 92%, but this difference was not statistically significant (p = 0.052) (Figures 1 and 2).
FIGURE 1.
Kaplan–Meier curve for overall survival according to pathological complete response status.
FIGURE 2.
Kaplan–Meier curve for disease‐free survival according to pathological complete response status.
During follow‐up, a total of 24 deaths were observed, including 1 in the platinum group and 23 in the non‐platinum group. A total of 33 DFS events occurred, including 5 in the platinum group and 28 in the non‐platinum group. In the non‐platinum arm, OS rates at 12, 24, 36, 48, and 60 months were 97.9%, 89.5%, 88.4%, 81%, and 73.9%, respectively. In contrast, OS rates in the platinum arm were 100% at 12, 24, and 36 months and 96% at both 48 and 60 months. This difference was statistically significant (p = 0.027; Figure 3).
FIGURE 3.
Kaplan–Meier curve for overall survival according to neoadjuvant platinum use.
Median DFS was not reached due to an insufficient number of events. The DFS rates in the non‐platinum arm at 12, 24, 36, and 60 months were 89.2%, 79.1%, 71.8%, and 67.6%, respectively. In the platinum arm, DFS was 90.5% at 12 months and 86.1% at 24, 36, 48, and 60 months. The difference between groups was not statistically significant (p = 0.139) (Figure 4).
FIGURE 4.
Kaplan–Meier curve for disease‐free survival according to neoadjuvant platinum use.
3.4. Cox Regression Models for Baseline Factors
In univariate Cox regression analysis for overall survival, age, histological grade, HER2 status, cT stage, cN stage, multifocality, bilaterality, and neoadjuvant platinum use were evaluated. Among these variables, bilaterality was significantly associated with worse OS (HR: 10.688, 95% CI: 1.375–83.074, p = 0.024), whereas neoadjuvant platinum use was associated with improved OS (HR: 0.134, 95% CI: 0.018–0.995, p = 0.049). Other baseline factors were not significantly associated with OS in univariate analysis. For disease‐free survival, univariate Cox regression showed that HER2 IHC 2+ status was associated with worse DFS (HR: 2.543, 95% CI: 1.038–6.227, p = 0.041). Advanced nodal burden was also associated with inferior DFS, particularly cN3 disease (HR: 11.884, 95% CI: 1.328–106.370, p = 0.027). In addition, bilaterality was significantly associated with poorer DFS (HR: 11.804, 95% CI: 1.505–92.591, p = 0.019). Neoadjuvant platinum use was not significantly associated with DFS in the univariate model (HR: 0.496, 95% CI: 0.191–1.291, p = 0.151).
3.5. Cox Regression Analysis of Post‐Neoadjuvant Treatment Factors
For overall survival, univariate analysis demonstrated that achieving pCR was significantly associated with better OS (HR: 0.231, 95% CI: 0.096–0.557, p < 0.001). Increasing RCB class was associated with progressively worse OS; compared with the reference category, RCB‐II (HR: 4.269, 95% CI: 1.066–17.096, p = 0.040) and RCB‐III (HR: 12.597, 95% CI: 4.092–38.777, p < 0.001) were significant in univariate analysis, while RCB‐I was not (HR: 2.330, 95% CI: 0.656–8.283, p = 0.191). In the multivariate model for OS, RCB‐III remained an independent adverse prognostic factor (HR: 19.078, 95% CI: 4.127–88.183, p = 0.002), whereas RCB‐I and RCB‐II did not reach statistical significance.
For disease‐free survival, univariate analysis showed that pCR was strongly associated with improved DFS (HR: 0.073, 95% CI: 0.028–0.187, p < 0.001). Likewise, higher RCB class was associated with significantly worse DFS, with HRs increasing stepwise from RCB‐I to RCB‐III (RCB‐I: HR: 4.415, 95% CI: 1.171–16.647, p = 0.028; RCB‐II: HR: 9.364, 95% CI: 2.340–37.482, p = 0.001; RCB‐III: HR: 32.451, 95% CI: 9.336–112.797, p < 0.001). In multivariate analysis for DFS, pCR remained an independent predictor of improved DFS (HR: 0.028, 95% CI: 0.006–0.126, p < 0.001). All the findings are presented in Tables 4, 5, 6, 7.
TABLE 4.
Univariate analysis of pretreatment factors affecting disease‐free survival and overall survival.
| Parameter | Overall survival | Disease free‐survival | ||
|---|---|---|---|---|
| HR (95% CI) | p | HR (95% CI) | p | |
| Age (years) | 0.985 (0.953–1.018) | 0.375 | 0.989 (0.960–1.019) | 0.478 |
| Histological grade | ||||
| Grade 2 | — | 0.266 (0.033–2.152) | 0.214 | |
| Grade 3 | — | 0.196 (0.026–1.474) | 0.113 | |
| HER2 status | ||||
| +1 | 1.132 (0.327–3.922) | 0.845 | 1.161 (0.349–3.861) | 0.808 |
| +2 | 1.712 (0.582–5.033) | 0.328 | 2.543 (1.038–6.227) | 0.041 |
| cT stage | ||||
| cT1 | 0.209 (0.019–2.345) | 0.204 | 0.064 (0.004–1.025) | 0.052 |
| cT2 | 0.266 (0.034–2.076) | 0.207 | 0.247 (0.033–1.868) | 0.175 |
| cT3 | 0.423 (0.051–3.550) | 0.428 | 0.465 (0.058–3.736) | 0.472 |
| cT4 | 0.701 (0.080–6.140) | 0.748 | 0.762 (0.093–6.221) | 0.800 |
| cN stage | ||||
| cN1 | 0.603 (0.154–2.367) | 0.468 | 2.984 (0.385–23.122) | 0.295 |
| cN2 | 1.764 (0.502–6.204) | 0.376 | 6.566 (0.873–49.370) | 0.068 |
| cN3 | 1.699 (0.277–10.424) | 0.567 | 11.884 (1.328–106.370) | 0.027 |
| Multifocality (yes vs. no) | 0.746 (0.174–3.200) | 0.0693 | 1.117 (0.339–3.678) | 0.855 |
| Bilaterality (yes vs. no) | 10.688 (1.375–83.074) | 0.024 | 11.804 (1.505–92.591) | 0.019 |
| Neoadjuvant platinum (yes vs. no) | 0.134 (0.018–0.995) | 0.049 | 0.496 (0.191–1.291) | 0.151 |
Note: Values shown in bold represent statistically significant findings (p < 0.05).
Abbreviations: CI, confidence interval; cN, clinical nodal stage; cT, clinical tumor stage; DFS, disease‐free survival; HR, hazard ratio; OS, overall survival.
TABLE 5.
Multivariate analysis of pretreatment factors affecting disease‐free survival and overall survival a .
| Parameter | Overall survival | Disease free‐survival | ||
|---|---|---|---|---|
| HR (95% CI) | p | HR (95% CI) | p | |
| Age (years) | 0.987 (0.943–1.033) | 0.560 | 0.991 (0.962–1.021) | 0.554 |
| Histological grade | ||||
| Grade 2 vs. Grade 1 | — | 0.103 (0.046–0.233) | < 0.001 | |
| Grade 3 vs. Grade 1 | — | 0.074 (0.033–0.161) | < 0.001 | |
| HER2 status | ||||
| +1 vs. 0 | 0.787 (0.181–3.425) | 0.749 | 1.113 (0.335–3.694) | 0.862 |
| +2 vs. 0 | 1.007 (0.268–3.782) | 0.992 | 1.941 (0.789–4.773) | 0.149 |
| cT stage | ||||
| cT2 vs. cT1 | — | — | ||
| cT3 vs. cT1 | ||||
| cT4 vs. cT1 | ||||
| cN stage | ||||
| cN1 vs. cN0 | 1.514 (0.149–15.414) | 0.726 | — | |
| cN2 vs. cN0 | 6.796 (0.723–63.871) | 0.094 | ||
| cN3 vs. cN0 | 3.905 (0.303–50.327) | 0.296 | ||
| Multifocality (yes vs. no) | 0.425 (0.043–4.153) | 0.462 | 0.795 (0.239–2.637) | 0.707 |
| Bilaterality (yes vs. no) | — | — | 13.023 (1.664–101.918) | 0.014 |
| Neoadjuvant platinum (yes vs. no) | — | — | 0.456 (0.167–1.242) | 0.125 |
Note: Values shown in bold represent statistically significant findings (p < 0.05).
Abbreviations: CI, confidence interval; cN, clinical nodal stage; cT, clinical tumor stage; DFS, disease‐free survival; HR, hazard ratio; OS, overall survival.
Only pretreatment variables were included in this model. Post‐treatment variables such as pCR and RCB were analyzed separately to avoid overadjustment and collinearity.
TABLE 6.
Univariate and multivariate Cox regression analyses of parameters post neoadjuvant therapy for overall survival.
| Parameter | Univariate analysis | Multivariate analysis | ||
|---|---|---|---|---|
| HR (95% CI) | p | HR (95% CI) | p | |
| pCR (yes vs. no) | 0.231 (0.096–0.557) | < 0.001 | ||
| RCB | ||||
| RCB1 | 2.330 (0.656–8.283) | 0.191 | 4.478 (0.890–22.536) | 0.069 |
| RCB2 | 4.269 (1.066–17.096) | 0.040 | 5.677 (0.799–40.325) | 0.082 |
| RCB3 | 12.597 (4.092–38.777) | < 0.001 | 19.078 (4.127–88.183) | 0.002 |
Note: Values shown in bold represent statistically significant findings (p < 0.05).
TABLE 7.
Univariate and multivariate Cox regression analyses of parameters post neoadjuvant therapy for disease‐free survival.
| Parameter | Univariate analysis | Multivariate analysis | ||
|---|---|---|---|---|
| HR (95% CI) | p | HR (95% CI) | p | |
| pCR (yes vs. no) | 0.073 (0.028–0.187) | < 0.001 | 0.028 (0.006–0.126) | < 0.001 |
| RCB | ||||
| RCB1 | 4.415 (1.171–16.647) | 0.028 | ||
| RCB2 | 9.364 (2.340–37.482) | 0.001 | ||
| RCB3 | 32.451 (9.336–112.797) | < 0.001 | ||
Note: Values shown in bold represent statistically significant findings (p < 0.05).
3.6. Propensity Score Matching Analysis
After propensity score matching, a total of 66 patients were included in the matched cohort, with 33 patients in the platinum‐treated group and 33 patients in the non‐platinum group. Survival analyses demonstrated significant differences between the two groups for both overall survival (OS) and disease‐free survival (DFS). In the matched cohort, Cox proportional hazards regression analysis showed that the non‐platinum group had significantly worse OS compared with the platinum‐treated group. The hazard ratio (HR) for OS was 2.73 (95% CI: 1.54–4.83, p = 0.000552), indicating that the risk of death was approximately 2.7‐fold higher in patients who did not receive platinum.
Kaplan–Meier analysis supported these findings. The median OS was 65.6 months (95% CI: 56.8–80.2) in the platinum‐treated group and 35.8 months (95% CI: 32.3–56.0) in the non‐platinum group. Survival curves also suggested earlier occurrence of death events in the non‐platinum group. Similarly, DFS analysis revealed a significant disadvantage for the non‐platinum group. In Cox regression analysis, the HR for DFS was 2.35 (95% CI: 1.34–4.13, p = 0.00303), indicating that patients who did not receive platinum had more than twice the risk of recurrence, progression, or death compared with those who received platinum.
Consistent with the Cox model, Kaplan–Meier estimates showed that the median DFS was 54.7 months (95% CI: 46.3–70.8) in the platinum‐treated group and 23.7 months (95% CI: 20.2–36.2) in the non‐platinum group. The survival curves indicated that DFS events occurred earlier and accumulated more rapidly in the non‐platinum group. These findings supported the direction of the primary analyses in the unmatched cohort.
4. Discussion
In this multicenter real‐world cohort, the addition of carboplatin to neoadjuvant chemotherapy was associated with a higher pCR rate and favorable survival outcomes. Because treatment allocation was not randomized, these findings should be interpreted cautiously. Although propensity score–matched analyses supported the direction of the observed survival benefit, residual confounding inherent to retrospective observational studies cannot be excluded. In this study, survival analyses showed that bilaterality was one of the most consistent adverse prognostic factors, being associated with both worse OS and DFS in univariate analysis and remaining independently associated with DFS after adjustment. Although neoadjuvant platinum appeared to be associated with improved OS in the unadjusted analysis, this effect was not maintained in the multivariate model, suggesting that the initial association may have been confounded by baseline clinicopathological characteristics. In addition, factors reflecting more aggressive disease biology, such as higher histological grade and advanced nodal stage, were associated with poorer DFS. Taken together, these findings suggest that baseline tumor burden and biological aggressiveness may have had a stronger influence on survival outcomes than platinum exposure alone in this cohort.
Given the retrospective and non‐randomized nature of this study, confounding by indication was an important methodological concern. To minimize the impact of treatment‐selection bias, we conducted a propensity score–matched analysis based on pretreatment clinicopathologic variables. After matching, 66 patients were included in the matched cohort, with 33 patients in each treatment group, providing a more balanced basis for outcome comparison. Notably, the survival benefit associated with platinum‐containing neoadjuvant chemotherapy remained evident in the matched cohort. Patients in the non‐platinum group had significantly worse overall survival and disease‐free survival than those in the platinum‐treated group. The hazard ratio for overall survival was 2.73, indicating a markedly higher risk of death in patients who did not receive platinum, while the hazard ratio for disease‐free survival was 2.35, indicating a significantly higher risk of recurrence or death. Median survival estimates were also clearly in favor of the platinum‐treated group for both endpoints.
An important finding of the present study was the apparent difference between the unmatched multivariable analyses and the matched cohort analyses. In the overall cohort, the association between platinum and survival became less pronounced after adjustment, whereas in the matched cohort the survival advantage remained evident. This difference may reflect the impact of model structure, limited event numbers, and the distinction between adjustment for baseline characteristics and the inclusion of post‐treatment response variables. Therefore, the matched analyses should be interpreted as supportive but not causal evidence. The discrepancy between the OS and DFS findings deserves careful interpretation. Several factors may explain this pattern, including the limited number of recurrence events, differences in the completeness of recurrence documentation in retrospective follow‐up, and the potential influence of post‐recurrence treatments on OS. Notably, DFS became more clearly separated after propensity score matching, suggesting that baseline imbalances may have attenuated the DFS signal in the unmatched cohort.
In our analysis, the pCR rate was significantly higher in patients receiving platinum‐containing neoadjuvant therapy compared with those who did not (68.9% vs. 50.5%, p = 0.031). Previous studies have consistently shown that achieving pCR following neoadjuvant chemotherapy in TNBC is associated with improved long‐term survival outcomes [11, 12]. Consequently, strategies aimed at increasing pCR rates remain a central focus in TNBC management. Although the incorporation of platinum agents into neoadjuvant therapy has been debated for many years, recent randomized trials such as GeparSixto and BrighTNess have demonstrated a clear increase in pCR rates with carboplatin, albeit at the expense of increased toxicity. In the GeparSixto trial, pCR was achieved in 53.2% of patients receiving carboplatin compared with 36.9% in those who did not (p = 0.005) [13]. Similarly, in the BrighTNess study, the pCR rate was 58% with carboplatin plus paclitaxel versus 31% with paclitaxel alone [14].
In a randomized phase III trial conducted in India, the addition of carboplatin to neoadjuvant chemotherapy improved survival outcomes in premenopausal patients, whereas no survival benefit was observed in postmenopausal patients [15]. Furthermore, a large retrospective multicenter study demonstrated a benefit of platinum‐based neoadjuvant therapy in TNBC regardless of HER2‐low or HER2‐negative status [16]. However, in the present study, menopausal status was unavailable, and the number of patients with HER2‐low disease was limited, preventing further subgroup analyses.
Meta‐analyses evaluating the role of carboplatin in the neoadjuvant setting have yielded conflicting results. A 2021 meta‐analysis reported improved DFS but not OS with the addition of carboplatin [17], whereas another meta‐analysis demonstrated benefits in DFS and OS [18]. These discrepancies may reflect the biological heterogeneity of TNBC, variability in treatment regimens, and differences in patient populations. Additional hypotheses include the possibility that platinum exposure induces early treatment resistance or leads to reduced treatment completion rates due to increased toxicity, ultimately affecting long‐term outcomes [19]. Our findings should also be interpreted in the context of recent real‐world evidence from resource‐constrained public health care systems. In a large Brazilian public health care cohort, Mattar et al. [20] showed that achieving pCR after neoadjuvant treatment was strongly associated with improved overall survival, whereas carboplatin use was not associated with a significant OS benefit in multivariable analysis. This study is particularly relevant to our cohort because it reflects treatment decision‐making in a public health care setting where access to newer systemic therapies may be limited. Taken together with our findings, these data support the prognostic importance of pCR across different real‐world settings, while also suggesting that the independent survival impact of carboplatin may vary according to patient selection, treatment context, and available health care resources.
Interestingly, the pCR rate observed in our platinum‐treated cohort (68.9%) was higher than that reported in several pivotal trials. In the KEYNOTE‐522 study, the pCR rate in the placebo arm, which received a similar chemotherapy backbone, was approximately 51%. One potential explanation for this difference is the high proportion of patients in our cohort who received dose‐dense anthracycline‐based chemotherapy, which may have contributed to improved pathological responses.
The antitumor activity of platinum agents is primarily attributed to their ability to induce DNA cross‐linking, impair DNA repair mechanisms, and trigger apoptosis in cancer cells [21]. In a recent study evaluating neoadjuvant gemcitabine, carboplatin, and niraparib in resectable breast cancer, pCR rates were 33% in BRCA wild‐type patients and 56% in BRCA mutation carriers [22]. One speculative explanation for the numerically improved survival observed with platinum‐containing regimens is that increased DNA damage may enhance tumor immunogenicity and sensitivity to subsequent treatments [23]. However, this hypothesis remains speculative as our study did not include mechanistic or biomarker analyses. Moreover, due to the low rate of documented BRCA mutations, we were unable to assess carboplatin efficacy according to mutation status.
Toxicity remains a key consideration in the use of carboplatin in the neoadjuvant setting. In the present study, adverse‐event grading and treatment‐modification data were not uniformly documented across centers, precluding a reliable comparative safety analysis. Therefore, our findings primarily inform efficacy rather than tolerability, and the balance between response benefit and added toxicity should be further evaluated in prospective studies with standardized adverse‐event reporting.
The strengths of this study include its multicenter design and the presentation of real‐world data addressing a clinically relevant question with conflicting evidence in the literature. Our findings suggest that platinum‐containing and dose‐dense neoadjuvant regimens may improve pathological response rates, thereby contributing to treatment optimization for TNBC in settings where immunotherapy is not accessible due to reimbursement limitations. Although OS appeared numerically superior in the platinum group, this difference should be interpreted with caution and requires validation in prospective studies with adequate statistical power. Our findings may be particularly relevant in resource‐constrained settings where access to pembrolizumab remains limited. In such settings, real‐world studies are important for identifying pragmatic strategies that may improve pathological response and potentially survival outcomes in TNBC.
4.1. Limitations
The limited availability of germline testing remains an important limitation of this study. Because BRCA1/2 and other homologous recombination repair alterations may influence platinum sensitivity, incomplete and non‐uniform testing may have introduced bias. In addition, a potentially unequal distribution of mutation carriers between treatment groups cannot be excluded.
Toxicity is a clinically important issue in the use of platinum‐based neoadjuvant therapy. However, adverse‐event grading, dose modifications, and treatment delays were not uniformly documented across participating centers. For this reason, a robust comparative toxicity analysis could not be performed, and conclusions regarding safety should be interpreted cautiously.
The retrospective design introduces the potential for selection bias. The wide confidence intervals observed in several regression estimates should be interpreted cautiously, as they likely reflect the limited sample size and the relatively small number of events in some subgroups.
5. Conclusion
In this multicenter real‐world cohort of patients with TNBC, the addition of carboplatin to neoadjuvant chemotherapy was associated with higher pCR rates and numerically favorable survival outcomes. These findings support the potential role of platinum‐based treatment in selected patients, particularly in settings where access to immunotherapy is limited, but they should be considered hypothesis‐generating and require prospective validation.
Author Contributions
Halil İbrahim Ellez: conceptualization, methodology, writing – original draft, formal analysis. Hüseyin Salih Semiz: investigation, writing – review and editing, methodology. Murat Sarı: writing – review and editing, methodology, investigation. Yeşim Ağyol: investigation, methodology, data curation. Oktay Halit Aktepe: investigation, writing – review and editing, data curation. Elif Atağ: supervision, writing – review and editing, investigation, methodology. Olçun Umit Unal: writing – review and editing, data curation, supervision. Eda ÇalişkanYildirim: investigation, methodology, data curation. Nargiz Majidova: writing – review and editing, data curation.
Funding
The authors have nothing to report.
Ethics Statement
This study was conducted in accordance with the Declaration of Helsinki and its later amendments. Ethical approval was obtained from the Dokuz Eylul University Non‐Interventional Research Ethics Committee (approval date: February 7, 2024; Approval No. 2024/05‐01, İzmir, Turkey). Patient data were collected retrospectively after obtaining written informed consent from patients or their legal representatives.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgements
The authors have nothing to report.
Data Availability Statement
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.