A real-world clinicopathological model for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer
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SUBMITTER: Fang S
PROVIDER: S-EPMC10899694 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:Background and aimsPrediction of pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for breast cancer is critical for surgical planning and evaluation of NAC efficacy. The purpose of this project was to assess the efficiency of a novel nomogram based on ultrasound and clinicopathological features for predicting pCR after NAC.MethodsThis retrospective study included 282 patients with advanced breast cancer treated with NAC from two centers. Patients received breast ultrasound before NAC and after two cycles of NAC; and the ultrasound, clinicopathological features and feature changes after two cycles of NAC were recorded. A multivariate logistic regression model was combined with bootstrapping screened for informative features associated with pCR. Then, we constructed two nomograms: an initial-baseline nomogram and a two-cycle response nomogram. Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) were analyzed. The C-index was used to evaluate predictive accuracy.ResultsSixty (60/282, 21.28%) patients achieved pCR. Triple-negative breast cancer (TNBC) and HER2-amplified types were more likely to obtain pCR. Size shrinkage, posterior acoustic pattern, and elasticity score were identified as independent factors by multivariate logistic regression. In the validation cohort, the two-cycle response nomogram showed better discrimination than the initial-baseline nomogram, with the C-index reaching 0.79. The sensitivity, specificity, and NPV of the two-cycle response nomogram were 0.77, 0.77, and 0.92, respectively.ConclusionThe two-cycle response nomogram exhibited satisfactory efficiency, which means that the nomogram was a reliable method to predict pCR after NAC. Size shrinkage after two cycles of NAC was an important in dependent factor in predicting pCR.
| S-EPMC8650158 | biostudies-literature
Project description:The study explored the impact of pretreatment serum albumin-to-alkaline phosphatase ratio (AAPR) and changes in tumor blood supply on pathological complete response (pCR) in breast cancer (BC) patients following neoadjuvant chemotherapy (NACT). Additionally, a nomogram for predicting pCR was established and validated. The study included BC patients undergoing NACT at Yongchuan Hospital of Chongqing Medical University from January 2019 to October 2023. We analyzed the correlation between pCR and clinicopathological factors, as well as tumor ultrasound features, using chi-square or Fisher's exact test. We developed and validated a nomogram predicting pCR based on regression analysis results. The study included 176 BC patients. Logistic regression analysis identified AAPR [odds ratio (OR) 2.616, 95% confidence interval (CI) 1.140-5.998, P = 0.023], changes in tumor blood supply after two NACT cycles (OR 2.247, 95%CI 1.071-4.716, P = 0.032), tumor histological grade (OR 3.843, 95%CI 1.286-10.659, P = 0.010), and HER2 status (OR 2.776, 95%CI 1.057-7.240, P = 0.038) as independent predictors of pCR after NACT. The nomogram, based on AAPR, changes in tumor blood supply after two NACT cycles, tumor histological grade, and HER2 status, demonstrated a good predictive capability.
| S-EPMC11252377 | biostudies-literature
Project description:ObjectiveTo explore the value of a predictive model combining the multiparametric magnetic resonance imaging (mpMRI) radiomics score (RAD-score), clinicopathologic features, and morphologic features for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in invasive breast carcinoma of no specific type (IBC-NST).MethodsWe enrolled, retrospectively and consecutively, 206 women with IBC-NST who underwent surgery after NAC and obtained pathological results from August 2018 to October 2021. Four RAD-scores were constructed for predicting the pCR based on fat-suppression T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), contrast-enhanced T1-weighted imaging (T1WI+C) and their combination, which was called mpMRI. The best RAD-score was combined with clinicopathologic and morphologic features to establish a nomogram model through binary logistic regression. The predictive performance of the nomogram was evaluated using the area under receiver operator characteristic (ROC) curve (AUC) and calibration curve. The clinical net benefit of the model was evaluated using decision curve analysis (DCA).ResultsThe mpMRI RAD-score had the highest diagnostic performance, with AUC of 0.848 among the four RAD-scores. T stage, human epidermal growth factor receptor-2 (HER2) status, RAD-score, and roundness were independent factors for predicting the pCR (P < 0.05 for all). The combined nomogram model based on these factors achieved AUCs of 0.930 and 0.895 in the training cohort and validation cohort, respectively, higher than other models (P < 0.05 for all). The calibration curve showed that the predicted probabilities of the nomogram were in good agreement with the actual probabilities, and DCA indicated that it provided more net benefit than the treat-none or treat-all scheme by decision curve analysis in both training and validation datasets.ConclusionThe combined nomogram model based on the mpMRI RAD-score combined with clinicopathologic and morphologic features may improve the predictive performance for the pCR of NAC in patients with IBC-NST.
| S-EPMC9207207 | biostudies-literature
Project description:BackgroundGiven the low chance of response to neoadjuvant chemotherapy (NACT) in luminal breast cancer (LBC), the identification of predictive factors of pathological complete response (pCR) represents a challenge. A multicenter retrospective analysis was performed to develop and validate a predictive nomogram for pCR, based on pre-treatment clinicopathological features.MethodsClinicopathological data from stage I-III LBC patients undergone NACT and surgery were retrospectively collected. Descriptive statistics was adopted. A multivariate model was used to identify independent predictors of pCR. The obtained log-odds ratios (ORs) were adopted to derive weighting factors for the predictive nomogram. The receiver operating characteristic analysis was applied to determine the nomogram accuracy. The model was internally and externally validated.ResultsIn the training set, data from 539 patients were gathered: pCR rate was 11.3% [95% confidence interval (CI): 8.6-13.9] (luminal A-like: 5.3%, 95% CI: 1.5-9.1, and luminal B-like: 13.1%, 95% CI: 9.8-13.4). The optimal Ki67 cutoff to predict pCR was 44% (area under the curve (AUC): 0.69; p < 0.001). Clinical stage I-II (OR: 3.67, 95% CI: 1.75-7.71, p = 0.001), Ki67 ⩾44% (OR: 3.00, 95% CI: 1.59-5.65, p = 0.001), and progesterone receptor (PR) <1% (OR: 2.49, 95% CI: 1.15-5.38, p = 0.019) were independent predictors of pCR, with high replication rates at internal validation (100%, 98%, and 87%, respectively). According to the nomogram, the probability of pCR ranged from 3.4% for clinical stage III, PR > 1%, and Ki67 <44% to 53.3% for clinical stage I-II, PR < 1%, and Ki67 ⩾44% (accuracy: AUC, 0.73; p < 0.0001). In the validation set (248 patients), the predictive performance of the model was confirmed (AUC: 0.7; p < 0.0001).ConclusionThe combination of commonly available clinicopathological pre-NACT factors allows to develop a nomogram which appears to reliably predict pCR in LBC.
| S-EPMC10017935 | biostudies-literature
Project description:Purpose To develop a scoring system for hormone receptor-positive (HR+) breast cancer patients who are expected to achieve axillary pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). To confirm the correlation between axillary status and survival rate in HR+ breast cancer after NAC. Methods Women from the Shanghai Jiao Tong University Breast Cancer Database (SJTU-BCDB) who underwent NAC for cT1-4N1-3M0 primary HR+ breast cancer between 2009 and 2018 were included in the study. In this case, patient follow up was performed until 2022 for those with complete data before and after NAC. The main outcome measures were the axillary pCR rate, overall survival (OS), and disease-free survival (DFS). The patients were randomly assigned to a test set (n = 175) and a validation set (n = 68) in a 7 : 3 ratio. A prediction risk score was then developed based on the odds ratios from the multivariate analysis of the test set (n = 175) before being validated in the validation set (n = 68). Finally, the Kaplan–Meier curves were used to explore the survival on this score system. Results From the database, 243 women were included, and the median follow-up period was 47.5 months (95% confidence interval: 41.9–53.1). The axillary pCR rate was 18.9% (46 of 243), with the independent predictors of residual positive axillary lymph nodes (LNs) being lymphovascular invasion (LVI), breast conserving surgery (BCS), Ki67 < 14%, HER2 negativity, positive lymph nodes in ultrasound (US) before surgery, and stage III histological grade (All, P < 0.05). Using the above predictors of the model, the receiver operating characteristic (ROC) curve was used for calibration and inspection, with values for the test and validation sets being 0.847 (P < 0.001; 95% CI: 0.769, 0.925) and 0.813 (P < 0.001; 95% CI: 0.741, 0.885), respectively. The total risk score ranged from 0 to 6 for the multivariate analysis, and from this range, a risk score of 0–2 was defined as a low-risk group, while scores of 3–6 were defined as the high-risk one. By constructing the survival curve, it was found that the 5-year OS rates for the low-risk and high-risk groups were 89.0% and 84.2% (P = 0.236). Similarly, the 5-year DFS rates for the low-risk and high-risk groups were 80% and 68.5% (P = 0.048), respectively. In addition, axillary pathological stages were significantly correlated with the overall survival (OS) and disease-free survival (DFS) (All, P < 0.05). Conclusion The prediction model showed good performance for HR + breast cancer. LVI, BCS, low Ki-67, HER2 negativity, suspected positive LNs before surgery, and stage III histological grade were all risk factors for residual positive axillary LNs. However, unlike pathological stages, achieving pCR in the axillary LNs does not affect the survival status.
| S-EPMC9797309 | biostudies-literature
Project description:A single tumor marker is not enough to predict the breast pathologic complete response (bpCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients. We aimed to establish a nomogram based on multiple clinicopathological features and routine serological indicators to predict bpCR after NAC in breast cancer patients. Data on clinical factors and laboratory indices of 130 breast cancer patients who underwent NAC and surgery in First Affiliated Hospital of Xi'an Jiaotong University from July 2017 to July 2019 were collected. Multivariable logistic regression analysis identified 11 independent indicators: body mass index, carbohydrate antigen 125, total protein, blood urea nitrogen, cystatin C, serum potassium, serum phosphorus, platelet distribution width, activated partial thromboplastin time, thrombin time, and hepatitis B surface antibodies. The nomogram was established based on these indicators. The 1000 bootstrap resampling internal verification calibration curve and the GiViTI calibration belt showed that the model was well calibrated. The Brier score of 0.095 indicated that the nomogram had a high accuracy. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was 0.941 (95% confidence interval: 0.900-0.982) showed good discrimination of the model. In conclusion, this nomogram showed high accuracy and specificity and did not increase the economic burden of patients, thereby having a high clinical application value.
| S-EPMC8167133 | biostudies-literature
Project description:BackgroundAccurate assessment of pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer (BC) is crucial for mitigating chemotherapy-related toxicity in patients who do not respond to the treatment. Conventional ultrasound (US) has become a pivotal method for evaluating treatment response due to its cost-effectiveness, convenience, and absence of ionizing radiation. The objective of this study was to develop a model combining US and clinicopathological characteristics at baseline, as well as US features after one cycle of NAC, to predict the pCR to NAC in BC.MethodsThis retrospective study included 74 patients with invasive BC who underwent NAC from January 2022 to December 2023. Data from US and clinicopathological characteristics before NAC (pre-NAC) and US features after one cycle of NAC were collected from all patients. Univariate and multivariate analyses were used to screen the factors independently associated with pCR and to develop the prediction model. Receiver operating characteristic (ROC) curve analysis was performed, and the area under the curve (AUC), sensitivity, and specificity were calculated to assess the predictive efficiency.ResultsFour characteristics, including human epidermal growth factor receptor 2 (HER2)-positive [odds ratio (OR) 9.265; 95% confidence interval (CI): 1.617-53.095, P=0.012] and absence of posterior feature or posterior acoustic enhancement of the breast mass on the US pre-NAC (OR 9.435; 95% CI: 1.585-56.180, P=0.014), the maximum diameter reduction measured with the US (OR 1.081; 95% CI: 1.009-1.157, P=0.026), and the angular or spiculated margin of the breast lesion with the US after one cycle of NAC (OR 9.475; 95% CI: 1.247-71.969, P=0.030), were screened as independent predictors. The AUC, sensitivity, and specificity of the prediction model were 0.912, 90.0%, and 79.6%, respectively.ConclusionsUS and clinicopathological characteristics at baseline and the US features after one cycle of NAC helped predict pCR for BC. The prediction model may enable early evaluation of the efficacy of treatment strategies and guide less invasive surgical options or personalized post-treatment plans.
| S-EPMC11652014 | biostudies-literature
Project description:BackgroundTo investigate the prognostic differences following the achievement of a pathological complete response (pCR) through neoadjuvant chemotherapy across different molecular subtypes of breast invasive ductal carcinoma.MethodsData from the Surveillance, Epidemiology, and End Results (SEER) were identified for patients undergoing neoadjuvant chemotherapy who achieved pathological complete response for invasive ductal carcinoma of the breast between 2010 and 2019.Comparing the clinicopathological characteristics of patients across different molecular subtypes. Univariate and Cox multivariate analyses were utilized to identify independent predictors of overall survival (OS) and cancer-specific survival (CSS). The Kaplan-Meier method is used to compare OS and CSS among different molecular subtypes. After propensity score matching, subgroup analysis results were presented through forest plots.ResultsThis study included 9,380 patients diagnosed with invasive ductal carcinoma, who were categorized into four molecular subtypes: 2,721 (29.01%) HR + /HER-2 + , 1,661 (17.71%) HR + /HER2-, 2,082 (22.20%) HR-/HER2 + , and 2,916 (31.08%) HR-/HER-2-. HR + /HER-2- subgroup exhibited a significantly higher proportion of patients under 50 years old than the other subtype groups (54.67% vs 40.2%, 50.35% and 51.82%, p < 0.01), and had a higher N2 + N3 stage (11.2% vs 7.24%, 8.69% and 7.48%, p < 0.01). Univariate and multivariate analysis revealed that molecular subtype was the independent risk factor for OS and CSS in patients(p < 0.05). The Kaplan-Meier curves indicated that the HR + /HER-2 + subtype had the highest OS and CSS(p < 0.05). Next, were the HR-/HER-2 + and HR-/HER-2- subtypes, with the HR + /HER-2- group having the lowest OS and CSS(p < 0.05). After propensity score matching, the OS and CSS of patients in the HR + /HER-2 + group remained higher compared to HR + /HER-2- group(p < 0.05).ConclusionsPatients with invasive ductal carcinoma of different molecular subtypes exhibit varying prognoses after achieving pCR to neoadjuvant chemotherapy. Those in the HR + /HER-2- group are younger, have a higher lymph node stage, and the lowest OS and CSS, whereas patients in the HR + /HER-2 + group have the highest OS and CSS.
| S-EPMC11403885 | biostudies-literature
Project description:Pathological complete response (pCR) achievement is undoubtedly the essential goal of neoadjuvant therapy for breast cancer, directly affecting survival endpoints. This retrospective study of 237 triple-negative breast cancer (TNBC) patients with a median follow-up of 36 months evaluated the role of adding platinum salts into standard neoadjuvant chemotherapy (NACT). After the initial four standard NACT cycles, early clinical response (ECR) was assessed and used to identify tumors and patients generally sensitive to NACT. BRCA1/2 mutation, smaller unifocal tumors, and Ki-67 ≥ 65% were independent predictors of ECR. The total pCR rate was 41%, the achievement of pCR was strongly associated with ECR (OR = 15.1, p < 0.001). According to multivariable analysis, the significant benefit of platinum NACT was observed in early responders ≥45 years, Ki-67 ≥ 65% and persisted lymph node involvement regardless of BRCA1/2 status. Early responders with pCR had a longer time to death (HR = 0.28, p < 0.001) and relapse (HR = 0.26, p < 0.001). The pCR was achieved in only 7% of non-responders. However, platinum salts favored non-responders' survival outcomes without statistical significance. Toxicity was significantly often observed in patients with platinum NACT (p = 0.003) but not for grade 3/4 (p = 0.155). These results based on real-world evidence point to the usability of ECR in NACT management, especially focusing on the benefit of platinum salts.
| S-EPMC8036281 | biostudies-literature
Project description:BackgroundIn the neoadjuvant setting, changes in the proliferation marker Ki67 are associated with primary endocrine treatment efficacy, but its value as a predictor of response to chemotherapy is still controversial.Patients and methodsWe analyzed 262 patients with centralized basal Ki67 immunohistochemical evaluation derived from 4 GEICAM (Spanish Breast Cancer Group) clinical trials of neoadjuvant chemotherapy for breast cancer. The objective was to identify the optimal threshold for Ki67 using the receiver-operating characteristic curve method to maximize its predictive value for chemotherapy benefit. We also evaluated the predictive role of the defined Ki67 cutoffs for molecular subtypes defined by estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2).ResultsA basal Ki67 cutpoint of 50% predicted pathological complete response (pCR). Patients with Ki67 >50% achieved a pCR rate of 40% (36 of 91) versus a pCR rate of 19% in patients with Ki67 ≤ 50% (33 of 171) (p = .0004). Ki67 predictive value was especially relevant in ER-HER2- and ER-HER2+ patients (pCR rates of 42% and 64%, respectively, in patients with Ki67 >50% versus 15% and 45%, respectively, in patients with Ki67 ≤ 50%; p = .0337 and .3238, respectively). Both multivariate analyses confirmed the independent predictive value of the Ki67 cutpoint of 50%.ConclusionBasal Ki67 proliferation index >50% should be considered an independent predictive factor for pCR reached after neoadjuvant chemotherapy, suggesting that cell proliferation is a phenomenon closely related to chemosensitivity. These findings could help to identify a group of patients with a potentially favorable long-term prognosis.Implications for practiceThe use of basal Ki67 status as a predictive factor of chemotherapy benefit could facilitate the identification of a patient subpopulation with high probability of achieving pathological complete response when treated with primary chemotherapy, and thus with a potentially favorable long-term prognosis.
| S-EPMC4746087 | biostudies-literature