Independent Predictors Of pCR Research Articles

Prognostic Value of Immunohistochemistry-based Subtyping Before and After Neoadjuvant Chemotherapy in Patients with Triple-negative Breast Cancer.

To assess the predictive and prognostic value of a subtyping method based on immunohistochemistry in patients with triple-negative breast cancer (TNBC) treated with neoadjuvant chemotherapy (NAC). This study included patients with TNBC treated with anthracycline- and taxane-based NAC and curative surgery. Immunohistochemical (IHC) subtyping was performed using core needle biopsy specimens before NAC (pre-NAC) and residual tumors after NAC (post-NAC). Logistic regression was performed to identify predictive biomarkers of pathological complete response (pCR). Invasive disease-free survival (iDFS), distant disease-free survival (DDFS), and overall survival (OS) were assessed using the log-rank test and Cox proportional hazards regression. A total of 230 patients were followed up for a median of 59 months. Clinical lymph node status and the pre-NAC subtype were independent predictors of pCR (P=0.006 and 0.005, respectively). The pre-NAC subtype was an independent prognostic factor for long-term survival (iDFS: P < 0.001, DDFS: P=0.010, and OS: P=0.044). Among patients with residual disease (RD) after NAC, approximately 45% of tumors changed their IHC subtype. Furthermore, the post-NAC subtype, but not the pre-NAC subtype, was strongly associated with the survival of patients with RD (iDFS: P < 0.001, DDFS: P=0.005, and OS: P=0.006). The IHC subtype predicted response to NAC and long-term survival in patients with early TNBC. In patients with RD, almost 45% of the tumors changed subtype after NAC. The IHC subtype should be considered when planning additional therapies pre- and post-NAC.

The Possible Role of Anti- and Protumor-Infiltrating Lymphocytes in Pathologic Complete Response in Early Breast Cancer Patients Treated with Neoadjuvant Systemic Therapy.

The tumor microenvironment, composed of pro- and antitumor immune cells, affects cancer cell behavior. We aimed to evaluate whether tumor-infiltrating lymphocyte (TIL) density and TIL subtypes in core biopsies at the diagnosis of breast cancer patients could predict a pathologic complete response (pCR; ypT0/is ypN0) from neoadjuvant systemic therapy (NST). The TIL subtypes were determined based on the proportions of presumably antitumor (CD8+, CXCL13+) and protumor (PD-1+, FOXP3+) immune cells. A prospective, noninterventional study, including 171 participants undergoing NST, was performed. The median TIL density for the entire cohort was 10% (IQR: 3.5-23.8), and 59 (35%) patients achieved pCR. TIL density was positively associated with pCR (univariately and multivariably). In the multivariable logistic regression model, TIL density was an independent predictor of pCR (p = 0.012, OR 1.27; 95% CI 1.05-1.54) when controlled for age (p = 0.232), Ki-67 (p = 0.001), node-negative status (p = 0.024), and HER2+/triple negative vs. luminal B-like subtype (p < 0.001). In our sample, higher proportions of PD-1+ TILs and FOXP3+ TILs were associated with a higher probability of pCR but the association was not statistically significant and we could not make any conclusions on the direction of associations in the model with all four biomarkers. In the exploratory multivariable analysis, we showed that only higher CD8+ TILs were associated with pCR. In conclusion, TIL density and its subtypes are associated with pCR.

Neoadjuvant camrelizumab and chemotherapy in patients with resectable esophageal squamous cell carcinoma: A prospective, single-arm, open-label study.

Esophageal cancer (EC) is a major cause of cancer-related deaths worldwide, bringing tremendous pressure to the healthcare system and patients. Esophageal squamous cell carcinoma (ESCC) is the main subtype of EC in the Chinese population. This study aimed to extend the neoadjuvant therapy cycle to 4 cycles and evaluate the efficacy and safety of neoadjuvant camrelizumab combined with chemotherapy for the treatment of resectable ESCC. The enrolled patients received neoadjuvant camrelizumab (200 mg, day 1), nab-paclitaxel (260 mg/m2, day 1) and carboplatin (area under curve; 5 mg/mL/min) every 21 days for 4 cycles, and surgery was performed within 4-6 weeks after the first day of the 4th treatment cycle. The primary endpoint of the study was the pathological complete response (pCR) rate. From December 15, 2021, to October 1, 2022, a total of 35 patients were enrolled in the study. All patients completed the full 4-cycle treatment and were deemed fit for surgical intervention. Thirty-four (97.1%) patients achieved R0 resection, 18 (51.4%) showed a pCR rate, and 27 (77.1%) achieved a major pathological response (MPR). Tumor degradation was observed in 30 out of 35 patients (85.7%). Multivariate logistic regression analyses further confirmed that age (odds ratio (OR) = 6.710, 95% confidence interval (95% CI): 3.512-44.403) and programmed death-ligand 1 (PD-L1) (OR = 2.855, 95% CI: 1.181-3.079) were independent predictors of pCR. The most prevalent adverse event (AE) was leukopenia, which was experienced by 23 out of 35 patients (65.7%). Grade 3 or higher AEs included leukopenia in 2 cases (5.7%) and neutropenia in 12 cases (34.3%). No delays in surgery were observed. As demonstrated in this study, the 4 cycles of camrelizumab combined with nab-paclitaxel and carboplatin, which exhibited a relatively high pCR rate and acceptable safety, suggest a strong rationale for its further evaluation in resectable ESCC.

A multiple-time-scale comparative study for the added value of magnetic resonance imaging-based radiomics in predicting pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Radiomics based on magnetic resonance imaging (MRI) shows potential for prediction of therapeutic effect to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC); however, thorough comparison between radiomics and traditional models is deficient. We aimed to construct multiple-time-scale (pretreatment, posttreatment, and combined) radiomic models to predict pathological complete response (pCR) and compare their utility to those of traditional clinical models. In this research, 165 LARC patients undergoing nCRT followed by surgery were enrolled retrospectively, which were divided into training and testing sets in the ratio of 7:3. Morphological features on pre- and posttreatment MRI, coupled with clinical data, were evaluated by univariable and multivariable logistic regression analysis for constructing clinical models. Radiomic parameters were derived from pre- and posttreatment T2- and diffusion-weighted images to develop the radiomic signatures. The clinical-radiomics models were then generated. All the models were developed in the training set and then tested in the testing set, the performance of which was assessed using the area under the receiver operating characteristic curve (AUC). Radiomic models were compared with the clinical models with the DeLong test. One hundred and sixty-five patients (median age, 55 years; age interquartile range, 47-62 years; 116 males) were enrolled in the study. The pretreatment maximum tumor length, posttreatment maximum tumor length, and magnetic resonance tumor regression grade were selected as independent predictors for pCR in the clinical models. In the testing set, the pre- and posttreatment and combined clinical models generated AUCs of 0.625, 0.842, and 0.842 for predicting pCR, respectively. The MRI-based radiomic models performed reasonably well in predicting pCR, but neither the pure radiomic signatures (AUCs, 0.734, 0.817, and 0.801 for the pre- and posttreatment and combined radiomic signatures, respectively) nor the clinical-radiomics models (AUCs, 0.734, 0.860, and 0.801 for the pre- and posttreatment and combined clinical-radiomics models, respectively) showed significant added value compared with the clinical models (all P > 0.05). The MRI-based radiomic models exhibited no definite added value compared with the clinical models for predicting pCR in LARC. Radiomic models can serve as ancillary tools for tailoring adequate treatment strategies.

Development and External Validation of 18F-FDG PET-Based Radiomic Model for Predicting Pathologic Complete Response after Neoadjuvant Chemotherapy in Breast Cancer.

The aim of our retrospective study is to develop and externally validate an 18F-FDG PET-derived radiomics model for predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients. A total of 87 breast cancer patients underwent curative surgery after NAC at Soonchunhyang University Seoul Hospital and were randomly assigned to a training cohort and an internal validation cohort. Radiomic features were extracted from pretreatment PET images. A radiomic-score model was generated using the LASSO method. A combination model incorporating significant clinical variables was constructed. These models were externally validated in a separate cohort of 28 patients from Soonchunhyang University Buscheon Hospital. The model performances were assessed using area under the receiver operating characteristic (AUC). Seven radiomic features were selected to calculate the radiomic-score. Among clinical variables, human epidermal growth factor receptor 2 status was an independent predictor of pCR. The radiomic-score model achieved good discriminability, with AUCs of 0.963, 0.731, and 0.729 for the training, internal validation, and external validation cohorts, respectively. The combination model showed improved predictive performance compared to the radiomic-score model alone, with AUCs of 0.993, 0.772, and 0.906 in three cohorts, respectively. The 18F-FDG PET-derived radiomic-based model is useful for predicting pCR after NAC in breast cancer.

Multiparametric Contrast-Enhanced Ultrasound in Early Prediction of Response to Neoadjuvant Chemotherapy and Recurrence-Free Survival in Breast Cancer.

We aimed to explore the value of contrast-enhanced ultrasound (CEUS) in early prediction of pathologic complete response (pCR) and recurrence-free survival (RFS) in locally advanced breast cancer (LABC) patients treated with neoadjuvant chemotherapy (NAC). LABC patients who underwent CEUS before and during NAC from March 2014 to October 2018 were included and assessed. Logistic regression analysis and the Cox proportional hazards model were used to identify independent variables associated with pCR and RFS. Among 122 women, 44 underwent pCR. Molecular subtype, peak intensity (PEAK) and change in diameter were independent predictors of pCR after one cycle of NAC (area under the receiver operating characteristic curve [AUC], 0.81; 95% CI: 0.73, 0.88); Molecular subtype, PEAK and change in time to peak (TTP) were independently associated with pCR after two cycles of NAC (AUC, 0.85; 95% CI: 0.77, 0.91). A higher clinical T (hazard ratio [HR] = 4.75; 95% CI: 1.75, 12.87; p = 0.002) and N stages (HR = 3.39; 95% CI: 1.25, 9.19; p = 0.02) and a longer TTP (HR = 1.06; 95% CI: 1.01, 1.11; p = 0.02) at pre-NAC CEUS were independently associated with poorer RFS. CEUS can be used as a technique to predict pCR and RFS early in LABC patients treated with NAC.

Early Prediction of Response to Neoadjuvant Chemotherapy Using Quantitative Parameters on Automated Breast Ultrasound Combined with Contrast-Enhanced Ultrasound in Breast Cancer.

This prospective study was aimed at evaluating the role of automated breast ultrasound (ABUS) and contrast-enhanced ultrasound (CEUS) in the early prediction of treatment response to neoadjuvant chemotherapy (NAC) in patients with breast cancer. Forty-three patients with pathologically confirmed invasive breast cancer treated with NAC were included. The standard for evaluation of response to NAC was based on surgery within 21 d of completing treatment. The patients were classified as having a pathological complete response (pCR) and a non-pCR. All patients underwent CEUS and ABUS 1 wk before receiving NAC and after two treatment cycles. The rising time (RT), time to peak (TTP), peak intensity (PI), wash-in slope (WIS) and wash-in area under the curve (Wi-AUC) were measured on the CEUS images before and after NAC. The maximum tumor diameters in the coronal and sagittal planes were measured on ABUS, and the tumor volume (V) was calculated. The difference (∆) in each parameter between the two treatment time points was compared. Binary logistic regression analysis was used to identify the predictive value of each parameter. ∆V, ∆TTP and ∆PI were independent predictors of pCR. The CEUS-ABUS model achieved the highest AUC (0.950), followed by those based on CEUS (0.918) and ABUS (0.891) alone. The CEUS-ABUS model could be used clinically to optimize the treatment of patients with breast cancer.

Differential impact of proliferation signature on efficacy of neoadjuvant chemoimmunotherapy in sTIL-high and sTIL-low triple-negative breast cancer (TNBC): Biomarker analysis of the NeoPACT trial.

507 Background: TNBCs with enrichment of stromal tumor-infiltrating lymphocytes (sTILs) and/or immune gene expression are more sensitive to neoadjuvant systemic therapy (NAST) and exhibit higher rates of pathologic complete response (pCR). Other biomarkers, including proliferation, are also prognostic in TNBC patients treated with NAST. We aim to investigate the impact of proliferation gene expression on efficacy of NAST in sTIL-high and sTIL-low TNBC. Methods: 110 TNBC patients treated with neoadjuvant chemoimmunotherapy (Carboplatin+Docetaxel+Pembrolizumab) on the phase II NeoPACT trial (NCT03639948) with available whole exome RNA sequencing were included. sTILs were scored in 5% increments by H&amp;E. Tumors were defined as sTIL-high (≥ 20% sTILs) or sTIL-low ( &lt; 20% sTILs). The ImSig Proliferation Signature score (ProlifSig) was computed from RNA sequencing data and samples were classified as ProlifSig-high (≥ median) or ProlifSig-low ( &lt; median). ProlifSig was tested for prediction of pCR in sTIL-high and sTIL-low groups. Logistic regression was used to examine the independent prognostic utility of sTILs and ProlifSig on pCR. Results: 63/110 (57%) patients achieved a pCR. 56/110 (51%) patients were classified as sTIL-high, and 54/110 (49%) classified as sTIL-low. sTILs and ProlifSig as continuous variables were each predictive of pCR (OR = 1.022, 95%CI = 1.009-1.035, P= 0.001 for sTILs; OR = 2.682, 95%CI = 1.23-5.85, P= 0.01 for ProlifSig). In the sTIL-high group, ProlifSig was not associated with pCR either as a continuous score (AUC = 0.56) or when assessed as high/low categories (pCR 78% vs. 67% in ProlifSig-high and ProlifSig-low groups, respectively; OR = 1.79, 95%CI = 0.54-5.89, P= 0.34). In contrast, in the sTIL-low group, ProlifSig was significantly associated with pCR both as continuous score (AUC = 0.74) and when assessed as high/low categories (pCR 57% vs. 29% in ProlifSig-high and ProlifSig-low groups, respectively; OR = 3.18, 95%CI = 1.03-9.86, P= 0.045). On multivariate analysis, sTILs and ProlifSig were independent predictors of pCR (OR = 1.02, 95%CI = 1.01-1.03, P= 0.004 for sTILs; OR = 3.13, 95%CI = 1.44-6.83, P= 0.004 for ProlifSig). Conclusions: In TNBC patients treated with chemoimmunotherapy sTILs and ProlifSig provide complimentary information for prediction of pCR. ProlifSig is positively associated with pCR in sTIL-low tumors but not in sTIL-high tumors. We hypothesize that the therapeutic response in sTIL-high tumors is dominated by lymphocyte-dependent cytotoxic mechanisms, while in sTIL-low tumors, the response may be dominated by proliferation-dependent responses. ProlifSig could identify a subgroup of immune low TNBCs that can achieve substantial rates of pCR with neoadjuvant chemoimmunotherapy.

Efficacy of Endocrine Therapy Plus Trastuzumab and Pertuzumab vs De-escalated Chemotherapy in Patients with Hormone Receptor–Positive/ERBB2-Positive Early Breast Cancer

Combination of chemotherapy with (dual) ERBB2 blockade is considered standard in hormone receptor (HR)-positive/ERBB2-positive early breast cancer (EBC). Despite some promising data on endocrine therapy (ET) combination with dual ERBB2 blockade in HR-positive/ERBB2-positive BC, to our knowledge, no prospective comparison of neoadjuvant chemotherapy vs ET plus ERBB2 blockade in particular with focus on molecular markers has yet been performed. To determine whether neoadjuvant de-escalated chemotherapy is superior to endocrine therapy, both in combination with pertuzumab and trastuzumab, in a highly heterogeneous HR-positive/ERBB2-positive EBC. This prospective, multicenter, neoadjuvant randomized clinical trial allocated 207 patients with centrally confirmed estrogen receptor-positive and/or progesterone receptor-positive (>1%) HR-positive/ERBB2-positive EBC to 12 weeks of standard ET (n = 100) vs paclitaxel (n = 107) plus trastuzumab and pertuzumab. A total of 186 patients were required to detect a statistically significant difference in pathological complete response (pCR) (assumptions: 19% absolute difference in pCR; power, ≥80%; 1-sided Fisher exact test, 2.5% significance level). Standard ET (aromatase inhibitor or tamoxifen) or paclitaxel, 80 mg/m2, weekly plus trastuzumab and pertuzumab every 21 days. The primary end point was pCR (ypT0/is, ypN0). Secondary end points included safety, translational research, and health-related quality of life. Omission of further chemotherapy was allowed in patients with pCR. PAM50 analysis was performed on baseline tumor biopsies. Of the 207 patients included (median [range] age, 53 [25-83] years), 121 (58%) had cT2 to cT4 tumors, and 58 (28%) had clinically node-positive EBC. The pCR rate in the ET plus trastuzumab and pertuzumab arm was 23.7% (95% CI, 15.7%-33.4%) vs 56.4% (95% CI, 46.2%-66.3%) in the paclitaxel plus trastuzumab and pertuzumab arm (odds ratio, 0.24; 95% CI, 0.12-0.46; P < .001). Both immunohistochemical ERBB2 score of 3 or higher and ERBB2-enriched subtype were independent predictors for pCR in both arms. Paclitaxel was superior to ET only in the first through third quartiles but not in the highest ERBB2 quartile by messenger RNA. In contrast with the paclitaxel plus trastuzumab and pertuzumab arm, no decrease in health-related quality of life after 12 weeks was observed in the ET plus trastuzumab and pertuzumab arm. The WSG-TP-II randomized clinical trial is, to our knowledge, the first prospective trial comparing 2 neoadjuvant de-escalation treatments in HR-positive/ERBB2-positive EBC and demonstrated an excellent pCR rate after 12 weeks of paclitaxel plus trastuzumab and pertuzumab that was clearly superior to the pCR rate after ET plus trastuzumab and pertuzumab. ClinicalTrials.gov Identifier: NCT03272477.

A Novel Predictor of Pathologic Complete Response for Neoadjuvant Immunochemotherapy in Resectable Locally Advanced Esophageal Squamous Cell Carcinoma.

Neoadjuvant immunochemotherapy (nICT) for resectable locally advanced esophageal squamous cell carcinoma (LA-ESCC) has attracted widespread attention recently, whose safety and clinical benefit was observed in clinical researches. This study aimed to develop and validate a novel predictor systemic inflammation-tumor markers index (SITI) to predict the pathological complete response (pCR) for resectable LA-ESCC patients receiving nICT. A total of 147 LA-ESCC patients who underwent nICT followed by surgery from February 2020 to April 2022 were included in the study. The dynamic change of inflammatory indexes was compared at baseline, after two cycles of nICT and postoperative one month. Least absolute shrinkage and selection operator (LASSO) regression was performed to avoid collinearity and identify key indexes, with SITI constructed. After univariate and multivariate stepwise forward logistic analyses, a nomogram for pCR prediction was developed. 41(27.9%) patients achieved pCR among 147 resectable LA-ESCC patients received nICT. Compared with baseline, most inflammatory indexes were significantly decreased at postoperative one month. 5 key indexes were identified and then a predictive index named SITI was constructed. The result showed that lower SITI and earlier clinical tumor node metastasis (cTNM) stage were more likely to achieve pCR. The nomogram for pCR prediction had excellent discrimination performance (C-index = 0.791). The SITI is an independent predictor for pCR in resectable LA-ESCC patients received nICT. To our knowledge, our nomogram is the first model using systemic inflammation-tumor markers for pCR prediction and may be a promising predictor to effectively differentiate pCR for nICT in LA-ESCC patients.

Assessing the predictive value of clinical factors to pathological complete response for locally advanced rectal cancer: An analysis of 124 patients.

To investigate the clinical factors affecting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). Clinical data of 124 LARC patients treated with nCRT and surgery in the fourth Hospital of Hebei Medical University from 2014 to 2019 were retrospectively analyzed. In this study, univariate analysis and logistic dichotomous multivariate regression analysis were used to study the clinical factors affecting pCR, and the receiver operator characteristic curve (ROC) analysis was used to further verify the accuracy of partial indexes in predictingpCR. Of the 124 enrolled patients, 19 patients (15.32%) achieved pCR. Univariate analysis showed that the number of cycles of consolidation chemotherapy, serum carcino-embryonic antigen (CEA) level before treatment, MRI longitudinal length of tumor, and extramural vascular invasion (EMVI) were statistically correlated with pCR. ROC analysis of the longitudinal length of tumor measured by MRI showed that the area under the curve (AUC) value, sensitivity and specificity were 0.735, 89.47% and 48.57% respectively, and the optimal cut-off value was 5.5cm. The ROC analysis showed that the AUC value, sensitivity and specificity of pCR prediction using CEA were 0.741, 63.16% and 90.48%, respectively, and the optimal cut-off value was 3.1ng/ml. Multivariate results showed that the number of cycles of consolidation chemotherapy, serum CEA level before treatment, and EMVI were independent predictors of pCR. The number of cycles of consolidation chemotherapy, serum CEA level before treatment, and EMVI may be important determinants of LARC patients to reach pCR after nCRT.

Intratumoral heterogeneity, treatment response, and survival outcome of ER-positive HER2-positive breast cancer.

ER+HER2+ breast cancer requires most types of systemic therapies perioperatively. However, treatment resistance is often experienced. The current study investigated the predictive and prognostic value of intratumoral heterogeneity and conventional clinicopathological factors in patients with ER+HER2+ breast cancer. This research included two patient cohorts with ER+HER2+ breast cancer. Cohort A included patients who underwent surgery without neoadjuvant chemotherapy (NAC). Cohort B comprised patients who received NAC followed by surgery. Intratumoral heterogeneity was assessed via ER and HER2 double staining, and the number of cells stained with different patterns of ER and HER2 was counted. In total, 11 of 92 tumors in cohort A and four of 45 tumors in cohort B consisted exclusively of double-positive (ER+ and HER2+) cells (homogeneous). The rest had different combinations of cells (heterogeneous). The pathological complete response (pCR) rates differed based on tumoral cell components but not intratumoral heterogeneity. The pCR rate of tumors with ER-HER2+ cells but without HER2- cells was higher than that of others (45.5% vs 4.3%; p= 0.0013). Low ER and PgR Allred scores indicated better pCR rates than high scores (p= 0.0005 and 0.024, respectively). Multivariate analysis showed that the ER Allred score and cell component of ER-HER2+ cells without HER2- cells were independent predictors of pCR (p= 0.0055 and 0.0081, respectively). In cohort B, posttreatment Ki67, but not pCR, was a prognostic factor of DFS and OS (p= 0.028 and 0.017, respectively). The prognostic value of combined posttreatment Ki67 and pCR was superior to that of either alone. Combined pCR and posttreatment Ki67 had an independent prognostic value for DFS and OS (p= 0.0068 and 0.0101, respectively). In ER+HER2+ breast cancer, the presence of ER-HER2+ cells without HER2- cells was independently associated with pCR. Combined posttreatment Ki67 and pCR can be more precise in predicting prognosis than pCR alone.

A nomogram based on platelet-to-lymphocyte ratio for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy

ObjectiveTo investigate the role of platelet-to-lymphocyte ratio (PLR) in complete pathological response (pCR) of breast cancer (BC) patients after neoadjuvant chemotherapy (NAC), as well as to establish and validate a nomogram for predicting pCR.MethodsBC patients diagnosed and treated in the First Affiliated Hospital of Xi’an Jiaotong University from January 2019 to June 2022 were included. The correlation between pCR and clinicopathological characteristics was analyzed by Chi-square test. Logistic regression analysis was performed to evaluate the factors that might affect pCR. Based on the results of regression analysis, a nomogram for predicting pCR was established and validated.ResultsA total of 112 BC patients were included in this study. 50.89% of the patients acquired pCR after NAC. Chi-square test showed that PLR was significantly correlated with pCR (X2 = 18.878, P < 0.001). And the PLR before NAC in pCR group was lower than that in Non-pCR group (t = 3.290, P = 0.001). Logistic regression analysis suggested that white blood cell (WBC) [odds ratio (OR): 0.19, 95% confidence interval (CI): 0.04–0.85, P = 0.030)], platelet (PLT) (OR: 0.19, 95%CI: 0.04–0.85, P = 0.030), PLR (OR: 0.18, 95%CI: 0.04–0.90, P = 0.036) and tumor grade (OR: 9.24, 95%CI: 1.89–45.07, P = 0.006) were independent predictors of pCR after NAC. A nomogram prediction model based on WBC, PLR, PLR and tumor grade showed a good predictive ability.ConclusionPLR, PLT, WBC and tumor grade were independent predictors of pCR in BC patients after NAC. The nomogram based on the above positive factors showed a good predictive ability.

Abstract P1-04-16: A nomogram based on clinicopathologic factors and pretreatment systemic inflammation response index to predict pathological complete response of neoadjuvant systemic therapy in HER2-positive breast cancer: A dual-center study

Abstract Purpose: Multiple pretreatment systemic inflammatory markers (SIMs) have been reported as predictors of pathological complete response (pCR) after neoadjuvant systemic therapy (NST) in patients with breast cancer (BC). However, the most significant SIM remains to be conclusively identified, and variations among different molecular subtypes remain unknown. The objective of the study was to identify the most significant SIM in patients with human epidermal growth factor receptor 2 (HER2) positive BC, and to construct a pCR-predictive nomogram combining it with other clinicopathological factors. Methods: We retrospectively reviewed the findings for 240 patients with stage I–III HER2-positive BC who underwent NST and subsequent surgery at Kaohsiung and Taichung Veterans General Hospital from 2011 to 2021. Clinicopathological factors were analyzed by stepwise logistic regression with forward selection. The data were used to construct a nomogram plot for determining the probability of pCR. Results: Among the pretreatment SIMs, only SIRI was significantly related to pCR, with an optimal cutoff value of 1.27 × 10^9/L. Stepwise logistic analyses indicated that clinical N stage, HER2 immunohistochemistry (IHC) score, hormone receptor status, targeted therapy regimen, and SIRI were independent predictors of pCR, with an area under the curve (AUC) of 0.722. The Hosmer–Lemeshow test and calibration curve revealed that the predictive ability was a good fit to actual observations. A nomogram was constructed based on the logistic model. Conclusions: Pretreatment SIRI &amp;lt; 1.27 is predictive of pCR in HER2-positive BC. Our nomogram could efficiently predict pCR and facilitate clinical decision-making before neoadjuvant treatment. Univariable and multivariable analyses for predictive factors of pathological complete response of neoadjuvant systemic therapy in HER2-positive breast cancer Citation Format: Hong Yu Wu, Yen-Dun Tzeng, Jie Ru Yang, Chih Chiang Hung. A nomogram based on clinicopathologic factors and pretreatment systemic inflammation response index to predict pathological complete response of neoadjuvant systemic therapy in HER2-positive breast cancer: A dual-center study [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-04-16.

Abstract PD12-07: PD12-07 The effect of BMI on the pathological response after neoadjuvant systemic therapy in breast cancer patients: a nationwide retrospective study

Abstract Background: Neoadjuvant systemic therapy is increasingly applied in breast cancer patients to improve surgical and oncological outcomes. There is only limited data from clinical practice on the relevance of body mass index (BMI) on the pathologic complete response (pCR) rate following neoadjuvant systemic treatment (NST). We aimed to retrospectively analyze the impact of BMI on pCR after NST for Dutch breast cancer patients. Methods: Patients diagnosed with invasive breast cancer between 2019 and 2021 who were treated with NST followed by a surgical procedure, were selected from the Netherlands Cancer Registry (NCR). Patients were divided into three groups based on BMI: patients with underweight/normal weight (BMI&amp;lt; 25 kg/m2), patients with overweight (BMI 25-29.9 kg/m2) and patients with obesity (BMI&amp;gt;30 kg/m2). Patients with unknown BMI, ER/PR/HER2 or pCR status were excluded for analysis. The primary outcome was pCR after NST. The association between BMI and pCR was estimated using logistic regression models with the expression of odds ratios (ORs). Results: After applying in- and exclusion criteria, 4430 patients were included for analysis, statified into four molecular breast cancer subtypes; HR+/HER2- (n=2256), HR+/HER2- (n=722), HR-/HER2+ (n=405) and HR-/HER2- (n=1047). The predictors age, differentiation grade, histological type, clinical tumor (cT) and nodal (cN) stage and molecular breast cancer subtype were found siginificant for achieving pCR after NST. Multivariabele regression analysis identified differentiation grade, cT and cN stage and molecular subtype as independent predictors for pCR after NST. There was no association between pCR and (continuous or categorical) BMI. Above mentioned analyses performed by stratification according to molecular breast cancer subtype, also showed no statistically meaningful association between BMI and pCR. Conclusion: In this nationwide retrospective cohort study, evaluating 3340 patients with invasive breast cancer, we found no evidence of BMI being a predictive factor for achieving pCR following NST in neither the whole cohort, nor stratified according to molecular breast cancer subtype. Table 1. Multivariable regression analysis of the total cohort Citation Format: Britt Jansen, Anke Gielen, Mariette Agteroff, Marissa van Maaren, Sandra Beijer, Martine Moossdorff, Marjolein Smidt, Emily Postma. PD12-07 The effect of BMI on the pathological response after neoadjuvant systemic therapy in breast cancer patients: a nationwide retrospective study [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD12-07.

Abstract P6-01-47: Stromal tumor infiltrating lymphocytes and pathological complete response in patients with inflammatory breast cancer treated with neoadjuvant chemotherapy

Abstract Background: Inflammatory breast cancer (IBC) is a rare (1-5%), but aggressive form of breast cancer (BC), accounting for ~10% of BC mortality. In early setting (M0), standard of care is neoadjuvant chemotherapy (NACT), followed by surgery. Nevertheless, outcome is still relatively poor. Pathological complete response (pCR) after NACT is prognostic in BC in general, and can be predicted by a high percentage of stromal tumor infiltrating lymphocytes (sTIL) in the primary tumor. The predictive value of sTIL in IBC has only been sporadically investigated, often in smaller series. Our aim was to determine which variables, including sTIL, are associated with pCR and to determine the prognostic value of pCR in IBC in a large multicentric, retrospective cohort. Patients &amp; Methods: We included patients with IBC treated with NACT+/- anti-Human Epidermal growth factor Receptor 2 (HER2) therapy, followed by surgery from 10/1996 to 10/2021 in 7 different European hospitals. Clinicopathological variables were collected and central pathological review was performed, including sTIL scoring. This study focused on M0 cases. Considered clinicopathological variables were: age, histology, tumor grade, estrogen receptor status (ER), HER2 status, focality (unifocal vs not), and baseline locoregional nodal status (Table 1). Associations between pCR, clinicopathological variables and sTIL were assessed using Firth’s logistic regression models: Model 1 was adjusted for center, Model 2 additionally included all variables of interest. Similarly, linear regression was used to investigate the association between sTIL and clinicopathological features. Univariable and multivariable Cox regression was used to evaluate the role of pCR on disease free survival (DFS), distant recurrence free survival (DRFS) and overall survival (OS). DFS and DRFS were analyzed considering death without the respective event as competing risk. Results: 494 patients were included. The distribution according to receptor status was: ER-/HER2- (24.3%), ER+/HER2- (34.4%), ER+/HER2+ (13%) and ER-/HER2+ (20.2%). pCR rate was 26% and per receptor status: ER-/HER2- (28%), ER+/HER2- (10%), ER+/HER2+ (42%) and ER-/HER2+ (45%). pCR was associated with grade (G3 vs G1/2, OR =2.79 (1.70 − 4.74), p &amp;lt; .001), ER-status (positive vs negative, OR = 0.39 (0.26 − 0.60), p &amp;lt; .001) and HER2 status (positive vs negative, OR = 3.74 (2.43 − 5.81), p &amp;lt; .001) in Model 1. Only the association with HER2 status remained significant in Model 2 (OR = 5.34 (2.83 − 10.47), p &amp;lt; .001). sTIL was scored for 385 patients. Median sTIL was 5.3% [IQR 2.0%;16.7%] and according to receptor status: ER-/HER2- (10%), ER+/HER2- (2.5%), ER+/HER2+ (6.7%) and ER-/HER2+ (8.3%). Higher sTIL was associated with NST (p = .032), grade 3 (p = .015), and ER-negativity (p = .007) in Model 1. This was no longer significant in Model 2, but the direction of the trends was preserved. sTIL was associated with pCR (5% increment, OR = 1.13 (1.05 − 1.22), p = .002), but no longer after adjustment. No association between pCR and sTIL was found stratifying by receptor status. The median FU was 9.4 years and multivariable Cox regression models revealed that ER+ and HER2+ status and achieving pCR were significantly associated with better DFS, DRFS, and OS (Table 1). Conclusion: Our results indicate that patients with HER2+ tumors have a higher probability of achieving pCR and that pCR has an independent prognostic role in IBC. This is the largest IBC study with centrally scored sTIL, demonstrating that sTIL is associated with pCR but its role as an independent predictor of pCR is still not certain. Citation Format: Maxim De Schepper, Ha-Linh Nguyen, François Richard, Florence Lerebours, Roman Vion, Florian Clatot, Anca Berghian, Marion Maetens, Sophia Leduc, Edoardo Isnaldi, Chiara Molinelli, Matteo Lambertini, Frederica Grillo, Gabriele Zoppoli, Luc Dirix, Hilde Wuyts, Kevin Punie, Hans Wildiers, Chantal Remmerie, Ann Smeets, Ines Nevelsteen, Patrick Neven, Anne Salomon, Denis Larsimont, Caroline Duhem, Patrice Viens, François BERTUCCI, Elia Biganzoli, Peter Vermeulen, Giuseppe Floris, Christine Desmedt. Stromal tumor infiltrating lymphocytes and pathological complete response in patients with inflammatory breast cancer treated with neoadjuvant chemotherapy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-01-47.

Metabolic syndrome is a risk factor for breast cancer patients receiving neoadjuvant chemotherapy: A case-control study.

To investigate the impact of metabolic syndrome (MetS) on pathologic complete response (pCR) and clinical outcomes in breast cancer (BC) patients who received neoadjuvant chemotherapy (NAC). We analyzed 221 female BC patients at Harbin Medical University Cancer Hospital who received NAC and divided them into MetS and non-MetS groups according to National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) criteria to investigate the association between MetS and clinicopathological characteristics, pathologic response, and long-term survival and to observe the changes in metabolic parameters after NAC. A total of 53 (24.0%) BC patients achieved pCR after NAC in our study. MetS status was an independent predictor of pCR, and pCR was more difficult to obtain in the MetS group than the non-MetS group (P=0.028). All metabolic parameters deteriorated significantly after NAC, especially the blood lipid index (P<0.010). The median follow-up time was 6 years. After adjusting for other prognostic factors, MetS was found to be strongly associated with an increased risk of recurrence (P=0.007) and mortality (P=0.004) in BC patients receiving NAC. Compared to individuals without any MetS component, the risk of death and disease progression increased sharply as the number of MetS components increased. In BC patients who received NAC, MetS was associated with poor outcomes, including a lower pCR rate and increased risks of recurrence and mortality.

Predicting Pathological Complete Response in Breast Cancer After Two Cycles of Neoadjuvant Chemotherapy by Tumor Reduction Rate: A Retrospective Case-Control Study.

We aimed to identify effectiveness-associated indicators and evaluate the optimal tumor reduction rate (TRR) after two cycles of neoadjuvant chemotherapy (NAC) in patients with invasive breast cancer. This retrospective case-control study included patients who underwent at least four cycles of NAC at the Department of Breast Surgery between February 2013 and February 2020. A regression nomogram model for predicting pathological responses was constructed based on potential indicators. A total of 784 patients were included, of whom 170 (21.68%) reported pathological complete response (pCR) after NAC and 614 (78.32%) had residual invasive tumors. The clinical T stage, clinical N stage, molecular subtype, and TRR were identified as independent predictors of pCR. Patients with a TRR > 35% were more likely to achieve pCR (odds ratio, 5.396; 95% confidence interval [CI], 3.299-8.825). The receiver operating characteristic (ROC) curve was plotted using the probability value, and the area under the ROC curve was 0.892 (95% CI, 0.863-0.922). TRR > 35% is predictive of pCR after two cycles of NAC, and an early evaluation model using a nomogram based on five indicators, age, clinical T stage, clinical N stage, molecular subtype, and TRR, is applicable in patients with invasive breast cancer.

Predicting neoadjuvant chemotherapy benefit using deep learning from stromal histology in breast cancer

Neoadjuvant chemotherapy (NAC) is a standard treatment option for locally advanced breast cancer. However, not all patients benefit from NAC; some even obtain worse outcomes after therapy. Hence, predictors of treatment benefit are crucial for guiding clinical decision-making. Here, we investigated the predictive potential of breast cancer stromal histology via a deep learning (DL)-based approach and proposed the tumor-associated stroma score (TS-score) for predicting pathological complete response (pCR) to NAC with a multicenter dataset. The TS-score was demonstrated to be an independent predictor of pCR, and it not only outperformed the baseline variables and stromal tumor-infiltrating lymphocytes (sTILs) but also significantly improved the prediction performance of the baseline variable-based model. Furthermore, we discovered that unlike lymphocytes, collagen and fibroblasts in the stroma were likely associated with a poor response to NAC. The TS-score has the potential to better stratify breast cancer patients in NAC settings.

Prognostic value of mesorectal package area in patients with locally advanced rectal cancer following neoadjuvant chemoradiotherapy: A retrospective cohort study.

BackgroundThe aim of this study is to explore the most effective inflammation, magnetic resonance imaging (MRI), and nutrition markers for survival and pathology complete response (pCR) in patients with locally advanced rectal cancer (LARC).MethodsA total of 278 patients with LARC undergoing neoadjuvant chemoradiotherapy (NCRT) and radical surgery from 2016 to 2019 were included. The X-tile method was used to select the optimal cutoff points for the mesorectal package area (MPA), advanced lung cancer inflammation index (ALI), prognostic nutritional index (PNI), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) scores. Cox regression analysis was used to identify risk factors of disease-free survival (DFS). To discover pCR risk factors, logistic regression analysis was employed. A predictive nomogram for DFS was constructed.ResultsAccording to the least absolute shrinkage and selection operator analysis, the MPA was the only significant predictor for the DFS in patients with LARC. Kaplan-Meier (K-M) analysis demonstrated that groups with higher MPA, PNI, SII, NLR, MLR, and ALI score had improved DFS (all P < 0.05). Receiver operating characteristic (ROC) analysis revealed that the MPA and PNI could accurately predict the pCR in patients with LARC after NCRT. The MPA score and NLR score were found to be independent predictors of DFS after NCRT using Cox regression analysis. Logistical regression analysis demonstrated that the MPA score, PNI score, and pre-NCRT cN stage were all independent predictors of pCR in patients with LARC after NCRT. Recursive partitioning analysis and time-independent ROC curve analysis demonstrated that MPA score was the most important predictor of pCR and prognosis in patients with LARC after NCRT.ConclusionsMPA was identified as the most effective marker for MRI, and the prognostic value was further confirmed by time–ROC analysis. More intense adjuvant treatment could be considered for lower–MPA score patients with LARC after NCRT. Obesity in the pelvis encourages the understanding of the prognosis prediction of patients with LARC after NCRT.