Development of a nomogram for predicting pathological complete response in luminal breast cancer patients following neoadjuvant chemotherapy

被引:4
作者
Garufi, Giovanna [2 ,3 ]
Carbognin, Luisa [1 ]
Sperduti, Isabella [5 ]
Miglietta, Federica [6 ,7 ]
Dieci, Maria Vittoria [6 ,7 ]
Mazzeo, Roberta [8 ,9 ]
Orlandi, Armando [10 ]
Gerratana, Lorenzo [8 ,9 ]
Palazzo, Antonella [10 ]
Fabi, Alessandra [11 ]
Paris, Ida [4 ]
Franco, Antonio [12 ]
Franceschini, Gianluca [12 ]
Fiorio, Elena [13 ]
Pilotto, Sara [13 ]
Guarneri, Valentina [6 ,7 ]
Puglisi, Fabio [8 ,9 ]
Conte, Pierfranco [6 ,7 ]
Milella, Michele [13 ]
Scambia, Giovanni [4 ]
Tortora, Giampaolo [2 ,3 ]
Bria, Emilio [2 ,3 ]
机构
[1] Fdn Policlin Univ A Gemelli IRCCS, Ple A Gemelli, Dept Women & Child Hlth & Publ Hlth, I-00168 Rome, Italy
[2] Fdn Policlin Univ Agostino Gemelli, IRCCS, Comprehens Canc Ctr, Rome, Italy
[3] Univ Cattolica Sacro Cuore, Sect Med Oncol, Rome, Italy
[4] Fdn Policlin Univ A Gemelli IRCCS, Dept Woman & Child Hlth & Publ Hlth, I-00168 Rome, Italy
[5] Regina Elena Inst Canc Res, Biostat, Rome, Italy
[6] Univ Padua, Dept Surg Oncol & Gastroenterol, Padua, Italy
[7] IRCCS, Ist Oncol Veneto IOV, Med Oncol 2, Padua, Italy
[8] IRCCS, Ctr Riferimento Oncol CRO, Oncol Med, Aviano, PN, Italy
[9] Univ Udine, Udine, Italy
[10] Fdn Policlin Univ Agostino Gemelli, IRCCS, Comprehens Canc Ctr, Rome, Italy
[11] Fdn Policlin Univ Agostino Gemelli, IRCCS, Unit Precis Med Senol, Rome, Italy
[12] Univ Cattolica Sacro Cuore, Fdn Policlin Univ A Gemelli IRCCS, Breast Unit, Rome, Italy
[13] Univ Verona Hosp Trust, Dept Med, Med Oncol, Verona, Italy
关键词
factors of response; luminal breast cancer; neoadjuvant chemotherapy; pathological complete response; predictive model; INTERNATIONAL EXPERT CONSENSUS; PREOPERATIVE CHEMOTHERAPY; PRIMARY THERAPY; STAGING SYSTEM; SURVIVAL; HIGHLIGHTS; ADJUVANT; SURGERY; BURDEN; WOMEN;
D O I
10.1177/17588359221138657
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background:Given 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. Methods:Clinicopathological 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. Results:In 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). Conclusion:The combination of commonly available clinicopathological pre-NACT factors allows to develop a nomogram which appears to reliably predict pCR in LBC.
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页数:14
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