Validation of a Novel Nomogram for Prediction of Local Relapse after Surgery for Invasive Breast Carcinoma

被引:23
|
作者
Corso, Giovanni [1 ,2 ]
Maisonneuve, Patrick [3 ]
Massari, Giulia [1 ]
Invento, Alessandra [1 ]
Pravettoni, Gabriella [2 ,4 ]
De Scalzi, Alessandra [1 ]
Intra, Mattia [1 ]
Galimberti, Viviana [1 ]
Morigi, Consuelo [1 ]
Lauretta, Milena [1 ]
Sacchini, Virgilio [2 ,5 ]
Veronesi, Paolo [1 ,2 ]
机构
[1] IEO European Inst Oncol IRCCS, Div Breast Surg, Milan, Italy
[2] Univ Milan, Fac Med, Milan, Italy
[3] IEO European Inst Oncol IRCCS, Div Epidemiol & Biostat, Milan, Italy
[4] IEO European Inst Oncol IRCCS, Appl Res Div Cognit & Psychol Sci, Milan, Italy
[5] Mem Sloan Kettering Canc Ctr, Dept Surg, Breast Serv, New York, NY 10021 USA
关键词
PATHOLOGICAL COMPLETE RESPONSE; SURGICAL ADJUVANT BREAST; POSITIVE SENTINEL NODE; PREOPERATIVE CHEMOTHERAPY; CONSERVING SURGERY; ESTROGEN-RECEPTOR; CANCER PATIENTS; FREE SURVIVAL; RECURRENCE; RISK;
D O I
10.1245/s10434-019-08160-7
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background Around 7% of women who undergo breast-conserving surgery (BCS) or mastectomy are at risk of developing ipsilateral breast tumor recurrence (IBTR). When assessing risks that, like that of IBTR, depend on multiple clinicopathological variables, nomograms are the predictive tools of choice. In this study, two independent nomograms were constructed to estimate the individualized risk of IBTR after breast surgery. Patients and Methods In this retrospective study, 18,717 consecutive patients with primary invasive breast cancer were enrolled. The training set used for building the nomograms comprised 15,124 patients (11,627 treated with BCS and 3497 with mastectomy), while the validation set included 3593 women (2565 BCS and 1028 mastectomy). Median follow-up time was 8 years in the training set and 6 years in the validation set. Multivariable Cox proportional hazards regression was used to identify independent factors for IBTR. Two separated nomograms were constructed on multivariate models for BCS and mastectomy. Results The factors that associated with IBTR after either BCS or mastectomy were identified. The two multivariable models were used to build nomograms for the prediction of IBTR 1 year, 5 years, and 10 years after BCS or after mastectomy. Five-year and 10-year IBTR rates in the BCS training set were equal to 3.50% and 7.00%, respectively, and to 5.39% and 7.94% in the mastectomy training set. The nomograms were subsequently validated with c-index values of 0.77 and 0.69 in the BCS and mastectomy validation sets, respectively. Conclusions The nomograms presented in this study provide clinicians and patients with a valuable decision-making tool for choosing between different treatment options for invasive breast cancer.
引用
收藏
页码:1864 / 1874
页数:11
相关论文
共 50 条
  • [31] Local Relapse After Breast-Conserving Therapy for Ductal Carcinoma In Situ A European Single-Center Experience and External Validation of the Memorial Sloan-Kettering Cancer Center DCIS Nomogram
    Sweldens, Caroline
    Peeters, Stephanie
    van Limbergen, Erik
    Janssen, Hilde
    Laenen, Annouschka
    Patil, Sujata
    Van Zee, Kimberly J.
    Weltens, Caroline
    CANCER JOURNAL, 2014, 20 (01): : 1 - 7
  • [32] How to make decisions in ductal carcinoma in situ? The first study of clinical applicability of the MSKCC ductal carcinoma in situ nomogram in the prediction of local recurrence risk after breast conserving surgery in a Brazilian cohort
    Marques, Larissa
    Carvalho, Heloisa
    Carvalho, Filomena
    Rodrigues, Luciana
    Aguiar, Fernando
    Barros, Alfredo
    CANCER RESEARCH, 2023, 83 (05)
  • [33] Local recurrence after breast conserving surgery for ductal carcinoma in situ
    Horvat, A. Gojkovic
    Gugic, J.
    Ratosa, I.
    Majdic, E.
    Marinko, T.
    Kosir, S. M. Paulin
    Jugovec, V.
    Korosec, P.
    Demsar, A.
    Kuhar, C. Grasic
    BREAST, 2015, 24 : S130 - S130
  • [34] Outcome after invasive local recurrence in patients with ductal carcinoma in situ of the breast
    Silverstein, MJ
    Lagios, MD
    Martino, S
    Lewinsky, BS
    Craig, PH
    Beron, PJ
    Gamagami, P
    Waisman, JR
    JOURNAL OF CLINICAL ONCOLOGY, 1998, 16 (04) : 1367 - 1373
  • [35] Development and Validation of a Novel Nomogram Integrated with Hypoxic and Lactate Metabolic Characteristics for Prognosis Prediction in Hepatocellular Carcinoma
    Qiu, Xun
    Dong, Libin
    Wang, Kai
    Zhong, Xinyang
    Xu, Hanzhi
    Xu, Shengjun
    Guo, Haijun
    Wei, Xuyong
    Chen, Wei
    Xu, Xiao
    JOURNAL OF HEPATOCELLULAR CARCINOMA, 2024, 11 : 241 - 255
  • [36] Prognostic factors and survival prediction in hepatocellular carcinoma: development and validation of a novel nomogram based on the SEER database
    Huang, Shanshan
    Zhu, Zheng
    Ruan, Yejiao
    Zhang, Fayuan
    Xu, Yueting
    Jin, Lingxiang
    Lopez-Lopez, Victor
    Merle, Philippe
    Lu, Guangrong
    Li, Liyi
    JOURNAL OF GASTROINTESTINAL ONCOLOGY, 2023, 14 (04) : 1817 - 1829
  • [37] The nomogram based on the 6-lncRNA model can promote the prognosis prediction of patients with breast invasive carcinoma
    Dankun Luo
    Wenchao Yao
    Qiang Wang
    Qiu Yang
    Xuxu Liu
    Yang Yang
    Weihui Zhang
    Dongbo Xue
    Biao Ma
    Scientific Reports, 11
  • [38] The nomogram based on the 6-lncRNA model can promote the prognosis prediction of patients with breast invasive carcinoma
    Luo, Dankun
    Yao, Wenchao
    Wang, Qiang
    Yang, Qiu
    Liu, Xuxu
    Yang, Yang
    Zhang, Weihui
    Xue, Dongbo
    Ma, Biao
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [39] Establishment and validation of a novel nomogram for survival prediction of ovarian carcinosarcoma
    Liu, Yi
    Lin, Xiaoling
    Xue, Lujiadai
    Wen, Yue
    Wang, Shuguang
    Wang, Xiaoyu
    TRANSLATIONAL CANCER RESEARCH, 2022, 11 (01) : 52 - 62
  • [40] Construction and Validation of a Novel Nomogram for Predicting the Risk of Metastasis in a Luminal B Type Invasive Ductal Carcinoma Population
    Zhu, Xu Dong
    Yu, Jia Hui
    Ai, Fu Lu
    Wang, Yue
    Lv, Wu
    Yu, Gui Lin
    Cao, Xian Kui
    Lin, Jie
    WORLD JOURNAL OF ONCOLOGY, 2023, 14 (06) : 476 - 487