Validation of the CancerMath prognostic tool for breast cancer in Southeast Asia

BMC Cancer

Research Article

Hoong-Seam Wong¹  Shridevi Subramaniam¹  Nirmala Bhoo-Pathy²  Soo-Chin Lee³  Cheng-Har Yip⁴  Nur Aishah Taib⁴  Patrick Chan⁵  Ern-Yu Tan⁵  Helena M. Verkooijen⁶  Hui Miao⁷  Mikael Hartman⁸ 

[1] Clinical Epidemiology Unit, National Clinical Research Centre, Jalan Pahang, 50586, Kuala Lumpur, Malaysia;Clinical Epidemiology Unit, National Clinical Research Centre, Jalan Pahang, 50586, Kuala Lumpur, Malaysia;Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia;Julius Center for Health Sciences and Primary Care, University Medical Center, PO Box 85500, 3508, Utrecht, AB, The Netherlands;Department of Hematology Oncology, National University Cancer Institute, National University Health System, 1E Kent Ridge Road, 119228, Singapore, Singapore;Department of Surgery, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia;Department of Surgery, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, 308433, Singapore, Singapore;Imaging Division, University Medical Center Utrecht, PO Box 85500, 3508, Utrecht, GA, The Netherlands;Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Tahir Foundation Building, 12 Science Drive 2, 117549, Singapore, Singapore;Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Tahir Foundation Building, 12 Science Drive 2, 117549, Singapore, Singapore;Department of Surgery, National University Hospital, 1E Kent Ridge Road, 119228, Singapore, Singapore;Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, SE-171 77, Stockholm, Sweden;

关键词: Breast cancer;    CancerMath;    Prognostic model;    Asia;   

DOI  :  10.1186/s12885-016-2841-9

 received in 2015-12-16, accepted in 2016-10-05,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundCancerMath is a set of web-based prognostic tools which predict nodal status and survival up to 15 years after diagnosis of breast cancer. This study validated its performance in a Southeast Asian setting.MethodsUsing Singapore Malaysia Hospital-Based Breast Cancer Registry, clinical information was retrieved from 7064 stage I to III breast cancer patients who were diagnosed between 1990 and 2011 and underwent surgery. Predicted and observed probabilities of positive nodes and survival were compared for each subgroup. Calibration was assessed by plotting observed value against predicted value for each decile of the predicted value. Discrimination was evaluated by area under a receiver operating characteristic curve (AUC) with 95 % confidence interval (CI).ResultsThe median predicted probability of positive lymph nodes is 40.6 % which was lower than the observed 43.6 % (95 % CI, 42.5 %–44.8 %). The calibration plot showed underestimation for most of the groups. The AUC was 0.71 (95 % CI, 0.70–0.72). Cancermath predicted and observed overall survival probabilities were 87.3 % vs 83.4 % at 5 years after diagnosis and 75.3 % vs 70.4 % at 10 years after diagnosis. The difference was smaller for patients from Singapore, patients diagnosed more recently and patients with favorable tumor characteristics. Calibration plot also illustrated overprediction of survival for patients with poor prognosis. The AUC for 5-year and 10-year overall survival was 0.77 (95 % CI: 0.75–0.79) and 0.74 (95 % CI: 0.71–0.76).ConclusionsThe discrimination and calibration of CancerMath were modest. The results suggest that clinical application of CancerMath should be limited to patients with better prognostic profile.

【 授权许可】

CC BY   
© The Author(s). 2016