Prognostic models for breast cancer: a systematic review

Abstract

BackgroundBreast cancer is the most common cancer in women worldwide, with a great diversity in outcomes among individual patients. The ability to accurately predict a breast cancer outcome is important to patients, physicians, researchers, and policy makers. Many models have been developed and tested in different settings. We systematically reviewed the prognostic models developed and/or validated for patients with breast cancer.MethodsWe conducted a systematic search in four electronic databases and some oncology websites, and a manual search in the bibliographies of the included studies. We identified original studies that were published prior to 1st January 2017, and presented the development and/or validation of models based mainly on clinico-pathological factors to predict mortality and/or recurrence in female breast cancer patients.ResultsFrom the 96 articles selected from 4095 citations found, we identified 58 models, which predicted mortality (n = 28), recurrence (n = 23), or both (n = 7). The most frequently used predictors were nodal status (n = 49), tumour size (n = 42), tumour grade (n = 29), age at diagnosis (n = 24), and oestrogen receptor status (n = 21). Models were developed in Europe (n = 25), Asia (n = 13), North America (n = 12), and Australia (n = 1) between 1982 and 2016. Models were validated in the development cohorts (n = 43) and/or independent populations (n = 17), by comparing the predicted outcomes with the observed outcomes (n = 55) and/or with the outcomes estimated by other models (n = 32), or the outcomes estimated by individual prognostic factors (n = 8). The most commonly used methods were: Cox proportional hazards regression for model development (n = 32); the absolute differences between the predicted and observed outcomes (n = 30) for calibration; and C-index/AUC (n = 44) for discrimination.Overall, the models performed well in the development cohorts but less accurately in some independent populations, particularly in patients with high risk and young and elderly patients. An exception is the Nottingham Prognostic Index, which retains its predicting ability in most independent populations.ConclusionsMany prognostic models have been developed for breast cancer, but only a few have been validated widely in different settings. Importantly, their performance was suboptimal in independent populations, particularly in patients with high risk and in young and elderly patients.Electronic supplementary materialThe online version of this article (10.1186/s12885-019-5442-6) contains supplementary material, which is available to authorized users.

Peritumor to tumor apparent diffusion coefficient ratio is associated with biologically more aggressive breast cancer features and correlates with the prognostication tools

“…Both NPI and PREDICT are recognized as reliable prognostic tools that facilitate treatment decision-making in the adjuvant setting [40,41]. Because ADC ratios are associated with factors related to the aggressiveness of breast cancer, such as tumor size and grade, upon which well-established prognostic indexes are based, we investigated the prognostic significance of ADC values and ratios compared with those of well-established prognostic indexes.…”

Breast cancer risk factors and their effects on survival: a Mendelian randomisation study

“…Providing a precise prognostication for breast cancer patients is important in order to inform them accurately about the course of the disease and to allocate them to the right treatment [2]. To date, most commonly used prognostic factors relate to tumour characteristics and the extent of the disease at the time of diagnosis [2]. Many observational studies have evaluated the association of breast cancer risk and survival with other patient characteristics and lifestylerelated risk factors [3][4][5].…”

Tamoxifen induces hypercoagulation and alterations in ERα and ERβ dependent on breast cancer sub-phenotype ex vivo

“…Since these cell lines both correspond to the clinical luminal A subtype where ER and progesterone receptor (PR) expression is evident 35,36 , this was not entirely expected. Since ER status is predictive of better prognosis following treatment [37][38][39] , we investigated whether the ERs, ERα, most commonly studied 37,40 and ERβ, considered as predictive marker of Tamoxifen resistance in breast tumours yet not clinically assessed [41][42][43] , showed any association with markers of hypercoagulation that could hold predictive value for thrombotic propensity relative to tumour phenotype.…”