Prognostic contribution of mammographic breast density and HER2 overexpression to the Nottingham Prognostic Index in patients with invasive breast cancer

Masarwah, Amro; Auvinen, Päivi; Sudah, Mazen; Dabravolskaite, Vaiva; Arponen, Otso; Sutela, Anna; Oikari, Sanna; Kosma, Veli‐Matti; Vanninen, Ritva

doi:10.1186/s12885-016-2892-y

Cited by 12 publications

(8 citation statements)

References 44 publications

(37 reference statements)

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“…Jung et al (2013) [44]LowModerateLowModerate26Kim et al (2012) [22]LowHighHighLow27Kim et al (2016) [117]ModerateHighHighLow28Lisboa et al (2003) [23]ModerateHighLowHigh29Y.Q. Liu et al (2009) [118]ModerateModerateLowModerate30Lovekin et al (1991) [119]HighModerateLowModerate31Masarwah et al (2016) [55]ModerateLowHighLow32Mazouni et al (2011) [120]ModerateModerateLowLow33Michaelson et al (2011) [42]ModerateHighLowModerate34Musial et al (2005) [121]ModerateModerateLowLow35Ni et al (2014) [122]ModerateModerateHighLow36Paik et al (1990) [123]ModerateLowLowModerate37Putter et al (2006) [124]ModerateModerateModerateModerate38Rakha et al (2014) [90]ModerateModerateLowModerate39Ravdin et al (2001) [125]LowHighModerateModerate40Ripley et al (1998) [29]ModerateHighHighModerate41Sanghani et al (2007) [126]HighHighHighModerate42Sanghani et al (2010) [38]…”

Section: Resultsmentioning

confidence: 99%

Prognostic models for breast cancer: a systematic review

2019

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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.

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Section: Resultsmentioning

confidence: 99%

Prognostic models for breast cancer: a systematic review

2019

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“…One study reported that patients with low MBD (<25%) showed worse prognosis compared to those with mixed breast density (>25%), and patients with very low MBD (<10%) showed the strongest significance compared to the remaining patients (HR, 3.275; 95% CI, 1.750–6.127) 10 . The authors also reported that patients with very low MBD (<10%) had a clinically worse disease-free survival compared to those with mixed MBD (>10%) by multivariable analysis (HR, 2.790; 95% CI, 1.724–4.516) 11 . Other papers reported the favorable prognostic effect of low MBD on breast cancer.…”

Section: Discussionmentioning

confidence: 93%

“…Third, the association between MBD and breast cancer prognosis has also been investigated, but the results have not been consistent and overall, remain controversial. Some papers reported that fatty breast was associated with worse prognosis 10 , 11 , but others reported completely opposite results suggesting a favorable prognostic effect of fatty breast 12 , 13 . Still other studies reported no association between MBD and breast cancer prognosis 14 – 16 .…”

Section: Introductionmentioning

confidence: 99%

Prognostic Influence of Preoperative Mammographic Breast Density in Operable Invasive Female Breast Cancer

Hwang

Chu

Kim

et al. 2018

Sci Rep

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We aimed to investigate the potential of preoperative mammographic breast density (MBD) as a prognostic factor in breast cancer. Data of 969 patients with primary breast cancer were analyzed. We defined low MBD as fatty or fibroglandular breast, and high MBD as heterogeneously dense or extremely dense breast, respectively. The high MBD group demonstrated a superior overall survival rate compared to the low MBD group (p < 0.001). Favorable prognostic effects of high MBD were observed in subgroups aged >50 years (p < 0.001) and with positive hormone receptor (HRc) and negative human epidermal growth factor receptor 2 (HER2) (p < 0.001). The high MBD group had a higher proportion of patients aged ≤50 years (p < 0.001) and patients with body mass index (BMI) ≤25 kg/m2 (p < 0.001), and a higher proportion of patients who received chemotherapy (p < 0.001). MBD was a significant independent prognostic factor by multivariable analysis (hazard ratio, 0.382; 95% confidence interval, 0.206–0.708). The high MBD group was associated with superior overall survival rates. Preoperative MBD was a strong independent prognostic factor in operable primary invasive female breast cancer, especially in patients with age >50 years and the HRc(+)/HER2(−) subtype. Favorable clinicopathologic features, active treatments, and other factors could contribute to this causality.

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“…7,23 Studies on breast density and breast cancer prognosis are yet to reach a consensus on the matter. There is research suggesting fatty breast density to indicate poor prognosis, 5,6 while there is also research suggesting the opposite. 24,25 In addition, there are also studies arguing that breast density has no correlation to prognosis.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, the correlation between MBD and tumor biology and prognosis has been the subject of our study. [5][6][7] In this study, we investigated correlation between breast parenchymal density and prognosis, tumor biology, reoperation rates, and prognostic factors. With the changing life habits and nutrition habits and the new diagnosis and treatment modalities, it is crucial for this correlation to be examined now.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Breast Parenchymal Density on Breast Cancer Subtypes and Prognostic Factors

Yüksel

Çulcu

Bakırarar

et al. 2020

J. Contemp. Med. Sci.

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Objective: Mammographic breast parenchymal density is the radiological composition of radiodense fibroglandular tissue and radiolucent adipose tissue. Dense breasts restrict the imaging of lesions detected by mammography and reduce the sensitivity of mammography. In this study, we investigated correlation between breast parenchymal density and prognosis, tumor biology, reoperation rates and prognostic factors. Methods: Patients who were operated for breast cancer between January 2017-December 2019 were included. The craniocaudal and mediolateral images obtained during conventional mammograms were collected in a database. The appearance of radiologically dense and lucent areas on mammography was taken as the mammographic percentage consistent with the current literatüre Results: According to breast parenchymal density, there were 21 patients (14.7%) with type 1 breast density, 29 (20.3%) with type 2, 47 (32.9%) with type 3 and 46 (32.1%) with type 4. Mean survival time due to breast cancer was 27.45±17.85 months (1-63), and 139 patients (97.2%) lived, while 4 (2.8%) were exitus. Conclusion: Increased breast parenchymal density is a crucial risk factor for breast cancer. The effects of density on tumor biology and prognosis are still controversial. Although increased breast density seems to have an effect on indicators of poor prognosis. Additional examinations should be taken into consideration in order not to cause delay or skipping in diagnosis due to the decreased sensitivity of mammography in dense breasts

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Prognostic contribution of mammographic breast density and HER2 overexpression to the Nottingham Prognostic Index in patients with invasive breast cancer

Cited by 12 publications

References 44 publications

Prognostic models for breast cancer: a systematic review

Prognostic models for breast cancer: a systematic review

Prognostic Influence of Preoperative Mammographic Breast Density in Operable Invasive Female Breast Cancer

The Effect of Breast Parenchymal Density on Breast Cancer Subtypes and Prognostic Factors

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