Real‐world impact of non–breast cancer–specific death on overall survival in resectable breast cancer

Fu, Jianfei; Wu, Lidong; Jiang, Mengjie; Li, Dan; Jiang, Ting; Fu, Wei; Wang, Liangjing; Du, Jinlin

doi:10.1002/cncr.30617

Cited by 23 publications

(19 citation statements)

References 40 publications

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“…OCSD means death due to causes other than breast cancer, including cardiovascular disease, respiratory disease, diabetes mellitus and so on. In our study, advanced age and unmarried status lead to OCSD more possibly, which is in agreement with previous studies 31. Older age means a significant decline in bodily functions and the resulting worse compensatory capabilities.…”

Section: Discussionsupporting

confidence: 93%

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Nomogram Predicting Cause-Specific Mortality in Nonmetastatic Male Breast Cancer: A Competing Risk Analysis

Sun¹,

Cheng²,

Zhou³

et al. 2019

J. Cancer

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Introduction: Male breast cancer (MBC) is a rare tumor with few cases for research. Using the Surveillance, Epidemiology, and End Results program database, we carried out a competing risk analysis in patients with primary nonmetastatic MBC and built a predictive nomogram.Materials and Methods: We extracted primary nonmetastatic MBC patients according to the inclusion and exclusion criteria. Cumulative incidence function (CIF) and proportional subdistribution hazard model were adopted to explore risk factors for breast cancer-specific death (BCSD) and other cause-specific death (OCSD). Then we built a nomogram to predict the 3-year, 5-year and 8-year probabilities of BCSD and OCSD. C-indexes, Brier scores and calibration curves were chosen for validation.Results: We identified 1,978 nonmetastatic MBC patients finally. CIF analysis showed that the 3-year, 5-year and 8-year mortalities were 5.2%, 10.6% and 16.5% for BCSD, and 6.1%, 9.6% and 14.4% for OCSD. After adjustment of Fine and Gray models, black race, PR (-), advanced T/N/grade and no surgery were independently associated with BCSD. Meanwhile, elderly, unmarried status, advanced AJCC stage and no chemotherapy resulted in OCSD more possibly. A graphic nomogram was developed according to the coefficients from the Fine and Gray models. The calibration curves displayed exceptionally, with C-indexes nearly larger than 0.700 and Brier scores nearly smaller than 0.100.Conclusion: The competing risk nomogram showed good accuracy for predictive prognosis in nonmetastatic MBC patients. It was a useful implement to evaluate crude mortalities of BCSD and OCSD, and help clinicians to choose appropriate therapeutic plans.

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Section: Discussionsupporting

confidence: 93%

“…Older age means a significant decline in bodily functions and the resulting worse compensatory capabilities. Thus, advanced age is the predominant factor affecting OCSD 31. A married status brought a comfortable, confident and enjoyable emotional state.…”

Section: Discussionmentioning

confidence: 99%

Nomogram Predicting Cause-Specific Mortality in Nonmetastatic Male Breast Cancer: A Competing Risk Analysis

Sun¹,

Cheng²,

Zhou³

et al. 2019

J. Cancer

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“…And more young patients have a higher risk of mortality from IPBC, preventing the development of SPCs (13). More young patients have a higher risk of mortality from IPBC, preventing the development of SPCs (14). In addition, SIR study was not enough to ascribe causation when several risk factors are implicated (5).…”

Section: Discussionmentioning

confidence: 99%

Risk of Second Primary Cancers Among Long-Term Survivors of Breast Cancer

Weng

Zhong

et al. 2020

Front. Oncol.

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Purpose: The current study explored the risk of developing second primary cancers (SPCs) among long-term early-stage breast cancer survivors and identified risk factors to build an externally validated clinical prediction model. Methods:The cumulative incidence of SPCs was calculated by Gray method among survivors of early-stage initial primary breast cancer (IPBC). Comparisons of treatment-related risk by selected organ sites were performed. A nomogram was established to estimate the individual risk of developing SPCs based on the multivariate Fine and Gray risk model. Decision curve analysis (DCA) was used to evaluate clinical usefulness of the model. Results:The cumulative incidence of developing SPCs after early-stage IPBC was 7.43% at 10 years, 14.41% at 15 years, and 20.08% at 20 years. Radiotherapy was associated with elevated risks of any SPCs and with elevated risks of lung cancer (SHR: 1.109; P = 0.045), breast cancer (SHR: 1.389; P < 0.001), and AML (SHR: 1.298; P = 0.045). Chemotherapy was significantly associated with a declined risk of any SPCs, with decreased risks of lung (SHR: 0.895; P = 0.015) and breast cancers (SHR: 0.891; P < 0.001), as well as elevated risks of other leukemias (SHR: 1.408; P = 0.002). HR-positive status was associated with decreased risks of any SPCs; with decreased risks of breast (SHR: 0.842; P < 0.001) and ovarian cancers (SHR: 0.483; P < 0.001); and with elevated risks of urinary tract cancers (SHR: 1.214; P = 0.029). Conclusion:We found that the cumulative incidence of developing SPCs increased over time and did not plateau. Risk factors for developing SPCs identified by our study were not consistent with those of previous studies. The prediction model can help identify individuals at higher risk of SPCs.

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“…[ 5 ] Based on the latest available statistics, the proportion of non-cancer-related death has increased gradually, which has even exceeded cancer-related death in early BC survivors. [ 6 , 7 ] Cardiovascular diseases (CVD), which accounts for 35% of non-cancer-related deaths, are the most common cause of non-cancer-related death and competes with BC as the leading cause of death in older patients with early BC. [ 8 ]…”

Section: Introductionmentioning

confidence: 99%

Adjuvant chemotherapy-associated lipid changes in breast cancer patients

Wang

Tan

et al. 2020

Medicine

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Adjuvant chemotherapy may cause alterations in serum lipids in postoperative breast cancer (BC) patients, but the specific alterations caused by different chemotherapy regimens remain unclear. The aim of this study was to investigate the status of serum lipids pre- and post-chemotherapy and to compare the side effects of different chemotherapy regimens on serum lipid. We retrospectively analysed the lipid profiles of 1934 consecutive postoperative BC patients who received one of the following chemotherapy regimens: doxorubicin and cyclophosphamide followed by paclitaxel (AC-T); epirubicin and cyclophosphamide followed by paclitaxel (EC-T); cyclophosphamide and paclitaxel (TC); and fluorouracil, cyclophosphamide, and epirubicin (FEC). The levels of triglycerides (TG), total cholesterols (TC), and low-density lipoprotein (LDL-C) were significantly elevated in patients who received chemotherapy regimens above ( P < .001). With respect to different chemotherapy regimens, FEC had less side effects on lipid profiles (TG ( P = .006), high-density lipoprotein (HDL-C) ( P < .001), and LDL-C ( P < .001)) than TC regimen and AC-T and EC-T regimen. Also, the incidence of newly diagnosed dyslipidemia after chemotherapy was lower in FEC group than TC group and AC-T and EC-T group ( P < .001). Additionally, the magnitude of the alterations in lipid profiles (TG, TC, HDL-C, and LDL-C) was greater in premenopausal patients than that of the postmenopausal patients ( P = .004; P < .001; P = .002; P = .003, respectively). Moreover, after adjusting for multiple baseline covariates, anthracycline-plus-taxane-based regimens (AC-T and EC-T) were still statistically associated with a high level of TG ( P = .004) and a low level of HDL-C ( P = .033) after chemotherapy compared with FEC regimen. Also, body mass index (BMI) > 24 was associated with abnormal lipid profiles (TG, TC, HDL-C, LDL-C) post-chemotherapy compared with BMI ≤ 24 ( P < .001; P = .036; P = .012; P = .048, respectively). BC patients receiving chemotherapy may have elevated lipid profiles, and anthracycline-based regimen had less side effects on lipid profiles compared with regimens containing taxane. Therefore, it is necessary to take lipid metabolism into consideration when making chemotherapy decisions and dyslipidemia prevention and corresponding interventions are indispensable during the whole chemotherapy period.

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Real‐world impact of non–breast cancer–specific death on overall survival in resectable breast cancer

Abstract: OS was largely impaired by non-BCSD during early breast cancer. For some future clinical trial planning, especially for the oldest patients and those with HoR+ breast cancer, non-BCSD should be considered a competing risk event. Cancer 2017;123:2432-43. © 2017 American Cancer Society.

Cited by 23 publications

References 40 publications

Nomogram Predicting Cause-Specific Mortality in Nonmetastatic Male Breast Cancer: A Competing Risk Analysis

Nomogram Predicting Cause-Specific Mortality in Nonmetastatic Male Breast Cancer: A Competing Risk Analysis

Risk of Second Primary Cancers Among Long-Term Survivors of Breast Cancer

Adjuvant chemotherapy-associated lipid changes in breast cancer patients

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