| Literature DB >> 35498020 |
Aya Agha1, Xi Wang2, Ming Wang2, Eric J Lehrer3, Samantha R Horn1, Jennifer C Rosenberg1, Daniel M Trifiletti4, Roberto Diaz5, Alexander V Louie6, Nicholas G Zaorsky7.
Abstract
Background: Most breast cancer patients die of non-cancer causes. The risk of death from heart disease, a leading cause of death, is unknown. The aim of this study is to characterize the long-term risk of fatal heart disease in breast cancer patients.Entities:
Keywords: breast cancer; cardio-oncology; chemotherapy; heart disease; radiotherapy
Year: 2022 PMID: 35498020 PMCID: PMC9043135 DOI: 10.3389/fcvm.2022.784409
Source DB: PubMed Journal: Front Cardiovasc Med ISSN: 2297-055X
Demographics for patients diagnosed with breast cancer from 1992 to 2014 and for patients who died from heart disease.
| Total diagnosis | Heart disease | |
| Total patients | 1,059,048 | 47,872 |
|
| ||
| ≤29 | 5,563 (0.5) | 9 (0.02) |
| 30–39 | 49,499 (4.7) | 157(0.3) |
| 40–49 | 177,711 (16.8) | 929 (1.9) |
| 50–59 | 246,858 (23.3) | 2,622 (5.5) |
| 60–69 | 248.681 (23.5) | 7,060 (14.7) |
| 70–79 | 202,083 (19.1) | 16,591(34.7) |
| 80+ | 128,636 (12.1) | 20,504 (42.8) |
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| ||
| 1992–1997 | 140,189 (13.2) | 15,279 (31.9) |
| 1998–2003 | 269,769 (25.5) | 18,320 (38.3) |
| 2004–2008 | 277,068 (26.2) | 10,027 (20.9) |
| 2009–2014 | 372,022 (35.1) | 4,246 (8.9) |
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| T0 | 1,014 (0.1) | 16 (0.03) |
| T1 | 563,596 (53.2) | 24,082 (50.3) |
| T2 | 264,690 (25.0) | 11,432 (23.9) |
| T3 | 44,764 (4.2) | 1,477 (3.1) |
| T4 | 30,755 (2.9) | 1,706 (3.6) |
| Tis | 1,625 (0.2) | 109 (0.2) |
| Tmic | 18,966 (1.8) | 608 (1.3) |
| TX adjusted | 81,940 (7.7) | 7,166 (15.0) |
| Any T, mets | 50,065 (4.7) | 1,203 (2.5) |
| Other | 1633(0.2) | 73 (0.2) |
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| ||
| N0 | 646,142 (61.0) | 29,782 (62.2) |
| N1 | 211,141 (19.9) | 6,930 (14.5) |
| N2 | 61,547 (5.8) | 2,193 (4.6) |
| N3 | 43,745 (4.1) | 1,179 (2.5) |
| NX adjusted | 94,840 (9.0) | 7,715 (16.1) |
| Other | 1,633 (0.2) | 73 (0.2) |
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| M0 | 972,635 (91.8) | 43,961 (91.8) |
| M1 | 50,065 (4.7) | 1,203 (2.5) |
| MX | 34,715 (3.3) | 2,635 (5.5) |
| Other | 1,633 (0.2) | 73 (0.2) |
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| White | 865,759 (81.7) | 41,180 (86.0) |
| African American | 107,108 (10.1) | 4,753 (9.9) |
| Other | 80,347 (7.6) | 1,789 (3.7) |
| Unknown | 5,834 (0.6) | 150 (0.3) |
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| Left | 514,685 (48.6) | 23,016 (48.1) |
| Right | 531,516 (50.2) | 23,949 (50.0) |
| Other | 12,847 (1.2) | 907 (1.9) |
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| Beam radiation | 449,318 (42.4) | 13,259 (27.7) |
| None/unknown | 547,376 (51.7) | 32,492 (67.9) |
| Other | 62,354 (5.9) | 2,121 (4.4) |
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| Yes | 391,296 (36.9) | 5,657 (11.8) |
| No/unknown | 667,752 (63.1) | 42,215 (88.2) |
*Database “SEER 18 Regs Research Data + Hurricane Katrina Impacted Louisiana Cases, Nov 2017 Sub (1973–2015 varying)” was used.
FIGURE 1Standard mortality ratios for death from heart disease in breast cancer patients stratified by treatment received, disease laterality, and era diagnosed. (A) The Y-axis represents the SMR for death from heart disease and the X-axis depicts the time since diagnosis in years. Each color represents a different treatment received by patients: blue, only radiotherapy; orange, only chemotherapy; gray, both radiotherapy and chemotherapy; yellow, neither chemotherapy nor radiotherapy. Throughout the follow-up, the two patient groups with the highest SMR for death from heart disease were patients receiving only chemotherapy and patients receiving both radiotherapy and chemotherapy. (B,C) The Y-axis represents SMR for death from heart disease and the X-axis depicts the time since diagnosis in years. Each color represents patients with either left-sided primary disease (blue) or right-sided primary disease (orange). Panel (B) shows patients who received only radiotherapy and panel (C) is patients who received both radiotherapy and chemotherapy. For all timepoints and treatment groups, the SMR for death from heart disease was similar regardless of disease laterality. Generated from SEER Database: Incidence – SEER 13 Regs excluding AK Custom Data (with additional treatment fields), Nov 2016 Sub (1992–2014) for SMRs – Linked To County. MP-SIR session.
FIGURE 2Cumulative death in breast cancer patients over time broken down by cause of death and stage of disease. The Y-axis of each panel shows the observed number of deaths and the X-axis shows the time since diagnosis in months. Each line represents a specific cause of death with the following colors: red, heart disease; pink, breast cancer; gray, non-primary cancer; and blue, non-cancer cause. (A) Cumulative number of deaths in all breast cancer patients (regardless of stage) separated by cause of death over time. Breast cancer was the leading cause of death at all time points. (B) Cause of death in stage I patients according to the Adjusted AJCC 6th Edition. (C) Cause of death in stage II patients. (D) Cause of death in stage III patients. (E) Cause of death in stage IV patients. Breast cancer was the leading cause of death in all patients, except those with stage 1 disease. Heart disease caused the most fatalities in stage I patients at 10+ years follow-up. Panel (F) shows the percentages of cause of death for each calendar year throughout the study period. The X-axis represents calendar years and the Y-axis represents percent of death per year. Pink represents breast cancer, gray is non-breast cancer, blue is non-cancer causes, and red is heart disease. Brest cancer accounts for the most deaths followed by non-cancer causes. As calendar year increases the percentage of patients dying from breast cancer decreases and the percentage of patients dying from non-cancer causes increases. Heart disease consistently accounts for at least 16% of cause of death. Panels (A–E): generated from SEER Database: Incidence – SEER 13 Regs excluding AK Custom Data (with additional treatment fields), Nov 2016 Sub (1992–2014) for SMRs – Linked To County. MP-SIR session. Panel (F): generated from Incidence-Based Mortality – SEER 9 Regs Research Data, Nov 2018 Sub (1975–2016)
Odds ratios and hazard ratios of fatal heart disease among cancer patients.
| Multivariable logistic regression model | Multivariable fine and gray’s model | |||||
| ORs | 95% CI | HRs | 95% CI | |||
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| 1992–1997 | 1.00 | – | 1.00 | – | ||
| 1998–2003 | 0.60 | 0.58–0.61 | <0.001 | 0.74 | 0.72–0.75 | <0.001 |
| 2004–2008 | 0.30 | 0.29–0.31 | <0.001 | 0.51 | 0.50–0.52 | <0.001 |
| 2009–2014 | 0.08 | 0.08–0.09 | <0.001 | 0.36 | 0.35–0.37 | <0.001 |
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| T1 | 1.00 | – | 1.00 | – | ||
| T2 | 1.14 | 1.11–1.17 | 0.252 | 1.15 | 1.12–1.18 | <0.001 |
| T3–T4 | 1.10 | 1.05–1.15 | 0.469 | 1.14 | 1.10–1.19 | <0.001 |
| TX adjusted | 1.23 | 1.09–1.39 | 0.023 | 1.12 | 1.01–1.26 | 0.03 |
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| N0 | 1.00 | – | 1.00 | – | ||
| N1 | 0.97 | 0.94–1.00 | 0.126 | 0.98 | 0.95–1.00 | 0.095 |
| N2–N3 | 0.93 | 0.89–0.97 | 0.549 | 0.96 | 0.93–1.00 | 0.083 |
| NX adjusted | 0.87 | 0.77–0.97 | 0.07 | 1.00 | 0.89–1.12 | 0.987 |
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| <49 years | 1.00 | – | 1.00 | – | ||
| 50–59 years | 2.43 | 2.26–2.62 | <0.001 | 2.42 | 2.25–2.60 | <0.001 |
| 60–69 years | 6.63 | 6.20–7.10 | 0.013 | 6.54 | 6.12–6.99 | <0.001 |
| 70–79 years | 17.61 | 16.49–18.80 | <0.001 | 16.77 | 15.73–17.89 | <0.001 |
| 80+ years | 38.56 | 36.09–41.21 | <0.001 | 35.72 | 33.47–38.12 | <0.001 |
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| White | 1.00 | – | 1.00 | – | ||
| African American | 1.41 | 1.36–1.46 | <0.001 | 1.37 | 1.33–1.42 | <0.001 |
| Other/unknown | 0.74 | 0.71–0.78 | <0.001 | 0.77 | 0.73–0.81 | <0.001 |
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| Right-origin of primary | 1.00 | – | 1.00 | – | ||
| Left-origin of primary | 1.00 | 0.98–1.02 | 0.946 | 1.00 | 0.98–1.02 | 0.828 |
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| No/unknown | 1.00 | – | 1.00 | – | ||
| Yes | 0.71 | 0.69–0.74 | <0.001 | 0.73 | 0.71–0.76 | <0.001 |
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| None/unknown | 1.00 | – | 1.00 | – | ||
| Yes | 0.75 | 0.74–0.77 | <0.001 | 0.75 | 0.74–0.77 | <0.001 |
FIGURE 3Nomogram for likelihood of breast cancer patients dying from heart disease. The two greatest predictors of death from heart disease are earlier year of diagnosis and older age. Disease laterality does not provide meaning predictive insight into death from heart disease. Receipt of chemotherapy and radiation therapy have a relative minimal impact of death from heart disease; in this part of the analysis they have a paradoxical protective effect because of bias in selecting patients for the treatment. To use the nomogram, sum each patient’s characteristic to get a total point sum which can then be used to predict the patient’s survival probability.