Menopausal hormone therapy and incidence, mortality, and survival of breast cancer subtypes: A prospective cohort study

Menopausal hormone therapy and incidence, mortality, and survival of breast cancer subtypes: A prospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Menopausal hormone therapy and incidence, mortality, and survival of breast cancer subtypes: A prospective cohort study Marit Katinka Busund, Giske Ursin, Eiliv Lund, Sairah Lai Fa Chen, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4912071/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Nov, 2024 Read the published version in Breast Cancer Research → Version 1 posted 11 You are reading this latest preprint version Abstract Background: Menopausal hormone therapy (MHT) is associated with an increased risk of postmenopausal breast cancer, predominantly the luminal A-like subtype. Little is known about the impact of MHT on deaths from breast cancer subtypes. This study aimed to explore associations between MHT use and the incidence, mortality, and survival of intrinsic-like breast cancer subtypes. Methods: Data from 160,881 participants with self-reported MHT use from the prospective Norwegian Women and Cancer Study were analyzed. Among them, 7,844 were incident breast cancer cases, and 721 were breast cancer-specific deaths. Cox proportional hazard regression was performed to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for the association between MHT use and the incidence, mortality, and survival of breast cancer subtypes. Results: MHT use was associated with increased incidence of overall, luminal A-like, and luminal B-like breast cancer, with respective HRs of 1.44 (95% CI: 1.36–1.52), 1.41 (95% CI: 1.31–1.52), and 1.23 (95% CI: 1.09–1.40) among current estrogen-progestin therapy (EPT) users compared with never users. The risk increased by 4%, 4%, and 2% per year of EPT use for overall, luminal A-like, and luminal B-like breast cancers, respectively. Increased risk of overall and luminal A-like breast cancer mortality was also associated with MHT use, with 61% (95% CI: 1.36–1.91) and 115% (95% CI: 1.51–3.05) increased risk among current EPT users compared with non-users. Among patients with breast cancer, pre-diagnostic MHT use was not associated with overall breast cancer survival but was inversely associated with survival from triple-negative breast cancer (TNBC; HR, 0.41; 95% CI: 0.24–0.73 among current users). Results varied significantly according to tumor subtype ( p heterogeneity = 0.02). Conclusions: Our study suggests that MHT use increases the risk of incident and fatal overall, luminal A-like, and incident luminal B-like breast cancer but does not decrease overall survival among patients with breast cancer. Further research is needed to elucidate the mechanisms underlying the differential associations between MHT use and breast cancer mortality and survival, and to explore whether MHT use among patients with TNBC is indeed free from harm. menopausal hormone therapy breast cancer subtypes incidence mortality survival Background Breast cancer is a heterogeneous disease with intrinsic molecular tumor subtypes that have different risk factors, tumor characteristics, responses to treatment, and survival outcomes ( 1 – 5 ). These molecular subtypes are commonly cross-classified into a surrogate definition referred to as intrinsic-like subtypes using standard immunohistochemical (IHC) analyses of tumor receptor status ( 6 ). Over the last three decades, numerous studies have identified combined menopausal hormone therapy (MHT) as an important risk factor for postmenopausal breast cancer ( 7 – 14 ). The latest analyses by the Collaborative Group on Hormonal Factors in Breast Cancer found that all types and regimens of MHT, except vaginal estrogens, were associated with increased risk ( 13 ). The risk escalated with longer use, with estrogen-progestin therapy (EPT) posing a higher risk than unopposed estrogen therapy (ET) compared with non-use ( 13 ). Many studies have investigated the associations between MHT use and intrinsic-like subtypes of breast cancer. A uniform consensus that MHT use is associated with luminal A-like (estrogen receptor (ER)-positive/progesterone receptor (PR)-positive/human epidermal growth factor 2 (HER2)-negative) breast cancer is apparent ( 15 – 21 ), while some studies have indicated a similar association with luminal B-like (ER+/any PR/HER2 + or ER+/PR-/HER2-) subtypes ( 16 , 19 – 21 ). Indications of increased risks of hormone receptor-negative ( 22 ) and triple-negative breast cancer (ER-/PR-/HER2-; TNBC) ( 21 ) associated with MHT have also been reported, although findings regarding MHT use and hormone receptor-negative subtypes, including TNBC and HER2-enriched (ER-/PR-/HER2+), are inconsistent. Contrary to breast cancer incidence, evidence on the impact of MHT use on breast cancer-specific mortality and survival is conflicting. Numerous studies have been published ( 23 – 36 ); however, the results have been ambiguous. Studies examining breast cancer-specific mortality have reported an increased risk of MHT ( 23 , 26 ). Conversely, studies of patients with breast cancer have generally indicated increased survival among MHT users ( 24 , 29 – 33 ). A pooled analysis from the Breast Cancer Association Consortium (BCAC) with 121,435 breast cancer cases and 8,554 breast cancer-specific deaths also demonstrated improved survival among MHT users ( 29 ). Studies assessing the association between pre-diagnostic MHT use and mortality from breast cancer subtypes and subtype-specific survival are sparse. The pooled BCAC analysis found increased survival across all subtypes with EPT and ET formulations ( 29 ). Survival can be influenced by several biases from early detection, typically through cancer screening or high awareness linked to socioeconomic status ( 37 , 38 ). Thus, the importance of interpreting survival in the context of incidence and mortality has been emphasized ( 38 , 39 ). Increased knowledge of the relationship between MHT use and mortality and survival in breast cancer subtypes could be valuable for mitigating risks and prognostication for patients with breast cancer. This study aimed to investigate the associations between MHT use and the incidence, mortality, and survival of intrinsic-like breast cancer subtypes. Methods Study population The Norwegian Women and Cancer (NOWAC) study ( 40 ), initiated in 1991, is a comprehensive, national prospective cohort study designed to explore cancer etiology in Norwegian women. Participants aged 30–70 years were randomly selected from the National Population Register between 1991 and 2008. A total of 172,472 women participated, completing up to three follow-up questionnaires approximately every 6 years. The unique national identification number for all Norwegian residents allows for complete follow-up through linkages to national registries ( 41 ). The NOWAC study has demonstrated considerable external validity; the distribution of risk factors is independent of response rates, and cancer incidence rates align with national data from the Cancer Registry of Norway ( 42 ). From the total cohort of 172,472, we excluded those with missing MHT status at the start of follow-up (n = 2,063), prevalent cancers (other than non-melanoma skin cancer; n = 8,866), participants who had died or emigrated before follow-up (n = 501), and those with extreme values for age at menarche ( 20 years; n = 30), age at menopause ( 60 years; n = 125), and age at first birth ( 50 years; n = 6). Our final study sample comprised 160,881 participants who completed a baseline questionnaire between 1991 and 2008. A flowchart of the study sample is presented in Supplementary Fig. 1 [see Additional file]. For breast cancer survival analyses, we included 7,832 women diagnosed with incident postmenopausal breast cancer between 1991 and 2020, excluding those without breast cancer and 12 who died or emigrated before diagnosis. Exposure and covariates Information on MHT use, including ever use, current use, age at first use, and duration of use, was obtained from questionnaires. Furthermore, MHT was categorized into specific MHT regimens, with participants providing this information via timeline tables and a photo booklet of all available Norwegian MHT brands. We then categorized MHT use into EPT and ET, calculating cumulative estradiol (E2)- and norethisterone (NETA)-equivalent doses. Patients who previously used EPT were excluded from the ET users’ group, leaving a category of patients who had only used unopposed estrogen. MHT status (ever/never, current/former/never) and duration were updated from the follow-up questionnaires to the last non-missing values at start of follow-up. Covariates of interest were extracted from the questionnaires, and the last non-missing value before inclusion was used. We selected covariates of interest a priori and used directed acyclic graphs (DAGs) to depict their assumed causal relationship with exposure and outcome, thereby identifying potential confounding factors adjusted for in the multivariable models ( 43 ). These covariates included age (used as time metric), body mass index (BMI) (continuous), parity (0, 1, 2, ≥ 3), and age at first birth (< 25, 25–29, ≥ 30 years) (combined into one variable), age at menarche (continuous), family history of breast cancer (none, mother and sister, only mother, only sister), physical activity (low, moderate, high), smoking status (current, former, never), and education (< 9, 10–12, 13–16, ≥ 17 years of schooling). Separate DAGs were performed for three outcome variables: overall breast cancer incidence, mortality, and survival (Supplementary Figs. 2–4, respectively) [see Additional file]. Outcome Incident breast cancer cases were identified through links to the Cancer Registry of Norway and classified according to the International Classification of Diseases 10th revision (ICD-10, C50). Breast cancer-specific deaths were identified through the Cause of Death Registry, and emigration status was provided by the Central Population Register. Information on tumor markers, characteristics, and mammography screening was obtained from the Cancer Registry of Norway. The registry routinely extracts information on ER and PR status from pathology reports. Receptor status was assessed using IHC by nationwide pathological departments. Before January 2012, ER-negative tumors were defined using a threshold of < 10% reactivity. Owing to alterations in the national treatment guidelines since February 2012, the threshold shifted to < 1% reactivity. This study employed these cutoff points. HER2 status was ascertained using IHC and/or in situ hybridization (ISH) techniques. Tumors exhibiting no or weak immunostaining were classified as HER2-negative, while those exhibiting moderate or strong immunostaining were classified as HER2-positive. ISH was used to verify cases of moderate immunostaining. Finally, molecular subtypes were approximated using the IHC surrogate definition from the St. Gallen 2013 Expert Panel: luminal A-like (ER + PR + HER2-), luminal B-like (ER + PR + HER2- or ER + PR- HER2 + or ER + PR + HER2+), HER2-enriched (ER- PR- HER2+), and triple-negative (ER- PR- HER2-) ( 6 ). The Cancer Registry of Norway is estimated to be 98.8% complete ( 44 ). Menopausal status Participants were considered postmenopausal if their menstrual period had stopped naturally or surgically by bilateral oopherectomy. Those with unknown menopausal age, who reported irregular menses, hysterectomy, or MHT use, were considered postmenopausal at age 53. This cutoff was used to maintain consistency with the Million Women Study convention ( 7 ), and previous NOWAC publications ( 45 , 46 ). For current smokers, this age was adjusted to 51 years, as smoking can reduce the menopausal age by approximately 2 years ( 47 ). Follow-up For incidence and mortality analyses, follow-up began at the date of the baseline questionnaire for postmenopausal participants. If menopause occurred later, follow-up began at the age of menopause, age at MHT initiation, or age 53 (51 for smokers). MHT use at study entry refers to the last questionnaire completed before inclusion in the regression analysis. Exit time was defined as the date of cancer diagnosis, death, emigration, or end of follow-up, whichever occurred first. For breast cancer survival analyses, follow-up was from diagnosis until death, emigration, or end of follow-up. Participants were censored at 10 years post-diagnosis to retrieve the 10-year risk of death among patients with breast cancer as a measure of survival. The NOWAC cohort is linked to the Central Population Register and the Cause of Death Registry, providing annual endpoint information, including the date of death, emigration, and cause of death. The cause and date of death were updated until April 30, 2022, and breast cancer incidence updated until December 31, 2020. Statistical analyses Cox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between MHT use and the incidence, mortality, and survival of overall and intrinsic-like breast cancer subtypes, using age as the underlying time scale. Distinct regression models were fitted for each subtype outcome, censoring patients diagnosed with or dying from a different subtype ( 48 ). The Cox proportional hazard’s assumption was evaluated by graphical inspection of Schoenfeld residuals and survival time ( 49 ). To account for variations in cumulative estrogen and progestin doses due to age differences, regression models included age at enrollment as a stratum variable. A total of 22,434 (14%) participants had missing information on at least one covariate. The percentages of missing covariates are listed in Table 1 . Assuming these variables were missing at random, we performed multiple imputations by chained equations (MICE) to handle the missing data. A MICE model was executed for each subtype outcome (overall breast cancer and intrinsic-like subtypes) within the incidence, mortality, and survival analytical samples. MICE models included all covariates, an MHT variable (never, current, or former use of ETP, ET, or an unknown type), age at study entry, a binary outcome variable, and the Nelson–Aalen cumulative hazard estimator. MICE models were constructed using predictive mean matching for continuous variables (BMI, age at menarche, and age at first birth), ordered logistic regression for ordinal categorical variables (physical activity and education), and multinomial logistic regression for non-ordinal categorical variables (smoking status). Family history of breast cancer and parity were used as auxillary variables. To reduce sampling variability during the imputation process, 20 duplicate datasets were created ( 50 ). The estimates and standard errors in the imputed datasets were combined using Rubin´s rule to account for within- and between-imputation variances ( 51 ). Age-adjusted and complete-case analyses were performed as sensitivity analyses. All p -values were two-sided with a type I error rate of 5%. Heterogeneity across breast cancer subtypes was tested using the Wald test after a duplication method for competing risk analysis ( 52 , 53 ). All statistical analyses were performed using STATA version 17.0 (StataCorp, College Station, TX, USA). Results A total of 160,881 patients were followed for a median of 15.8 years for breast cancer incidence and 18.0 years for breast cancer-specific mortality. Among them, 40,974 (26%) were current MHT users (29,522 EPT and 4,370 ET), 17,849 (11%) were former users (11,256 EPT and 1,260 ET), and 102,058 (63%) had never used MHT at study entry. For the 10-year breast cancer-specific survival estimates, 7,832 patients with incident breast cancer were followed for a median of 8.5 years. Descriptive statistics for the study sample are presented in Table 1 , with case characteristics in Supplementary Tables 1 and 2 [see Additional file]. Notably, MHT users had higher alcohol consumption, higher education, were less likely to smoke, and were more likely to use oral contraceptives than non-users. Table 1 – Descriptives of study sample according to MHT use at study entry MHT use at study entry Never MHT Ever EPT use Ever ET use only 1 Ever unknown type Mean ± SD or n (%) Number of women, n (%) 102,058 (63.4) 40,778 (25.4) 5,630 (3.5) 12,415 (7.7) Invasive breast cancer cases 4,297 (4.1) 2,599 (6.4) 262 (4.7) 686 (5.5) Age at study entry (yrs) 53.9 ± 0.01 53.2 ± 0.03 53.4 ± 0.07 52.6 ± 0.06 Age at menarche (yrs) Missing, n (%) 13.3 ± 0.00 1,797 (1.8) 13.3 ± 0.01 524 (1.3) 13.2 ± 0.02 86 (1.5) 13.3 ± 0.01 259 (2.1) Age at menopause (yrs) Missing, n (%) 49.5 ± 0.02 47,676 (46.7) 49.7 ± 0.03 10,731 (26.3) 46.2 ± 0.08 1,193 (21.2) 48.3 ± 0.06 4,075 (32.8) Age at first birth (yrs) 2 Missing, n (%) 24.2 ± 0.02 49 (0.1) 23.8 ± 0.02 2 (0.0) 23.3 ± 0.06 0 (0.0) 23.4 ± 0.04 0 (0.0) Parity Missing, n (%) 2.3 ± 0.00 0 (0) 2.2 ± 0.01 0 (0) 2.1 ± 0.01 0 (0) 2.3 ± 0.01 0 (0) BMI (kg/m 2 ) Missing, n (%) 24.7 ± 0.01 2,167 (2.1) 24.3 ± 0.02 706 (1.7) 24.7 ± 0.05 119 (2.1) 24.6 ± 0.04 365 (2.9) Alcohol consumption (g/day) Missing, n (%) 3.49 ± 0.02 4,088 (4.0) 4.23 ± 0.03 2,133 (5.2) 4.03 ± 0.07 282 (5.0) 3.46 ± 0.05 845 (6.8) Education, n (%) ≤ 9 yrs 10–12 yrs 13–16 yrs ≥ 17 yrs Missing 22,535 (22.1) 32,513 (31.9) 26,796 (26.3) 14,407 (14.1) 5,807 (5.7) 7,793 (19.1) 13,593 (33.3) 11,070 (27.2) 6,148 (15.1) 2,174 (5.3) 1,108 (19.7) 1,946 (34.6) 1,472 (26.2) 774 (13.8) 330 (5.9) 3,584 (28.9) 3,967 (32.0) 2,586 (20.8) 1,264 (10.2) 1,014 (8.2) Family history of breast cancer, n (%) None Mother and sister Mother Sister Missing 94,481 (92.6) 301 (0.3) 5,176 (5.1) 2,100 (2.1) 0 (0) 37,774 (92.6) 108 (0.3) 1,996 (4.9) 900 (2.2) 0 (0) 5,198 (92.3) 10 (0.2) 301 (5.4) 121 (2.2) 0 (0) 11,491 (92.6) 40 (0.3) 573 (4.6) 311 (2.5) 0 (0) Smoking status, n (%) Never Former Current Missing 37,843 (37.1) 33,783 (33.1) 29,502 (28.9) 930 (0.9) 12,842 (31.5) 15,368 (37.7) 12,358 (30.3) 210 (0.5) 1,870 (33.2) 2,118 (37.6) 1,602 (28.5) 40 (0.7) 3,964 (31.9) 4,099 (33.0) 4,109 (33.1) 243 (2.0) Physical activity, n (%) Low Moderate High Missing 22,411 (22.0) 54,820 (53.7) 17,013 (16.7) 7,814 (7.7) 9,386 (23.0) 22,735 (55.8) 6,507 (16.0) 2,150 (5.3) 1,382 (24.6) 3,053 (54.2) 885 (15.7) 310 (5.5) 3,026 (24.4) 6,001 (48.3) 1,782 (14.4) 1,606 (12.9) Oral contraceptive use, n (%) Never Ever Missing 43,708 (42.8) 54,967 (53.9) 3,383 (3.3) 16,551 (40.6) 23,584 (57.8) 643 (1.6) 2,496 (44.3) 3,015 (53.6) 119 (2.1) 5,466 (44.0) 6,406 (51.6) 543 (4.4) 1 Never EPT users 2 Among parous women Abbreviations: EPT: estrogen-progestin therapy; ET: estrogen therapy; MHT: menopausal hormone therapy; BMI: body mass index Breast cancer incidence Ever and current use of MHT and EPT at study entry was associated with increased risk of overall, luminal A-like, and luminal B-like breast cancer compared with never use (Table 2 ), with associations varying by subtype ( p heterogeneity = 0.02 and 0.04 for current MHT and EPT use, respectively). The highest HR was for the luminal A-like subtype (HR 1.41; 95% CI: 1.31–1.52 for current use). A significant trend for duration of use was observed for the overall, luminal A-like, and luminal B-like subtypes, with HRs increasing by 4%, 4%, and 2% per year of EPT use, respectively. Former EPT and ET use was associated with decreased risk of luminal A-like (HR 0.86; 95% CI: 0.75–0.99) and overall breast cancer (HR 0.68; 95% CI: 0.49–0.94) compared with never use. Increasing associations with the overall, luminal A-like, and luminal B-like subtypes were observed with increasing cumulative estrogen doses. The cumulative progestin dose was associated with overall (HR 1.66; 95% CI: 1.52–1.82), luminal A-like (HR 1.87; 95% CI: 1.65–2.12), luminal B-like (HR 1.60; 95% CI: 1.30–1.97), and HER2-enriched subtypes (HR 1.79; 95% CI: 1.08–2.98) for > 2 g NETA equivalence. High estrogen dose (≥ 5 g) combined with low progestin dose (< 1 g) was associated with a 2-fold increased risk of TNBC (HR 2.23; 95% CI: 1.22–4.09). Supplementary Tables 3 and 4 provide corresponding results for non-imputed, age-adjusted and multivariable-adjusted complete-case analyses [see Additional file] Table 2 – MHT use at study entry and breast cancer incidence by intrinsic-like subtypes Breast cancer overall (n = 7,844) Luminal A-like (n = 3,784) Luminal B-like (n = 1,480) HER2+ (n = 264) TNBC (n = 500) p het 2 n cases HR (95% CI) 1 n cases HR (95% CI) 1 n cases HR (95% CI) 1 n cases HR (95% CI) 1 n cases HR (95% CI) 1 MHT use overall Never use Ever use Current Former Duration < 5 yrs ≥ 5 yrs Per 1 yr 4,297 3,547 2,782 765 2,250 1,243 7,790 Ref. 1.24 (1.18–1.29) 1.35 (1.29–1.42) 0.95 (0.88–1.02) 1.16 (0.10–1.22) 1.40 (1.31–1.49) 1.03 (1.03–1.04) 2,113 1,671 1,310 361 984 656 3,753 Ref. 1.16 (1.10–1.25) 1.32 (1.23–1.41) 0.83 (0.75–0.93) 1.06 (0.98–1.14) 1.37 (1.26–1.50) 1.03 (1.02–1.04) 845 635 464 171 416 212 1,473 Ref. 1.13 (1.02–1.26) 1.17 (1.04–1.31) 1.04 (0.88–1.23) 1.13 (1.00–1.27) 1.15 (0.99–1.34) 1.02 (1.00–1.03) 155 109 77 32 78 30 263 Ref. 1.07 (0.83–1.37) 1.05 (0.80–1.39) 1.12 (0.76–1.64) 1.14 (0.86–1.50) 0.94 (0.63–1.40) 1.00 (0.96–1.04) 297 203 139 64 128 71 496 Ref. 1.03 (0.86–1.23) 0.99 (0.80–1.21) 1.12 (0.85–1.48) 0.97 (0.79–1.20) 1.13 (0.87–1.46) 1.01 (0.98–1.03) 0.51 0.02 0.08 0.04 EPT use Never use Ever use Current Former Duration < 5 yrs ≥ 5 yrs Per 1 yr 4,297 2,599 2,120 479 1,559 1,028 6,884 Ref. 1.32 (1.25–1.38) 1.44 (1.36–1.52) 0.96 (0.87–1.05) 1.22 (1.15–1.29) 1.49 (1.39–1.60) 1.04 (1.03–1.05) 2,113 1,248 1,012 236 688 553 3,354 Ref. 1.26 (1.17–1.35) 1.41 (1.31–1.52) 0.86 (0.75–0.99) 1.11 (1.02–1.22) 1.48 (1.35–1.63) 1.04 (1.03–1.05) 845 464 352 112 288 175 1,308 Ref. 1.19 (1.06–1.34) 1.23 (1.09–1.40) 1.09 (0.89–1.33) 1.18 (1.03–1.35) 1.22 (1.03–1.44) 1.02 (1.01–1.04) 155 82 58 24 56 25 236 Ref. 1.16 (0.88–1.52) 1.09 (0.81–1.49) 1.34 (0.86–2.06) 1.22 (0.89–1.66) 1.01 (0.66–1.54) 1.01 (0.97–1.06) 297 147 107 40 91 55 443 Ref. 1.08 (0.88–1.32) 1.06 (0.85–1.32) 1.13 (0.81–1.57) 1.04 (0.82–1.32) 1.12 (0.84–1.50) 1.01 (0.98–1.04) 0.45 0.04 0.11 0.05 ET use only Never use Ever use Current Former Duration < 5 yrs ≥ 5 yrs Per 1 yr 4,297 262 224 38 164 96 4,557 Ref. 0.96 (0.85–1.09) 1.04 (0.91–1.19) 0.68 (0.49–0.94) 0.97 (0.83–1.13) 0.95 (0.78–1.17) 0.99 (0.97–1.01) 2,113 122 102 20 78 43 2,234 Ref. 0.89 (0.74–1.06) 0.95 (0.78–1.16) 0.65 (0.42–1.01) 0.95 (0.76–1.20) 0.78 (0.58–1.06) 0.98 (0.95–1.01) 845 52 47 5 29 22 896 Ref. 0.97 (0.73–1.29) 1.12 (0.83–1.50) 0.43 (0.18–1.04) 0.90 (0.62–1.30) 1.05 (0.69–1.61) 1.00 (0.96–1.04) 155 12 9 3 8 4 167 Ref. 1.25 (0.69–2.26) 1.18 (0.60–2.32) 1.51 (0.48–4.74) 1.34 (0.66–2.72) 1.13 (0.42–3.05) 0.99 (0.89–1.10) 297 15 12 3 8 7 312 Ref. 0.80 (0.48–1.35) 0.81 (0.45–1.45) 0.76 (0.24–2.37) 0.70 (0.35–1.41) 0.98 (0.46–2.08) 0.98 (0.90–1.06) 0.68 0.68 0.39 0.85 Cumulative dose Never use Estrogen (E2-equivalence) 10 g Progestin (NETA-equivalence) 2 g E2 dose < 5 g NETA dose < 1 g NETA dose ≥ 1 g E2 dose ≥ 5 g NETA dose < 1 g NETA dose ≥ 1 g 4,297 1,999 827 192 1,411 695 608 1,306 439 93 862 Ref. 1.21 (1.15–1.28) 1.36 (1.26–1.47) 1.51 (1.30–1.75) 1.20 (1.13–1.28) 1.36 (1.25–1.47) 1.66 (1.52–1.82) 1.20 (1.14–1.28) 1.47 (1.33–1.63) 1.20 (0.98–1.48) 1.49 (1.38–1.61) 2,113 948 399 103 634 361 304 589 233 40 431 Ref. 1.23 (1.14–1.33) 1.45 (1.29–1.62) 1.79 (1.46–2.18) 1.16 (1.06–1.27) 1.55 (1.38–1.74) 1.87 (1.65–2.12) 1.16 (1.06–1.27) 1.73 (1.51–1.98) 1.14 (0.84–1.57) 1.66 (1.48–1.84) 845 347 154 34 257 112 107 237 66 18 153 Ref. 1.13 (1.00–1.29) 1.39 (1.16–1.66) 1.46 (1.03–2.07) 1.18 (1.02–1.36) 1.19 (0.97–1.45) 1.60 (1.30–1.97) 1.17 (1.01–1.35) 1.20 (0.93–1.55) 1.29 (0.80–2.05) 1.44 (1.20–1.72) 155 69 22 5 46 18 18 43 12 3 23 Ref. 1.29 (0.97–1.74) 1.24 (0.78–1.97) 1.39 (0.57–3.43) 1.19 (0.85–1.66) 1.18 (0.72–1.95) 1.79 (1.08–2.98) 1.20 (0.85–1.69) 1.36 (0.75–2.48) 1.30 (0.41–4.09) 1.39 (0.88–2.19) 297 112 48 6 92 33 24 79 18 11 39 Ref. 1.01 (0.81–1.27) 1.21 (0.88–1.66) 0.74 (0.33–1.66) 1.18 (0.93–1.50) 0.99 (0.68–1.43) 1.02 (0.66–1.56) 1.09 (0.85–1.41) 0.93 (0.57–1.50) 2.23 (1.22–4.09) 1.04 (0.74–1.48) 0.49 0.66 0.19 0.97 0.04 0.09 0.98 0.03 0.27 0.09 1 Adjusted for BMI, parity, age at first birth, age at menarche, family history, smoking, physical activity, education 2 p heterogeneity between intrinsic-like subtypes; Wald test by competing risks analysis Abbreviations: CI: confidence interval; ET: estrogen therapy; EPT: estrogen-progestin therapy; E2: estradiol; HER2: human epidermal growth factor receptor 2; HR: hazard ratio; MHT: menopausal hormone therapy; NETA: norethisterone acetate; TNBC: triple-negative breast cancer Breast cancer mortality Ever (HR 1.74; 95% CI: 1.24–2.44) and current use (HR 2.15; 95% CI: 1.51–3.05) of EPT at study entry were associated with increased risk of dying from luminal A-like breast cancer (Table 3 ). Table 3 – MHT use at study entry and breast cancer-specific mortality by intrinsic-like subtypes Breast cancer overall (n = 721) Luminal A-like (n = 163) Luminal B-like (n = 113) HER2-enriched (n = 33) TNBC (n = 81) p het 2 n HR (95% CI) 1 n HR (95% CI) 1 n HR (95% CI) 1 n HR (95% CI) 1 n HR (95% CI) 1 MHT use overall Never use Ever use Current Former Duration < 5 yrs ≥ 5 yrs Per 1 yr 392 329 268 61 220 104 716 Ref. 1.27 (1.09–1.47) 1.48 (1.26–1.73) 0.78 (0.60–1.03) 1.29 (1.09–1.53) 1.22 (0.98–1.52) 1.02 (1.00–1.04) 82 81 65 16 43 35 160 Ref. 1.52 (1.11–2.07) 1.82 (1.31–2.54) 0.91 (0.53–1.56) 1.28 (0.88–1.86) 1.86 (1.24–2.78) 1.06 (1.02–1.09) 64 49 39 10 31 17 112 Ref. 1.11 (0.76–1.61) 1.29 (0.86–1.94) 0.71 (0.36–1.39) 1.10 (0.71–1.69) 1.08 (0.63–1.86) 1.01 (0.96–1.06) 20 13 13 0 10 3 33 Ref. 1.00 (0.49–2.04) 1.43 (0.70–2.94) - 1.15 (0.53–2.50) 0.73 (0.11–1.49) 0.95 (0.83–1.09) 54 27 16 11 16 11 81 Ref. 0.72 (0.45–1.15) 0.60 (0.34–1.06) 1.01 (0.52–1.94) 0.65 (0.37–1.15) 0.89 (0.46–1.72) 0.98 (0.92–1.06) 0.10 0.03 0.80 0.13 ETP use Never use Ever use Current Former Duration < 5 yrs ≥ 5 yrs Per 1 yr 392 237 208 29 152 84 628 Ref. 1.35 (1.14–1.59) 1.61 (1.36–1.91) 0.62 (0.43–0.91) 1.38 (1.14–1.67) 1.28 (1.01–1.62) 1.02 (1.00–1.05) 82 62 54 8 30 31 143 Ref. 1.74 (1.24–2.44) 2.15 (1.51–3.05) 0.77 (0.37–1.60) 1.42 (0.93–2.18) 2.16 (1.42–3.29) 1.07 (1.04–1.11) 64 37 31 6 23 14 101 Ref. 1.23 (0.81–1.86) 1.44 (0.93–2.22) 0.71 (0.30–1.64) 1.27 (0.78–2.05) 1.15 (0.64–2.08) 1.02 (0.97–1.08) 20 11 11 0 9 2 31 Ref. 1.25 (0.59–2.64) 1.70 (0.80–3.62) - 1.60 (0.72–3.59) 0.63 (0.15–2.73) 0.95 (0.82–1.10) 54 20 14 6 11 9 74 Ref. 0.78 (0.46–1.31) 0.74 (0.41–1.33) 0.90 (0.38–2.11) 0.69 (0.36–1.32) 0.94 (0.46–1.92) 0.99 (0.92–1.07) 0.13 0.05 0.94 0.10 1 Adjusted for BMI, parity, age at first birth, age at menarche, family history, smoking, physical activity, education 2 p heterogeneity between intrinsic-like subtypes; Wald test by competing risks analysis Abbreviations: CI: confidence interval; ETP: estrogen-progestin therapy; HER2: human epidermal growth factor receptor 2; HR: hazard ratio; MHT: menopausal hormone therapy; TNBC: triple-negative breast cancer The association with breast cancer mortality increased by 2% per year of EPT use, and ≥ 5 years of EPT use was associated with a 2-fold risk of dying from luminal A-like breast cancer (HR 2.16; 95% CI: 1.42–3.29). No association was observed between MHT use and luminal B-like, HER2-enriched, or TNBC mortality. Relationships between current MHT use and breast cancer mortality varied across intrinsic-like subtypes ( p heterogeneity = 0.03). Complete-case analysis results are presented in Supplementary Table 5 [see Additional file]. Breast cancer survival Among patients with breast cancer, MHT use was statistically non-significantly associated with increased risk of death from luminal A-like cancer, thus lower 10-year survival compared with non-users (Table 4 ; HR death 1.36; 95% CI: 0.94–1.99 for current EPT use at study entry). Table 4 – MHT use at study entry and 10-year survival by intrinsic-like subtypes Breast cancer overall (n = 634) Luminal A-like (n = 148) Luminal B-like (n = 104) HER2+ (n = 32) TNBC (n = 81) p het 3 n HR (95% CI) 1,2 n HR (95% CI) 1,2 n HR (95% CI) 1,2 n HR (95% CI) 1,2 n HR (95% CI) 1,2 MHT use overall Never use Ever use Current Former Duration < 5 yrs ≥ 5 yrs Per 1 yr 356 278 226 52 181 93 630 Ref. 0.95 (0.81–1.11) 0.97 (0.82–1.15) 0.85 (0.63–1.13) 0.95 (0.79–1.14) 0.94 (0.74–1.18) 0.99 (0.97–1.02) 76 72 58 14 38 32 146 Ref. 1.20 (0.86–1.67) 1.28 (0.90–1.82) 0.95 (0.53–1.68) 1.04 (0.70–1.54) 1.43 (0.93–2.19) 1.03 (0.99–1.07) 62 42 32 10 26 15 103 Ref. 0.78 (0.52–1.17) 0.77 (0.50–1.19) 0.82 (0.42–1.62) 0.78 (0.49–1.25) 0.74 (0.42–1.32) 0.98 (0.92–1.04) 19 13 13 0 10 3 32 Ref. 0.90 (0.44–1.86) 1.14 (0.55–2.35) - 1.05 (0.48–2.29) 0.65 (0.19–2.24) 0.93 (0.81–1.07) 54 27 16 11 16 11 81 Ref. 0.56 (0.35–0.90) 0.41 (0.24–0.73) 1.13 (0.59–2.20) 0.52 (0.30–0.92) 0.66 (0.34–1.28) 0.95 (0.88–1.03) 0.10 0.02 0.78 0.12 ETP use Never use Ever use Current Former Duration < 5 yrs ≥ 5 yrs Per 1 yr 356 201 175 26 126 74 556 Ref. 0.94 (0.79–1.12) 0.99 (0.82–1.19) 0.70 (0.47–1.05) 0.97 (0.79–1.19) 0.90 (0.70–1.16) 0.99 (0.96–1.02) 76 54 47 7 25 28 129 Ref. 1.24 (0.86–1.77) 1.36 (0.94–1.99) 0.77 (0.35–1.67) 1.00 (0.63–1.58) 1.53 (0.98–2.39) 1.04 (1.00–1.09) 62 31 25 6 19 12 93 Ref. 0.78 (0.50–1.22) 0.78 (0.49–1.26) 0.79 (0.34–1.85) 0.83 (0.49–1.40) 0.71 (0.38–1.33) 0.98 (0.92–1.04) 19 11 11 0 9 2 30 Ref. 1.06 (0.49–2.26) 1.27 (0.59–2.72) - 1.38 (0.61–3.09) 0.52 (0.12–2.27) 0.93 (0.79–1.08) 54 20 14 6 11 9 74 Ref. 0.57 (0.34–0.96) 0.48 (0.26–0.87) 1.03 (0.44–2.44) 0.52 (0.27–1.01) 0.65 (0.32–1.34) 0.95 (0.88–1.03) 0.14 0.05 0.92 0.08 1 HRs of breast-cancer specific death 2 Adjusted for BMI, parity, age at first birth, age at menarche, family history, smoking, physical activity, education 3 p heterogeneity between intrinsic-like subtypes; Wald test by competing risks analysis Abbreviations: CI: confidence interval; ETP: estrogen-progestin therapy; HER2: human epidermal growth factor receptor 2; HR: hazard ratio; MHT: menopausal hormone therapy; TNBC: triple-negative breast cancer Similarly, the duration of EPT use at study entry was associated with an increased risk of death from luminal A-like breast cancer (HR death 1.04; 95% CI: 1.00–1.09 per year increment). Ever (HR death 0.57; 95% CI: 0.34–0.96) and current use (HR death 0.48; 95% CI: 0.26–0.87) of EPT at study entry was associated with decreased risk of dying from TNBC compared with never users. Moreover, current MHT use was differentially associated with survival by intrinsic-like subtypes ( p heterogeneity = 0.02). Complete-case analysis findings are presented in Supplementary Table 6 [see Additional file]. Discussion In this prospective cohort study with 160,881 participants, 7,844 incident breast cancer cases, and 721 breast cancer-specific deaths, MHT use was associated with increased risks of incident and fatal overall and luminal A-like breast cancers. Longer duration of use and higher cumulative doses of estrogen and progestin at study entry were associated with higher risks of overall, luminal A-like, and luminal B-like breast cancers, indicating a dose-response relationship. We observed differences in risk based on recency, where the strongest HRs were observed with current use at study entry. Despite positive associations between MHT use and breast cancer incidence and mortality, we found little evidence that pre-diagnostic MHT use was associated with a higher risk of death from breast cancer among patients with breast cancer. Although based on small numbers, there were indications that MHT and EPT use at study entry was associated with a decreased risk of breast cancer-specific death among patients with TNBC. This study provides insights into the nuanced effects of MHT on etiology and progression of breast cancer subtypes. Our findings on breast cancer incidence align with the empirically grounded consensus that MHT increases breast cancer risk ( 13 , 21 ), with effect estimates among current users similar to those of large, prospective studies ( 9 , 12 , 21 ). Consistent with previous reports, past use was not associated with increased risk of incident or fatal disease ( 7 ). Moreover, the association with an increased risk of luminal subtypes is also reflected in previous studies ( 16 , 17 , 19 , 21 ). We did not observe any association between general MHT use and HER2-enriched or TNBC subtypes, consistent with several studies ( 16 , 17 , 19 ). However, we observed an association between high cumulative estrogen combined with low cumulative progestin dose and incident TNBC, and increasing cumulative progestin dose and incident HER2-enriched breast cancer. These results are based on small numbers and should be interpreted cautiously. Our results predominantly did not suggest any associations with ET use. The findings on overall breast cancer mortality and survival reflect those reported in existing literature. Our results align with reports that MHT is associated with an increased risk of death from breast cancer ( 23 , 25 , 26 , 54 ). In contrast, and in agreement with previous publications, pre-diagnostic MHT use at study entry was not associated with an increased risk of death from overall breast cancer among patients with breast cancer, with some indication of inverse associations, though statistically insignificant, as previous studies have disclosed ( 24 , 29 – 33 , 35 ). Notably, our analyses of mortality and survival, particularly for hormone receptor-negative subtypes, were restricted by low statistical power and should be interpreted accordingly. Controlling for mammography screening in analyses of breast cancer survival and mortality has been advocated ( 25 , 26 ), as MHT users undergo mammography more frequently than non-users ( 55 , 56 ) and screen-detected cancers tend to be of more favorable grade, early stage, and hormone receptor-positive ( 55 , 57 , 58 ). The increased survival observed in previous studies could be attributed to mammography screening, producing lead-time bias due to early detection and length bias owing to the identification of slow-growing tumors. However, increased survival has been reported in studies both controlling for mammography ( 31 – 33 ) and those that did not ( 24 , 29 ). Furthermore, it has been argued that increased survival associated with MHT use is not explained by mammographic surveillance but by biological mechanisms ( 33 ). We chose not to adjust for mammographic screening in our analysis, as we do not consider it a confounder, but rather a possible intermediate variable in the causal pathway between MHT use and breast cancer subtypes. However, differences in health-seeking behaviors and screening attendance could be related to socioeconomic status ( 59 ), affecting MHT use ( 60 ) and survival rates. Therefore, we adjusted for educational level. We did not adjust for stage or treatment, as these factors do not temporally precede pre-diagnostic MHT use or subtype diagnosis and thus do not qualify as confounding factors. Evidence supporting a biological chronology in which the molecular subtype precedes tumor characteristics, such as stage, is found in studies where intrinsic-like subtypes have been assessed in pre-cancerous lesions ( 61 , 62 ). Several factors could explain the opposing results on overall breast cancer mortality and survival observed in our results, as in previous literature. Studies on breast cancer survival begin follow-up at breast cancer diagnosis and tend to adjust for stage, tumor characteristics, and/or treatment ( 24 , 29 , 31 – 33 ), whereas mortality studies begin follow-up at study entry and typically adjust for traditional breast cancer risk factors ( 23 , 26 ). Despite similar adjustments, we observed divergent effect estimates for overall breast cancer. One explanation for this result may be the presence of collider bias, introduced when conditioning on an intermediate variable between the exposure and outcome, coupled with unmeasured confounding factors affecting the mediator’s impact on the outcome ( 63 ). In our scenario, a cancer or subtype-specific cancer diagnosis is an intermediate variable between MHT use and breast cancer survival, and genetic susceptibility to breast cancer represents unmeasured confounding for the effect of a subtype diagnosis and death from breast cancer ( 64 , 65 ). We considered this by adjusting for a family history of breast cancer, a surrogate variable for genetic susceptibility. However, we cannot completely rule out residual confounding and selection biases. Hence, these results must be interpreted without drawing causal conclusions. Our findings indicated a reduced HR of death among patients with TNBC who were MHT users pre-diagnosis. The BCAC pooled analysis also demonstrated increased survival among patients with TNBC, with an HR of 0.64 (95% CI: 0.48–0.85) of death from TNBC among current EPT users ( 29 ). However, unlike this study, they revealed similar effect estimates for all subtypes and did not detect heterogeneity by intrinsic-like subtypes. One study demonstrated an increased risk of incident TNBC with current MHT use ( 21 ), aligning with our finding of an association between high cumulative estrogen combined with low cumulative progestin intake and incident TNBC. Potential biological mechanisms linking estrogen and progestin to TNBC include alternative ER/PR pathways, receptor conversion, alternative estrogen-binding receptors, and paracrine pathways ( 66 ). However, the direction of these effects remain unclear. Although several possible mechanisms exist by which MHT use could exert inverse associations in triple-negative tumor initiation and progression, cautious interpretation of these results is warranted. Our study has some limitations. First, we were limited by small numbers, particularly in the analyses of mortality and survival of the less common receptor-negative subtypes. This was partly due to missing data on receptor status and the small number of breast cancer-specific deaths. We chose not to perform multiple imputations on receptor status because imputing outcome data is a subject of controversy ( 67 ). Second, we used self-reported information on MHT use and covariates. Although a potential for misclassification exists, a validation study on MHT use in the NOWAC cohort demonstrated valid information on current MHT use at baseline and menopausal status among women aged 48–62 ( 46 ). Third, multiple imputations were performed on missing covariate data under the assumption that these variables were missing at random. Similar effect estimates in sensitivity analyses on complete-case data support the robustness of our assumptions; however, we cannot rule out the possibility that some information was missing not at random; thus, our estimates may not be free from bias. Lastly, as we only had information on the first incident breast cancer subtype, some deaths could have resulted from recurrent subtypes that differed from those identified at the initial diagnosis. Conclusions We have demonstrated that MHT use was associated with a small increased risk of incident and fatal overall and luminal breast cancers. However, the relationship between MHT use and breast cancer survival is complex. While pre-diagnostic MHT use was not associated with overall breast cancer survival, it was associated with increased survival among patients with TNBC. These findings underscore the intricate relationship between MHT and breast cancer outcomes across subtypes. Further research is needed to elucidate the mechanisms behind differential effects on breast cancer mortality and survival associated with MHT use. Abbreviations CI Confidence interval ER Estrogen receptor ET Estrogen therapy EPT Estrogen-progestin therapy HR Hazard ratio HER2 Human epidermal growth factor receptor 2 IHC Immunohistochemistry ISH In situ hybridization MHT Menopausal hormone therapy MICE Multiple imputation by chained equations NETA Norethisterone acetate NOWAC The Norwegian Women and Cancer Study PR Progesterone receptor TNBC Triple-negative breast cancer. Declarations Ethics approval and consent to participate The NOWAC study was approved by the Regional Committees for Medical and Health Research Ethics (REC) and the Norwegian Data Inspectorate. The participants received written information about the study, future linkages to national registers, and invitations to complete a second questionnaire. The return of a completed questionnaire was considered as consent to participate. A second questionnaire was sent to the participants who had agreed to receive one. Consent for publication Not applicable. Competing Interests GU is journal editor at Breast Cancer Research. The remaining authors have no conflicts of interest to declare. Funding No funding was received for conducting this study. Author Contribution MB performed statistical analyses and drafted the manuscript. GU, EL and SC interpreted the results and revised the manuscript. CR supervised the study design, statistical analyses and manuscript preparation. Acknowledgement The authors thank the staff and participants in the NOWAC study for their valuable contributions. 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Estrogen plus progestin and breast cancer incidence and mortality in postmenopausal women. JAMA. 2010;304(15):1684–92. Chlebowski RT, Manson JE, Anderson GL, Cauley JA, Aragaki AK, Stefanick ML, et al. Estrogen plus progestin and breast cancer incidence and mortality in the Women's Health Initiative Observational Study. J Natl Cancer Inst. 2013;105(8):526–35. Manson JE, Aragaki AK, Rossouw JE, Anderson GL, Prentice RL, LaCroix AZ, et al. Menopausal Hormone Therapy and Long-term All-Cause and Cause-Specific Mortality: The Women's Health Initiative Randomized Trials. JAMA. 2017;318(10):927–38. Meurer LN, Lena S. Cancer recurrence and mortality in women using hormone replacement therapy: meta-analysis. J FAM PRACT. 2002;51(12):1056–62. Morra A, Jung AY, Behrens S, Keeman R, Ahearn TU, Anton-Culver H, et al. Breast Cancer Risk Factors and Survival by Tumor Subtype: Pooled Analyses from the Breast Cancer Association Consortium. Cancer Epidemiol Biomarkers Prev. 2021;30(4):623–42. 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The effects of hormone replacement therapy on postmenopausal breast cancer biology and survival. Am J Surg. 2009;197(3):403–7. Yu X, Zhou S, Wang J, Zhang Q, Hou J, Zhu L, et al. Hormone replacement therapy and breast cancer survival: a systematic review and meta-analysis of observational studies. Breast Cancer. 2017;24(5):643–57. Norman SA, Weber AL, Localio AR, Marchbanks PA, Ursin G, Strom BL, et al. Hormone therapy and fatal breast cancer. Pharmacoepidemiol Drug Saf. 2010;19(5):440–7. Dickman PW, Adami HO. Interpreting trends in cancer patient survival. J Intern Med. 2006;260(2):103–17. Cho H, Mariotto AB, Schwartz LM, Luo J, Woloshin S. When do changes in cancer survival mean progress? The insight from population incidence and mortality. JNCI Monogr. 2014;2014(49):187–97. Mariotto AB, Noone AM, Howlader N, Cho H, Keel GE, Garshell J, et al. Cancer survival: an overview of measures, uses, and interpretation. J Natl Cancer Inst Monogr. 2014;2014(49):145–86. Lund E, Dumeaux V, Braaten T, Hjartaker A, Engeset D, Skeie G, et al. Cohort profile: The Norwegian Women and Cancer Study–NOWAC–Kvinner og kreft. Int J Epidemiol. 2008;37(1):36–41. Lunde AS, Lundeborg S, Lettenstrom GS, Thygesen L, Huebner J. The person-number systems of Sweden, Norway, Denmark, and Israel. Vital Health Stat 2. 1980(84):1–59. Lund E, Kumle M, Braaten T, Hjartaker A, Bakken K, Eggen E, et al. External validity in a population-based national prospective study–the Norwegian Women and Cancer Study (NOWAC). Cancer Causes Control. 2003;14(10):1001–8. Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology. 1999;10(1):37–48. Larsen IK, Smastuen M, Johannesen TB, Langmark F, Parkin DM, Bray F, et al. Data quality at the Cancer Registry of Norway: an overview of comparability, completeness, validity and timeliness. Eur J Cancer. 2009;45(7):1218–31. Bakken K, Alsaker E, Eggen AE, Lund E. Hormone replacement therapy and incidence of hormone-dependent cancers in the Norwegian Women and Cancer study. Int J Cancer. 2004;112(1):130–4. Waaseth M, Bakken K, Dumeaux V, Olsen KS, Rylander C, Figenschau Y, et al. Hormone replacement therapy use and plasma levels of sex hormones in the Norwegian Women and Cancer postgenome cohort - a cross-sectional analysis. BMC Womens Health. 2008;8:1. McKinlay SM, Bifano NL, McKinlay JB. Smoking and age at menopause in women. Ann Intern Med. 1985;103(3):350–6. Prentice RL, Kalbfleisch JD, Peterson AV Jr., Flournoy N, Farewell VT, Breslow NE. The analysis of failure times in the presence of competing risks. Biometrics. 1978;34(4):541–54. Schoenfeld D. Partial residuals for the proportional hazards regression model. Biometrika. 1982;69(1):239–41. Sterne JA, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393. Rubin DB. Multiple Imputation after 18 + Years. J Am Stat Assoc. 1996;91(434):473–89. Lunn M, McNeil D. Applying Cox regression to competing risks. Biometrics. 1995;51(2):524–32. Wang M, Spiegelman D, Kuchiba A, Lochhead P, Kim S, Chan AT, et al. Statistical methods for studying disease subtype heterogeneity. Stat Med. 2016;35(5):782–800. Chen WY, Manson JE, Hankinson SE, Rosner B, Holmes MD, Willett WC, et al. Unopposed estrogen therapy and the risk of invasive breast cancer. Arch Intern Med. 2006;166(9):1027–32. Dong W, Berry DA, Bevers TB, Kau SW, Hsu L, Theriault RL, et al. Prognostic role of detection method and its relationship with tumor biomarkers in breast cancer: the university of Texas M.D. Anderson Cancer Center experience. Cancer Epidemiol Biomarkers Prev. 2008;17(5):1096–103. Joffe MM, Byrne C, Colditz GA. Postmenopausal hormone use, screening, and breast cancer: characterization and control of a bias. Epidemiology. 2001;12(4):429–38. Shen Y, Yang Y, Inoue LY, Munsell MF, Miller AB, Berry DA. Role of detection method in predicting breast cancer survival: analysis of randomized screening trials. J Natl Cancer Inst. 2005;97(16):1195–203. Sihto H, Lundin J, Lehtimaki T, Sarlomo-Rikala M, Butzow R, Holli K, et al. Molecular subtypes of breast cancers detected in mammography screening and outside of screening. Clin Cancer Res. 2008;14(13):4103–10. Kregting LM, Olthof EMG, Breekveldt ECH, Aitken CA, Heijnsdijk EAM, Toes-Zoutendijk E, et al. Concurrent participation in breast, cervical, and colorectal cancer screening in the Netherlands. Eur J Cancer. 2022;175:180–6. Finley C, Gregg EW, Solomon LJ, Gay E. Disparities in hormone replacement therapy use by socioeconomic status in a primary care population. J Community Health. 2001;26(1):39–50. Livasy CA, Perou CM, Karaca G, Cowan DW, Maia D, Jackson S, et al. Identification of a basal-like subtype of breast ductal carcinoma in situ. Hum Pathol. 2007;38(2):197–204. Millikan RC, Newman B, Tse CK, Moorman PG, Conway K, Dressler LG, et al. Epidemiology of basal-like breast cancer. Breast Cancer Res Treat. 2008;109(1):123–39. Cole SR, Hernan MA. Fallibility in estimating direct effects. Int J Epidemiol. 2002;31(1):163–5. Hu C, Hart SN, Gnanaolivu R, Huang H, Lee KY, Na J, et al. A Population-Based Study of Genes Previously Implicated in Breast Cancer. N Engl J Med. 2021;384(5):440–51. Breast Cancer Association C, Dorling L, Carvalho S, Allen J, Gonzalez-Neira A, Luccarini C, et al. Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women. N Engl J Med. 2021;384(5):428–39. van Barele M, Heemskerk-Gerritsen BAM, Louwers YV, Vastbinder MB, Martens JWM, Hooning MJ et al. Estrogens and Progestogens in Triple Negative Breast Cancer: Do They Harm? Cancers (Basel). 2021;13(11). Groenwold RH, Donders AR, Roes KC, Harrell FE Jr., Moons KG. Dealing with missing outcome data in randomized trials and observational studies. Am J Epidemiol. 2012;175(3):210–7. Supplementary. tables and figures. Additional. file. Supplementary Table 1. Clinical descriptives of cases. Supplementary Table 2. Descriptives of cases according to MHT use at study entry. Supplementary Table 3. MHT use at study entry and incidence by intrinsic-like subtypes – age-adjusted analyses. Supplementary Table 4. MHT use at study entry and incidence by intrinsic-like subtypes- complete-case, MV-adjusted analyses. Supplementary Table 5. MHT use at study entry and breast cancer-specific mortality by intrinsic-like subtypes – complete-case analyses. Supplementary Table 6. MHT use at study entry and 10-year survival by intrinsic-like subtypes – complete-case analyses. Supplementary Fig. 1. Flow chart of study sample. Supplementary Fig. 2. Directed acyclic graph on the assumed relations between MHT use and incidence of postmenopausal breast cancer. Supplementary Fig. 3. Directed acyclic graph on the assumed relations between MHT use and mortality of postmenopausal breast cancer. Supplementary Fig. 4. Directed acyclic graph on the assumed relations between MHT use and survival of postmenopausal breast cancer. Additional Declarations Competing interest reported. GU is journal editor at Breast Cancer Research. The remaining authors have no conflicts of interest to declare. Supplementary Files Additionalfile.docx Additional file Supplementary Table 1. Clinical descriptives of cases Supplementary Table 2. Descriptives of cases according to MHT use at study entry Supplementary Table 3. MHT use at study entry and incidence by intrinsic-like subtypes – age-adjusted analyses Supplementary Table 4. MHT use at study entry and incidence by intrinsic-like subtypes- complete-case, MV-adjusted analyses Supplementary Table 5. MHT use at study entry and breast cancer-specific mortality by intrinsic-like subtypes – complete-case analyses Supplementary Table 6. MHT use at study entry and 10-year survival by intrinsic-like subtypes – complete-case analyses Supplementary Figure 1. Flow chart of study sample Supplementary Figure 2. Directed acyclic graph on the assumed relations between MHT use and incidence of postmenopausal breast cancer Supplementary Figure 3. Directed acyclic graph on the assumed relations between MHT use and mortality of postmenopausal breast cancer Supplementary Figure 4. Directed acyclic graph on the assumed relations between MHT use and survival of postmenopausal breast cancer Cite Share Download PDF Status: Published Journal Publication published 04 Nov, 2024 Read the published version in Breast Cancer Research → Version 1 posted Editorial decision: Revision requested 06 Sep, 2024 Reviews received at journal 06 Sep, 2024 Reviews received at journal 05 Sep, 2024 Reviews received at journal 05 Sep, 2024 Reviewers agreed at journal 20 Aug, 2024 Reviewers agreed at journal 20 Aug, 2024 Reviewers agreed at journal 20 Aug, 2024 Reviewers invited by journal 19 Aug, 2024 Editor assigned by journal 15 Aug, 2024 Submission checks completed at journal 15 Aug, 2024 First submitted to journal 14 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4912071","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":350560091,"identity":"2aef0dc6-0244-42b4-9da5-ca5352407408","order_by":0,"name":"Marit Katinka Busund","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYJCCAwwMCQwGYCabDQMbUVoOILSkMbARpweh5TADQWt0288+PPyBIY3BXCL9mXRB2fnEPvkGtgcf8GgxO5NuAHRYDoPljBwz6Rnnbie2sTGwG87Ap+VAGsgvFQwGN3LYpHnbwFrYpHnwaTn/DKYF6DDetnNEaLkBtiUHqCXBDKjlADFagLacMUjjsex5Y2zNcy7ZuI0tsU0Sr1/OpzF/qKhIljNnT394m6fMTnZ+8+FjEvhCDAIMGJBdwthAUMMoGAWjYBSMAvwAAPZiR7OgtjvEAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Community Medicine, UiT The Arctic University of Norway","correspondingAuthor":true,"prefix":"","firstName":"Marit","middleName":"Katinka","lastName":"Busund","suffix":""},{"id":350560096,"identity":"3761f296-3558-476e-8072-6f96581f406d","order_by":1,"name":"Giske Ursin","email":"","orcid":"","institution":"Cancer Registry of Norway, Norwegian Institute of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Giske","middleName":"","lastName":"Ursin","suffix":""},{"id":350560097,"identity":"7ee1454f-7183-429a-978f-396761463c3f","order_by":2,"name":"Eiliv Lund","email":"","orcid":"","institution":"Department of Community Medicine, UiT The Arctic University of Norway","correspondingAuthor":false,"prefix":"","firstName":"Eiliv","middleName":"","lastName":"Lund","suffix":""},{"id":350560098,"identity":"f4c08f47-6ede-4fc1-b4a1-dbdb372f2867","order_by":3,"name":"Sairah Lai Fa Chen","email":"","orcid":"","institution":"Department of Community Medicine, UiT The Arctic University of Norway","correspondingAuthor":false,"prefix":"","firstName":"Sairah","middleName":"Lai Fa","lastName":"Chen","suffix":""},{"id":350560099,"identity":"c98dbf1e-7b71-4969-80c5-067958c74727","order_by":4,"name":"Charlotta Rylander","email":"","orcid":"","institution":"Department of Community Medicine, UiT The Arctic University of Norway","correspondingAuthor":false,"prefix":"","firstName":"Charlotta","middleName":"","lastName":"Rylander","suffix":""}],"badges":[],"createdAt":"2024-08-14 08:36:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4912071/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4912071/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13058-024-01897-4","type":"published","date":"2024-11-04T15:58:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68750161,"identity":"260ff997-ae49-4b20-8c52-9e56c64bc365","added_by":"auto","created_at":"2024-11-11 16:11:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1494012,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4912071/v1/153065b5-b72d-4b03-ab31-f6ba1ea5498d.pdf"},{"id":64385032,"identity":"a55ff7c4-c8bf-4695-8fb5-0578c8d35705","added_by":"auto","created_at":"2024-09-12 12:24:00","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":739715,"visible":true,"origin":"","legend":"\u003ch4\u003e\u003cstrong\u003eAdditional file\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eSupplementary Table 1. Clinical descriptives of cases\u003c/p\u003e\n\u003cp\u003eSupplementary Table 2. Descriptives of cases according to MHT use at study entry\u003c/p\u003e\n\u003cp\u003eSupplementary Table 3. MHT use at study entry and incidence by intrinsic-like subtypes – age-adjusted analyses\u003c/p\u003e\n\u003cp\u003eSupplementary Table 4. MHT use at study entry and incidence by intrinsic-like subtypes- complete-case, MV-adjusted analyses\u003c/p\u003e\n\u003cp\u003eSupplementary Table 5. MHT use at study entry and breast cancer-specific mortality by intrinsic-like subtypes – complete-case analyses\u003c/p\u003e\n\u003cp\u003eSupplementary Table 6. MHT use at study entry and 10-year survival by intrinsic-like subtypes – complete-case analyses\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 1. Flow chart of study sample\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 2. Directed acyclic graph on the assumed relations between MHT use and incidence of postmenopausal breast cancer\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 3. Directed acyclic graph on the assumed relations between MHT use and mortality of postmenopausal breast cancer\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 4. Directed acyclic graph on the assumed relations between MHT use and survival of postmenopausal breast cancer\u003c/p\u003e","description":"","filename":"Additionalfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-4912071/v1/cdcd908e8285ab84d384bce4.docx"}],"financialInterests":"Competing interest reported. GU is journal editor at Breast Cancer Research. The remaining authors have no conflicts of interest to declare.","formattedTitle":"Menopausal hormone therapy and incidence, mortality, and survival of breast cancer subtypes: A prospective cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eBreast cancer is a heterogeneous disease with intrinsic molecular tumor subtypes that have different risk factors, tumor characteristics, responses to treatment, and survival outcomes (\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). These molecular subtypes are commonly cross-classified into a surrogate definition referred to as intrinsic-like subtypes using standard immunohistochemical (IHC) analyses of tumor receptor status (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOver the last three decades, numerous studies have identified combined menopausal hormone therapy (MHT) as an important risk factor for postmenopausal breast cancer (\u003cspan additionalcitationids=\"CR8 CR9 CR10 CR11 CR12 CR13\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The latest analyses by the Collaborative Group on Hormonal Factors in Breast Cancer found that all types and regimens of MHT, except vaginal estrogens, were associated with increased risk (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The risk escalated with longer use, with estrogen-progestin therapy (EPT) posing a higher risk than unopposed estrogen therapy (ET) compared with non-use (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Many studies have investigated the associations between MHT use and intrinsic-like subtypes of breast cancer. A uniform consensus that MHT use is associated with luminal A-like (estrogen receptor (ER)-positive/progesterone receptor (PR)-positive/human epidermal growth factor 2 (HER2)-negative) breast cancer is apparent (\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), while some studies have indicated a similar association with luminal B-like (ER+/any PR/HER2\u0026thinsp;+\u0026thinsp;or ER+/PR-/HER2-) subtypes (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Indications of increased risks of hormone receptor-negative (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) and triple-negative breast cancer (ER-/PR-/HER2-; TNBC) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) associated with MHT have also been reported, although findings regarding MHT use and hormone receptor-negative subtypes, including TNBC and HER2-enriched (ER-/PR-/HER2+), are inconsistent.\u003c/p\u003e \u003cp\u003eContrary to breast cancer incidence, evidence on the impact of MHT use on breast cancer-specific mortality and survival is conflicting. Numerous studies have been published (\u003cspan additionalcitationids=\"CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34 CR35\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e); however, the results have been ambiguous. Studies examining breast cancer-specific mortality have reported an increased risk of MHT (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Conversely, studies of patients with breast cancer have generally indicated increased survival among MHT users (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR30 CR31 CR32\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). A pooled analysis from the Breast Cancer Association Consortium (BCAC) with 121,435 breast cancer cases and 8,554 breast cancer-specific deaths also demonstrated improved survival among MHT users (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Studies assessing the association between pre-diagnostic MHT use and mortality from breast cancer subtypes and subtype-specific survival are sparse. The pooled BCAC analysis found increased survival across all subtypes with EPT and ET formulations (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSurvival can be influenced by several biases from early detection, typically through cancer screening or high awareness linked to socioeconomic status (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Thus, the importance of interpreting survival in the context of incidence and mortality has been emphasized (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Increased knowledge of the relationship between MHT use and mortality and survival in breast cancer subtypes could be valuable for mitigating risks and prognostication for patients with breast cancer. This study aimed to investigate the associations between MHT use and the incidence, mortality, and survival of intrinsic-like breast cancer subtypes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eThe Norwegian Women and Cancer (NOWAC) study (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), initiated in 1991, is a comprehensive, national prospective cohort study designed to explore cancer etiology in Norwegian women. Participants aged 30\u0026ndash;70 years were randomly selected from the National Population Register between 1991 and 2008. A total of 172,472 women participated, completing up to three follow-up questionnaires approximately every 6 years. The unique national identification number for all Norwegian residents allows for complete follow-up through linkages to national registries (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). The NOWAC study has demonstrated considerable external validity; the distribution of risk factors is independent of response rates, and cancer incidence rates align with national data from the Cancer Registry of Norway (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom the total cohort of 172,472, we excluded those with missing MHT status at the start of follow-up (n\u0026thinsp;=\u0026thinsp;2,063), prevalent cancers (other than non-melanoma skin cancer; n\u0026thinsp;=\u0026thinsp;8,866), participants who had died or emigrated before follow-up (n\u0026thinsp;=\u0026thinsp;501), and those with extreme values for age at menarche (\u0026lt;\u0026thinsp;8 or \u0026gt;\u0026thinsp;20 years; n\u0026thinsp;=\u0026thinsp;30), age at menopause (\u0026lt;\u0026thinsp;2 5 or \u0026gt;\u0026thinsp;60 years; n\u0026thinsp;=\u0026thinsp;125), and age at first birth (\u0026lt;\u0026thinsp;12 or \u0026gt;\u0026thinsp;50 years; n\u0026thinsp;=\u0026thinsp;6). Our final study sample comprised 160,881 participants who completed a baseline questionnaire between 1991 and 2008. A flowchart of the study sample is presented in Supplementary Fig.\u0026nbsp;1 [see Additional file].\u003c/p\u003e \u003cp\u003eFor breast cancer survival analyses, we included 7,832 women diagnosed with incident postmenopausal breast cancer between 1991 and 2020, excluding those without breast cancer and 12 who died or emigrated before diagnosis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eExposure and covariates\u003c/h2\u003e \u003cp\u003eInformation on MHT use, including ever use, current use, age at first use, and duration of use, was obtained from questionnaires. Furthermore, MHT was categorized into specific MHT regimens, with participants providing this information via timeline tables and a photo booklet of all available Norwegian MHT brands. We then categorized MHT use into EPT and ET, calculating cumulative estradiol (E2)- and norethisterone (NETA)-equivalent doses. Patients who previously used EPT were excluded from the ET users\u0026rsquo; group, leaving a category of patients who had only used unopposed estrogen. MHT status (ever/never, current/former/never) and duration were updated from the follow-up questionnaires to the last non-missing values at start of follow-up.\u003c/p\u003e \u003cp\u003eCovariates of interest were extracted from the questionnaires, and the last non-missing value before inclusion was used. We selected covariates of interest \u003cem\u003ea priori\u003c/em\u003e and used directed acyclic graphs (DAGs) to depict their assumed causal relationship with exposure and outcome, thereby identifying potential confounding factors adjusted for in the multivariable models (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). These covariates included age (used as time metric), body mass index (BMI) (continuous), parity (0, 1, 2, \u0026ge; 3), and age at first birth (\u0026lt;\u0026thinsp;25, 25\u0026ndash;29, \u0026ge; 30 years) (combined into one variable), age at menarche (continuous), family history of breast cancer (none, mother and sister, only mother, only sister), physical activity (low, moderate, high), smoking status (current, former, never), and education (\u0026lt;\u0026thinsp;9, 10\u0026ndash;12, 13\u0026ndash;16, \u0026ge; 17 years of schooling). Separate DAGs were performed for three outcome variables: overall breast cancer incidence, mortality, and survival (Supplementary Figs.\u0026nbsp;2\u0026ndash;4, respectively) [see Additional file].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eOutcome\u003c/h2\u003e \u003cp\u003eIncident breast cancer cases were identified through links to the Cancer Registry of Norway and classified according to the International Classification of Diseases 10th revision (ICD-10, C50). Breast cancer-specific deaths were identified through the Cause of Death Registry, and emigration status was provided by the Central Population Register.\u003c/p\u003e \u003cp\u003eInformation on tumor markers, characteristics, and mammography screening was obtained from the Cancer Registry of Norway. The registry routinely extracts information on ER and PR status from pathology reports. Receptor status was assessed using IHC by nationwide pathological departments. Before January 2012, ER-negative tumors were defined using a threshold of \u0026lt;\u0026thinsp;10% reactivity. Owing to alterations in the national treatment guidelines since February 2012, the threshold shifted to \u0026lt;\u0026thinsp;1% reactivity. This study employed these cutoff points. HER2 status was ascertained using IHC and/or \u003cem\u003ein situ\u003c/em\u003e hybridization (ISH) techniques. Tumors exhibiting no or weak immunostaining were classified as HER2-negative, while those exhibiting moderate or strong immunostaining were classified as HER2-positive. ISH was used to verify cases of moderate immunostaining. Finally, molecular subtypes were approximated using the IHC surrogate definition from the St. Gallen 2013 Expert Panel: luminal A-like (ER\u0026thinsp;+\u0026thinsp;PR\u0026thinsp;+\u0026thinsp;HER2-), luminal B-like (ER\u0026thinsp;+\u0026thinsp;PR\u0026thinsp;+\u0026thinsp;HER2- or ER\u0026thinsp;+\u0026thinsp;PR- HER2\u0026thinsp;+\u0026thinsp;or ER\u0026thinsp;+\u0026thinsp;PR\u0026thinsp;+\u0026thinsp;HER2+), HER2-enriched (ER- PR- HER2+), and triple-negative (ER- PR- HER2-) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The Cancer Registry of Norway is estimated to be 98.8% complete (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMenopausal status\u003c/h2\u003e \u003cp\u003eParticipants were considered postmenopausal if their menstrual period had stopped naturally or surgically by bilateral oopherectomy. Those with unknown menopausal age, who reported irregular menses, hysterectomy, or MHT use, were considered postmenopausal at age 53. This cutoff was used to maintain consistency with the Million Women Study convention (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), and previous NOWAC publications (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). For current smokers, this age was adjusted to 51 years, as smoking can reduce the menopausal age by approximately 2 years (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eFollow-up\u003c/h2\u003e \u003cp\u003eFor incidence and mortality analyses, follow-up began at the date of the baseline questionnaire for postmenopausal participants. If menopause occurred later, follow-up began at the age of menopause, age at MHT initiation, or age 53 (51 for smokers). MHT use at study entry refers to the last questionnaire completed before inclusion in the regression analysis. Exit time was defined as the date of cancer diagnosis, death, emigration, or end of follow-up, whichever occurred first. For breast cancer survival analyses, follow-up was from diagnosis until death, emigration, or end of follow-up. Participants were censored at 10 years post-diagnosis to retrieve the 10-year risk of death among patients with breast cancer as a measure of survival. The NOWAC cohort is linked to the Central Population Register and the Cause of Death Registry, providing annual endpoint information, including the date of death, emigration, and cause of death. The cause and date of death were updated until April 30, 2022, and breast cancer incidence updated until December 31, 2020.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eCox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between MHT use and the incidence, mortality, and survival of overall and intrinsic-like breast cancer subtypes, using age as the underlying time scale. Distinct regression models were fitted for each subtype outcome, censoring patients diagnosed with or dying from a different subtype (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). The Cox proportional hazard\u0026rsquo;s assumption was evaluated by graphical inspection of Schoenfeld residuals and survival time (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). To account for variations in cumulative estrogen and progestin doses due to age differences, regression models included age at enrollment as a stratum variable.\u003c/p\u003e \u003cp\u003eA total of 22,434 (14%) participants had missing information on at least one covariate. The percentages of missing covariates are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Assuming these variables were missing at random, we performed multiple imputations by chained equations (MICE) to handle the missing data. A MICE model was executed for each subtype outcome (overall breast cancer and intrinsic-like subtypes) within the incidence, mortality, and survival analytical samples. MICE models included all covariates, an MHT variable (never, current, or former use of ETP, ET, or an unknown type), age at study entry, a binary outcome variable, and the Nelson\u0026ndash;Aalen cumulative hazard estimator. MICE models were constructed using predictive mean matching for continuous variables (BMI, age at menarche, and age at first birth), ordered logistic regression for ordinal categorical variables (physical activity and education), and multinomial logistic regression for non-ordinal categorical variables (smoking status). Family history of breast cancer and parity were used as auxillary variables. To reduce sampling variability during the imputation process, 20 duplicate datasets were created (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). The estimates and standard errors in the imputed datasets were combined using Rubin\u0026acute;s rule to account for within- and between-imputation variances (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Age-adjusted and complete-case analyses were performed as sensitivity analyses.\u003c/p\u003e \u003cp\u003eAll \u003cem\u003ep\u003c/em\u003e-values were two-sided with a type I error rate of 5%. Heterogeneity across breast cancer subtypes was tested using the Wald test after a duplication method for competing risk analysis (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). All statistical analyses were performed using STATA version 17.0 (StataCorp, College Station, TX, USA).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 160,881 patients were followed for a median of 15.8 years for breast cancer incidence and 18.0 years for breast cancer-specific mortality. Among them, 40,974 (26%) were current MHT users (29,522 EPT and 4,370 ET), 17,849 (11%) were former users (11,256 EPT and 1,260 ET), and 102,058 (63%) had never used MHT at study entry. For the 10-year breast cancer-specific survival estimates, 7,832 patients with incident breast cancer were followed for a median of 8.5 years. Descriptive statistics for the study sample are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with case characteristics in Supplementary Tables\u0026nbsp;1 and 2 [see Additional file]. Notably, MHT users had higher alcohol consumption, higher education, were less likely to smoke, and were more likely to use oral contraceptives than non-users.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Descriptives of study sample according to MHT use at study entry\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eMHT use at study entry\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever MHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEver EPT use\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEver ET use only\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEver unknown type\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eMean \u0026plusmn; SD or n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of women, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102,058 (63.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40,778 (25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,630 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12,415 (7.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvasive breast cancer cases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,297 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,599 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e262 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e686 (5.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at study entry (yrs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.9 \u0026plusmn; 0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.2 \u0026plusmn; 0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.4 \u0026plusmn; 0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.6 \u0026plusmn; 0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at menarche (yrs)\u003c/p\u003e \u003cp\u003eMissing, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.3 \u0026plusmn; 0.00\u003c/p\u003e \u003cp\u003e1,797 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3 \u0026plusmn; 0.01\u003c/p\u003e \u003cp\u003e524 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.2 \u0026plusmn; 0.02\u003c/p\u003e \u003cp\u003e86 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.3 \u0026plusmn; 0.01\u003c/p\u003e \u003cp\u003e259 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at menopause (yrs)\u003c/p\u003e \u003cp\u003eMissing, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.5 \u0026plusmn; 0.02\u003c/p\u003e \u003cp\u003e47,676 (46.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.7 \u0026plusmn; 0.03\u003c/p\u003e \u003cp\u003e10,731 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.2 \u0026plusmn; 0.08\u003c/p\u003e \u003cp\u003e1,193 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.3 \u0026plusmn; 0.06\u003c/p\u003e \u003cp\u003e4,075 (32.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at first birth (yrs)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMissing, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.2 \u0026plusmn; 0.02\u003c/p\u003e \u003cp\u003e49 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.8 \u0026plusmn; 0.02\u003c/p\u003e \u003cp\u003e2 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.3 \u0026plusmn; 0.06\u003c/p\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.4 \u0026plusmn; 0.04\u003c/p\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParity\u003c/p\u003e \u003cp\u003eMissing, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.3 \u0026plusmn; 0.00\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2 \u0026plusmn; 0.01\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1 \u0026plusmn; 0.01\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3 \u0026plusmn; 0.01\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003cp\u003eMissing, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.7 \u0026plusmn; 0.01\u003c/p\u003e \u003cp\u003e2,167 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.3 \u0026plusmn; 0.02\u003c/p\u003e \u003cp\u003e706 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.7 \u0026plusmn; 0.05\u003c/p\u003e \u003cp\u003e119 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.6 \u0026plusmn; 0.04\u003c/p\u003e \u003cp\u003e365 (2.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol consumption (g/day)\u003c/p\u003e \u003cp\u003eMissing, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.49 \u0026plusmn; 0.02\u003c/p\u003e \u003cp\u003e4,088 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.23 \u0026plusmn; 0.03\u003c/p\u003e \u003cp\u003e2,133 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.03 \u0026plusmn; 0.07\u003c/p\u003e \u003cp\u003e282 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.46 \u0026plusmn; 0.05\u003c/p\u003e \u003cp\u003e845 (6.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation, n (%)\u003c/p\u003e \u003cp\u003e\u0026le; 9 yrs\u003c/p\u003e \u003cp\u003e10\u0026ndash;12 yrs\u003c/p\u003e \u003cp\u003e13\u0026ndash;16 yrs\u003c/p\u003e \u003cp\u003e\u0026ge; 17 yrs\u003c/p\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22,535 (22.1)\u003c/p\u003e \u003cp\u003e32,513 (31.9)\u003c/p\u003e \u003cp\u003e26,796 (26.3)\u003c/p\u003e \u003cp\u003e14,407 (14.1)\u003c/p\u003e \u003cp\u003e5,807 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,793 (19.1)\u003c/p\u003e \u003cp\u003e13,593 (33.3)\u003c/p\u003e \u003cp\u003e11,070 (27.2)\u003c/p\u003e \u003cp\u003e6,148 (15.1)\u003c/p\u003e \u003cp\u003e2,174 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,108 (19.7)\u003c/p\u003e \u003cp\u003e1,946 (34.6)\u003c/p\u003e \u003cp\u003e1,472 (26.2)\u003c/p\u003e \u003cp\u003e774 (13.8)\u003c/p\u003e \u003cp\u003e330 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,584 (28.9)\u003c/p\u003e \u003cp\u003e3,967 (32.0)\u003c/p\u003e \u003cp\u003e2,586 (20.8)\u003c/p\u003e \u003cp\u003e1,264 (10.2)\u003c/p\u003e \u003cp\u003e1,014 (8.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history of breast cancer, n (%)\u003c/p\u003e \u003cp\u003eNone\u003c/p\u003e \u003cp\u003eMother and sister\u003c/p\u003e \u003cp\u003eMother\u003c/p\u003e \u003cp\u003eSister\u003c/p\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94,481 (92.6)\u003c/p\u003e \u003cp\u003e301 (0.3)\u003c/p\u003e \u003cp\u003e5,176 (5.1)\u003c/p\u003e \u003cp\u003e2,100 (2.1)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37,774 (92.6)\u003c/p\u003e \u003cp\u003e108 (0.3)\u003c/p\u003e \u003cp\u003e1,996 (4.9)\u003c/p\u003e \u003cp\u003e900 (2.2)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,198 (92.3)\u003c/p\u003e \u003cp\u003e10 (0.2)\u003c/p\u003e \u003cp\u003e301 (5.4)\u003c/p\u003e \u003cp\u003e121 (2.2)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11,491 (92.6)\u003c/p\u003e \u003cp\u003e40 (0.3)\u003c/p\u003e \u003cp\u003e573 (4.6)\u003c/p\u003e \u003cp\u003e311 (2.5)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status, n (%)\u003c/p\u003e \u003cp\u003eNever\u003c/p\u003e \u003cp\u003eFormer\u003c/p\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37,843 (37.1)\u003c/p\u003e \u003cp\u003e33,783 (33.1)\u003c/p\u003e \u003cp\u003e29,502 (28.9)\u003c/p\u003e \u003cp\u003e930 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12,842 (31.5)\u003c/p\u003e \u003cp\u003e15,368 (37.7)\u003c/p\u003e \u003cp\u003e12,358 (30.3)\u003c/p\u003e \u003cp\u003e210 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,870 (33.2)\u003c/p\u003e \u003cp\u003e2,118 (37.6)\u003c/p\u003e \u003cp\u003e1,602 (28.5)\u003c/p\u003e \u003cp\u003e40 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,964 (31.9)\u003c/p\u003e \u003cp\u003e4,099 (33.0)\u003c/p\u003e \u003cp\u003e4,109 (33.1)\u003c/p\u003e \u003cp\u003e243 (2.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical activity, n (%)\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003cp\u003eModerate\u003c/p\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22,411 (22.0)\u003c/p\u003e \u003cp\u003e54,820 (53.7)\u003c/p\u003e \u003cp\u003e17,013 (16.7)\u003c/p\u003e \u003cp\u003e7,814 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,386 (23.0)\u003c/p\u003e \u003cp\u003e22,735 (55.8)\u003c/p\u003e \u003cp\u003e6,507 (16.0)\u003c/p\u003e \u003cp\u003e2,150 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,382 (24.6)\u003c/p\u003e \u003cp\u003e3,053 (54.2)\u003c/p\u003e \u003cp\u003e885 (15.7)\u003c/p\u003e \u003cp\u003e310 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,026 (24.4)\u003c/p\u003e \u003cp\u003e6,001 (48.3)\u003c/p\u003e \u003cp\u003e1,782 (14.4)\u003c/p\u003e \u003cp\u003e1,606 (12.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral contraceptive use, n (%)\u003c/p\u003e \u003cp\u003eNever\u003c/p\u003e \u003cp\u003eEver\u003c/p\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43,708 (42.8)\u003c/p\u003e \u003cp\u003e54,967 (53.9)\u003c/p\u003e \u003cp\u003e3,383 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,551 (40.6)\u003c/p\u003e \u003cp\u003e23,584 (57.8)\u003c/p\u003e \u003cp\u003e643 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,496 (44.3)\u003c/p\u003e \u003cp\u003e3,015 (53.6)\u003c/p\u003e \u003cp\u003e119 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,466 (44.0)\u003c/p\u003e \u003cp\u003e6,406 (51.6)\u003c/p\u003e \u003cp\u003e543 (4.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Never EPT users\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Among parous women\u003c/p\u003e \u003cp\u003eAbbreviations: EPT: estrogen-progestin therapy; ET: estrogen therapy; MHT: menopausal hormone therapy; BMI: body mass index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eBreast cancer incidence\u003c/h2\u003e \u003cp\u003eEver and current use of MHT and EPT at study entry was associated with increased risk of overall, luminal A-like, and luminal B-like breast cancer compared with never use (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with associations varying by subtype (\u003cem\u003ep\u003c/em\u003e\u003csub\u003eheterogeneity\u003c/sub\u003e = 0.02 and 0.04 for current MHT and EPT use, respectively). The highest HR was for the luminal A-like subtype (HR 1.41; 95% CI: 1.31\u0026ndash;1.52 for current use). A significant trend for duration of use was observed for the overall, luminal A-like, and luminal B-like subtypes, with HRs increasing by 4%, 4%, and 2% per year of EPT use, respectively. Former EPT and ET use was associated with decreased risk of luminal A-like (HR 0.86; 95% CI: 0.75\u0026ndash;0.99) and overall breast cancer (HR 0.68; 95% CI: 0.49\u0026ndash;0.94) compared with never use. Increasing associations with the overall, luminal A-like, and luminal B-like subtypes were observed with increasing cumulative estrogen doses. The cumulative progestin dose was associated with overall (HR 1.66; 95% CI: 1.52\u0026ndash;1.82), luminal A-like (HR 1.87; 95% CI: 1.65\u0026ndash;2.12), luminal B-like (HR 1.60; 95% CI: 1.30\u0026ndash;1.97), and HER2-enriched subtypes (HR 1.79; 95% CI: 1.08\u0026ndash;2.98) for \u0026gt;\u0026thinsp;2 g NETA equivalence. High estrogen dose (\u0026ge;\u0026thinsp;5 g) combined with low progestin dose (\u0026lt;\u0026thinsp;1 g) was associated with a 2-fold increased risk of\u003c/p\u003e \u003cp\u003eTNBC (HR 2.23; 95% CI: 1.22\u0026ndash;4.09). Supplementary Tables\u0026nbsp;3 and 4 provide corresponding results for non-imputed, age-adjusted and multivariable-adjusted complete-case analyses [see Additional file]\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003e\u0026ndash; MHT use at study entry and breast cancer incidence by intrinsic-like subtypes\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBreast cancer overall \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;7,844)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eLuminal A-like\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;3,784)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eLuminal B-like\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1,480)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eHER2+\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;264)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eTNBC\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;500)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003ehet\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR (95% CI) \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHR (95% CI) \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003en cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHR (95% CI) \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003en cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHR (95% CI) \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMHT use overall\u003c/p\u003e \u003cp\u003eNever use\u003c/p\u003e \u003cp\u003eEver use\u003c/p\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003cp\u003eFormer\u003c/p\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003ePer 1 yr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,297\u003c/p\u003e \u003cp\u003e3,547\u003c/p\u003e \u003cp\u003e2,782\u003c/p\u003e \u003cp\u003e765\u003c/p\u003e \u003cp\u003e2,250\u003c/p\u003e \u003cp\u003e1,243\u003c/p\u003e \u003cp\u003e7,790\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.24 (1.18\u0026ndash;1.29)\u003c/p\u003e \u003cp\u003e1.35 (1.29\u0026ndash;1.42)\u003c/p\u003e \u003cp\u003e0.95 (0.88\u0026ndash;1.02)\u003c/p\u003e \u003cp\u003e1.16 (0.10\u0026ndash;1.22)\u003c/p\u003e \u003cp\u003e1.40 (1.31\u0026ndash;1.49)\u003c/p\u003e \u003cp\u003e1.03 (1.03\u0026ndash;1.04)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,113\u003c/p\u003e \u003cp\u003e1,671\u003c/p\u003e \u003cp\u003e1,310\u003c/p\u003e \u003cp\u003e361\u003c/p\u003e \u003cp\u003e984\u003c/p\u003e \u003cp\u003e656\u003c/p\u003e \u003cp\u003e3,753\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.16 (1.10\u0026ndash;1.25)\u003c/p\u003e \u003cp\u003e1.32 (1.23\u0026ndash;1.41)\u003c/p\u003e \u003cp\u003e0.83 (0.75\u0026ndash;0.93)\u003c/p\u003e \u003cp\u003e1.06 (0.98\u0026ndash;1.14)\u003c/p\u003e \u003cp\u003e1.37 (1.26\u0026ndash;1.50)\u003c/p\u003e \u003cp\u003e1.03 (1.02\u0026ndash;1.04)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e845\u003c/p\u003e \u003cp\u003e635\u003c/p\u003e \u003cp\u003e464\u003c/p\u003e \u003cp\u003e171\u003c/p\u003e \u003cp\u003e416\u003c/p\u003e \u003cp\u003e212\u003c/p\u003e \u003cp\u003e1,473\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.13 (1.02\u0026ndash;1.26)\u003c/p\u003e \u003cp\u003e1.17 (1.04\u0026ndash;1.31)\u003c/p\u003e \u003cp\u003e1.04 (0.88\u0026ndash;1.23)\u003c/p\u003e \u003cp\u003e1.13 (1.00\u0026ndash;1.27)\u003c/p\u003e \u003cp\u003e1.15 (0.99\u0026ndash;1.34)\u003c/p\u003e \u003cp\u003e1.02 (1.00\u0026ndash;1.03)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e155\u003c/p\u003e \u003cp\u003e109\u003c/p\u003e \u003cp\u003e77\u003c/p\u003e \u003cp\u003e32\u003c/p\u003e \u003cp\u003e78\u003c/p\u003e \u003cp\u003e30\u003c/p\u003e \u003cp\u003e263\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.07 (0.83\u0026ndash;1.37)\u003c/p\u003e \u003cp\u003e1.05 (0.80\u0026ndash;1.39)\u003c/p\u003e \u003cp\u003e1.12 (0.76\u0026ndash;1.64)\u003c/p\u003e \u003cp\u003e1.14 (0.86\u0026ndash;1.50)\u003c/p\u003e \u003cp\u003e0.94 (0.63\u0026ndash;1.40)\u003c/p\u003e \u003cp\u003e1.00 (0.96\u0026ndash;1.04)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e297\u003c/p\u003e \u003cp\u003e203\u003c/p\u003e \u003cp\u003e139\u003c/p\u003e \u003cp\u003e64\u003c/p\u003e \u003cp\u003e128\u003c/p\u003e \u003cp\u003e71\u003c/p\u003e \u003cp\u003e496\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.03 (0.86\u0026ndash;1.23)\u003c/p\u003e \u003cp\u003e0.99 (0.80\u0026ndash;1.21)\u003c/p\u003e \u003cp\u003e1.12 (0.85\u0026ndash;1.48)\u003c/p\u003e \u003cp\u003e0.97 (0.79\u0026ndash;1.20)\u003c/p\u003e \u003cp\u003e1.13 (0.87\u0026ndash;1.46)\u003c/p\u003e \u003cp\u003e1.01 (0.98\u0026ndash;1.03)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003cp\u003e0.02\u003c/p\u003e \u003cp\u003e0.08\u003c/p\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEPT use\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNever use\u003c/p\u003e \u003cp\u003eEver use\u003c/p\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003cp\u003eFormer\u003c/p\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003ePer 1 yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,297\u003c/p\u003e \u003cp\u003e2,599\u003c/p\u003e \u003cp\u003e2,120\u003c/p\u003e \u003cp\u003e479\u003c/p\u003e \u003cp\u003e1,559\u003c/p\u003e \u003cp\u003e1,028\u003c/p\u003e \u003cp\u003e6,884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.32 (1.25\u0026ndash;1.38)\u003c/p\u003e \u003cp\u003e1.44 (1.36\u0026ndash;1.52)\u003c/p\u003e \u003cp\u003e0.96 (0.87\u0026ndash;1.05)\u003c/p\u003e \u003cp\u003e1.22 (1.15\u0026ndash;1.29)\u003c/p\u003e \u003cp\u003e1.49 (1.39\u0026ndash;1.60)\u003c/p\u003e \u003cp\u003e1.04 (1.03\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,113\u003c/p\u003e \u003cp\u003e1,248\u003c/p\u003e \u003cp\u003e1,012\u003c/p\u003e \u003cp\u003e236\u003c/p\u003e \u003cp\u003e688\u003c/p\u003e \u003cp\u003e553\u003c/p\u003e \u003cp\u003e3,354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.26 (1.17\u0026ndash;1.35)\u003c/p\u003e \u003cp\u003e1.41 (1.31\u0026ndash;1.52)\u003c/p\u003e \u003cp\u003e0.86 (0.75\u0026ndash;0.99)\u003c/p\u003e \u003cp\u003e1.11 (1.02\u0026ndash;1.22)\u003c/p\u003e \u003cp\u003e1.48 (1.35\u0026ndash;1.63)\u003c/p\u003e \u003cp\u003e1.04 (1.03\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e845\u003c/p\u003e \u003cp\u003e464\u003c/p\u003e \u003cp\u003e352\u003c/p\u003e \u003cp\u003e112\u003c/p\u003e \u003cp\u003e288\u003c/p\u003e \u003cp\u003e175\u003c/p\u003e \u003cp\u003e1,308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.19 (1.06\u0026ndash;1.34)\u003c/p\u003e \u003cp\u003e1.23 (1.09\u0026ndash;1.40)\u003c/p\u003e \u003cp\u003e1.09 (0.89\u0026ndash;1.33)\u003c/p\u003e \u003cp\u003e1.18 (1.03\u0026ndash;1.35)\u003c/p\u003e \u003cp\u003e1.22 (1.03\u0026ndash;1.44)\u003c/p\u003e \u003cp\u003e1.02 (1.01\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e155\u003c/p\u003e \u003cp\u003e82\u003c/p\u003e \u003cp\u003e58\u003c/p\u003e \u003cp\u003e24\u003c/p\u003e \u003cp\u003e56\u003c/p\u003e \u003cp\u003e25\u003c/p\u003e \u003cp\u003e236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.16 (0.88\u0026ndash;1.52)\u003c/p\u003e \u003cp\u003e1.09 (0.81\u0026ndash;1.49)\u003c/p\u003e \u003cp\u003e1.34 (0.86\u0026ndash;2.06)\u003c/p\u003e \u003cp\u003e1.22 (0.89\u0026ndash;1.66)\u003c/p\u003e \u003cp\u003e1.01 (0.66\u0026ndash;1.54)\u003c/p\u003e \u003cp\u003e1.01 (0.97\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e297\u003c/p\u003e \u003cp\u003e147\u003c/p\u003e \u003cp\u003e107\u003c/p\u003e \u003cp\u003e40\u003c/p\u003e \u003cp\u003e91\u003c/p\u003e \u003cp\u003e55\u003c/p\u003e \u003cp\u003e443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.08 (0.88\u0026ndash;1.32)\u003c/p\u003e \u003cp\u003e1.06 (0.85\u0026ndash;1.32)\u003c/p\u003e \u003cp\u003e1.13 (0.81\u0026ndash;1.57)\u003c/p\u003e \u003cp\u003e1.04 (0.82\u0026ndash;1.32)\u003c/p\u003e \u003cp\u003e1.12 (0.84\u0026ndash;1.50)\u003c/p\u003e \u003cp\u003e1.01 (0.98\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003cp\u003e0.04\u003c/p\u003e \u003cp\u003e0.11\u003c/p\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eET use only\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNever use\u003c/p\u003e \u003cp\u003eEver use\u003c/p\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003cp\u003eFormer\u003c/p\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003ePer 1 yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,297\u003c/p\u003e \u003cp\u003e262\u003c/p\u003e \u003cp\u003e224\u003c/p\u003e \u003cp\u003e38\u003c/p\u003e \u003cp\u003e164\u003c/p\u003e \u003cp\u003e96\u003c/p\u003e \u003cp\u003e4,557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.96 (0.85\u0026ndash;1.09)\u003c/p\u003e \u003cp\u003e1.04 (0.91\u0026ndash;1.19)\u003c/p\u003e \u003cp\u003e0.68 (0.49\u0026ndash;0.94)\u003c/p\u003e \u003cp\u003e0.97 (0.83\u0026ndash;1.13)\u003c/p\u003e \u003cp\u003e0.95 (0.78\u0026ndash;1.17)\u003c/p\u003e \u003cp\u003e0.99 (0.97\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,113\u003c/p\u003e \u003cp\u003e122\u003c/p\u003e \u003cp\u003e102\u003c/p\u003e \u003cp\u003e20\u003c/p\u003e \u003cp\u003e78\u003c/p\u003e \u003cp\u003e43\u003c/p\u003e \u003cp\u003e2,234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.89 (0.74\u0026ndash;1.06)\u003c/p\u003e \u003cp\u003e0.95 (0.78\u0026ndash;1.16)\u003c/p\u003e \u003cp\u003e0.65 (0.42\u0026ndash;1.01)\u003c/p\u003e \u003cp\u003e0.95 (0.76\u0026ndash;1.20)\u003c/p\u003e \u003cp\u003e0.78 (0.58\u0026ndash;1.06)\u003c/p\u003e \u003cp\u003e0.98 (0.95\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e845\u003c/p\u003e \u003cp\u003e52\u003c/p\u003e \u003cp\u003e47\u003c/p\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e29\u003c/p\u003e \u003cp\u003e22\u003c/p\u003e \u003cp\u003e896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.97 (0.73\u0026ndash;1.29)\u003c/p\u003e \u003cp\u003e1.12 (0.83\u0026ndash;1.50)\u003c/p\u003e \u003cp\u003e0.43 (0.18\u0026ndash;1.04)\u003c/p\u003e \u003cp\u003e0.90 (0.62\u0026ndash;1.30)\u003c/p\u003e \u003cp\u003e1.05 (0.69\u0026ndash;1.61)\u003c/p\u003e \u003cp\u003e1.00 (0.96\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e155\u003c/p\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.25 (0.69\u0026ndash;2.26)\u003c/p\u003e \u003cp\u003e1.18 (0.60\u0026ndash;2.32)\u003c/p\u003e \u003cp\u003e1.51 (0.48\u0026ndash;4.74)\u003c/p\u003e \u003cp\u003e1.34 (0.66\u0026ndash;2.72)\u003c/p\u003e \u003cp\u003e1.13 (0.42\u0026ndash;3.05)\u003c/p\u003e \u003cp\u003e0.99 (0.89\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e297\u003c/p\u003e \u003cp\u003e15\u003c/p\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e7\u003c/p\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.80 (0.48\u0026ndash;1.35)\u003c/p\u003e \u003cp\u003e0.81 (0.45\u0026ndash;1.45)\u003c/p\u003e \u003cp\u003e0.76 (0.24\u0026ndash;2.37)\u003c/p\u003e \u003cp\u003e0.70 (0.35\u0026ndash;1.41)\u003c/p\u003e \u003cp\u003e0.98 (0.46\u0026ndash;2.08)\u003c/p\u003e \u003cp\u003e0.98 (0.90\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003cp\u003e0.68\u003c/p\u003e \u003cp\u003e0.39\u003c/p\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCumulative dose\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNever use\u003c/p\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eEstrogen (E2-equivalence)\u003c/span\u003e\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 g\u003c/p\u003e \u003cp\u003e5\u003cb\u003e\u0026ndash;\u003c/b\u003e10 g\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 g\u003c/p\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eProgestin (NETA-equivalence)\u003c/span\u003e\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1 g\u003c/p\u003e \u003cp\u003e1\u003cb\u003e\u0026ndash;\u003c/b\u003e2 g\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 g\u003c/p\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eE2 dose\u0026thinsp;\u0026lt;\u0026thinsp;5 g\u003c/span\u003e\u003c/p\u003e \u003cp\u003eNETA dose\u0026thinsp;\u0026lt;\u0026thinsp;1 g\u003c/p\u003e \u003cp\u003eNETA dose\u0026thinsp;\u0026ge;\u0026thinsp;1 g\u003c/p\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eE2 dose\u0026thinsp;\u0026ge;\u0026thinsp;5 g\u003c/span\u003e\u003c/p\u003e \u003cp\u003eNETA dose\u0026thinsp;\u0026lt;\u0026thinsp;1 g\u003c/p\u003e \u003cp\u003eNETA dose\u0026thinsp;\u0026ge;\u0026thinsp;1 g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,297\u003c/p\u003e \u003cp\u003e1,999\u003c/p\u003e \u003cp\u003e827\u003c/p\u003e \u003cp\u003e192\u003c/p\u003e \u003cp\u003e1,411\u003c/p\u003e \u003cp\u003e695\u003c/p\u003e \u003cp\u003e608\u003c/p\u003e \u003cp\u003e1,306\u003c/p\u003e \u003cp\u003e439\u003c/p\u003e \u003cp\u003e93\u003c/p\u003e \u003cp\u003e862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.21 (1.15\u0026ndash;1.28)\u003c/p\u003e \u003cp\u003e1.36 (1.26\u0026ndash;1.47)\u003c/p\u003e \u003cp\u003e1.51 (1.30\u0026ndash;1.75)\u003c/p\u003e \u003cp\u003e1.20 (1.13\u0026ndash;1.28)\u003c/p\u003e \u003cp\u003e1.36 (1.25\u0026ndash;1.47)\u003c/p\u003e \u003cp\u003e1.66 (1.52\u0026ndash;1.82)\u003c/p\u003e \u003cp\u003e1.20 (1.14\u0026ndash;1.28)\u003c/p\u003e \u003cp\u003e1.47 (1.33\u0026ndash;1.63)\u003c/p\u003e \u003cp\u003e1.20 (0.98\u0026ndash;1.48)\u003c/p\u003e \u003cp\u003e1.49 (1.38\u0026ndash;1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,113\u003c/p\u003e \u003cp\u003e948\u003c/p\u003e \u003cp\u003e399\u003c/p\u003e \u003cp\u003e103\u003c/p\u003e \u003cp\u003e634\u003c/p\u003e \u003cp\u003e361\u003c/p\u003e \u003cp\u003e304\u003c/p\u003e \u003cp\u003e589\u003c/p\u003e \u003cp\u003e233\u003c/p\u003e \u003cp\u003e40\u003c/p\u003e \u003cp\u003e431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.23 (1.14\u0026ndash;1.33)\u003c/p\u003e \u003cp\u003e1.45 (1.29\u0026ndash;1.62)\u003c/p\u003e \u003cp\u003e1.79 (1.46\u0026ndash;2.18)\u003c/p\u003e \u003cp\u003e1.16 (1.06\u0026ndash;1.27)\u003c/p\u003e \u003cp\u003e1.55 (1.38\u0026ndash;1.74)\u003c/p\u003e \u003cp\u003e1.87 (1.65\u0026ndash;2.12)\u003c/p\u003e \u003cp\u003e1.16 (1.06\u0026ndash;1.27)\u003c/p\u003e \u003cp\u003e1.73 (1.51\u0026ndash;1.98)\u003c/p\u003e \u003cp\u003e1.14 (0.84\u0026ndash;1.57)\u003c/p\u003e \u003cp\u003e1.66 (1.48\u0026ndash;1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e845\u003c/p\u003e \u003cp\u003e347\u003c/p\u003e \u003cp\u003e154\u003c/p\u003e \u003cp\u003e34\u003c/p\u003e \u003cp\u003e257\u003c/p\u003e \u003cp\u003e112\u003c/p\u003e \u003cp\u003e107\u003c/p\u003e \u003cp\u003e237\u003c/p\u003e \u003cp\u003e66\u003c/p\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.13 (1.00\u0026ndash;1.29)\u003c/p\u003e \u003cp\u003e1.39 (1.16\u0026ndash;1.66)\u003c/p\u003e \u003cp\u003e1.46 (1.03\u0026ndash;2.07)\u003c/p\u003e \u003cp\u003e1.18 (1.02\u0026ndash;1.36)\u003c/p\u003e \u003cp\u003e1.19 (0.97\u0026ndash;1.45)\u003c/p\u003e \u003cp\u003e1.60 (1.30\u0026ndash;1.97)\u003c/p\u003e \u003cp\u003e1.17 (1.01\u0026ndash;1.35)\u003c/p\u003e \u003cp\u003e1.20 (0.93\u0026ndash;1.55)\u003c/p\u003e \u003cp\u003e1.29 (0.80\u0026ndash;2.05)\u003c/p\u003e \u003cp\u003e1.44 (1.20\u0026ndash;1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e155\u003c/p\u003e \u003cp\u003e69\u003c/p\u003e \u003cp\u003e22\u003c/p\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e46\u003c/p\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e43\u003c/p\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.29 (0.97\u0026ndash;1.74)\u003c/p\u003e \u003cp\u003e1.24 (0.78\u0026ndash;1.97)\u003c/p\u003e \u003cp\u003e1.39 (0.57\u0026ndash;3.43)\u003c/p\u003e \u003cp\u003e1.19 (0.85\u0026ndash;1.66)\u003c/p\u003e \u003cp\u003e1.18 (0.72\u0026ndash;1.95)\u003c/p\u003e \u003cp\u003e1.79 (1.08\u0026ndash;2.98)\u003c/p\u003e \u003cp\u003e1.20 (0.85\u0026ndash;1.69)\u003c/p\u003e \u003cp\u003e1.36 (0.75\u0026ndash;2.48)\u003c/p\u003e \u003cp\u003e1.30 (0.41\u0026ndash;4.09)\u003c/p\u003e \u003cp\u003e1.39 (0.88\u0026ndash;2.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e297\u003c/p\u003e \u003cp\u003e112\u003c/p\u003e \u003cp\u003e48\u003c/p\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e92\u003c/p\u003e \u003cp\u003e33\u003c/p\u003e \u003cp\u003e24\u003c/p\u003e \u003cp\u003e79\u003c/p\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.01 (0.81\u0026ndash;1.27)\u003c/p\u003e \u003cp\u003e1.21 (0.88\u0026ndash;1.66)\u003c/p\u003e \u003cp\u003e0.74 (0.33\u0026ndash;1.66)\u003c/p\u003e \u003cp\u003e1.18 (0.93\u0026ndash;1.50)\u003c/p\u003e \u003cp\u003e0.99 (0.68\u0026ndash;1.43)\u003c/p\u003e \u003cp\u003e1.02 (0.66\u0026ndash;1.56)\u003c/p\u003e \u003cp\u003e1.09 (0.85\u0026ndash;1.41)\u003c/p\u003e \u003cp\u003e0.93 (0.57\u0026ndash;1.50)\u003c/p\u003e \u003cp\u003e2.23 (1.22\u0026ndash;4.09)\u003c/p\u003e \u003cp\u003e1.04 (0.74\u0026ndash;1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003cp\u003e0.66\u003c/p\u003e \u003cp\u003e0.19\u003c/p\u003e \u003cp\u003e0.97\u003c/p\u003e \u003cp\u003e0.04\u003c/p\u003e \u003cp\u003e0.09\u003c/p\u003e \u003cp\u003e0.98\u003c/p\u003e \u003cp\u003e0.03\u003c/p\u003e \u003cp\u003e0.27\u003c/p\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Adjusted for BMI, parity, age at first birth, age at menarche, family history, smoking, physical activity, education\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026nbsp;heterogeneity between intrinsic-like subtypes; Wald test by competing risks analysis\u003c/p\u003e \u003cp\u003eAbbreviations: CI: confidence interval; ET: estrogen therapy; EPT: estrogen-progestin therapy; E2: estradiol; HER2: human epidermal growth factor receptor 2; HR: hazard ratio; MHT: menopausal hormone therapy; NETA: norethisterone acetate; TNBC: triple-negative breast cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBreast cancer mortality\u003c/h2\u003e \u003cp\u003eEver (HR 1.74; 95% CI: 1.24\u0026ndash;2.44) and current use (HR 2.15; 95% CI: 1.51\u0026ndash;3.05) of EPT at study entry were associated with increased risk of dying from luminal A-like breast cancer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003e\u0026ndash; MHT use at study entry and breast cancer-specific mortality by intrinsic-like subtypes\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBreast cancer overall\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;721)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eLuminal A-like\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;163)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eLuminal B-like\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;113)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eHER2-enriched\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eTNBC\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003ehet\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMHT use overall\u003c/p\u003e \u003cp\u003eNever use\u003c/p\u003e \u003cp\u003eEver use\u003c/p\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003cp\u003eFormer\u003c/p\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003ePer 1 yr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e392\u003c/p\u003e \u003cp\u003e329\u003c/p\u003e \u003cp\u003e268\u003c/p\u003e \u003cp\u003e61\u003c/p\u003e \u003cp\u003e220\u003c/p\u003e \u003cp\u003e104\u003c/p\u003e \u003cp\u003e716\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.27 (1.09\u0026ndash;1.47)\u003c/p\u003e \u003cp\u003e1.48 (1.26\u0026ndash;1.73)\u003c/p\u003e \u003cp\u003e0.78 (0.60\u0026ndash;1.03)\u003c/p\u003e \u003cp\u003e1.29 (1.09\u0026ndash;1.53)\u003c/p\u003e \u003cp\u003e1.22 (0.98\u0026ndash;1.52)\u003c/p\u003e \u003cp\u003e1.02 (1.00\u0026ndash;1.04)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82\u003c/p\u003e \u003cp\u003e81\u003c/p\u003e \u003cp\u003e65\u003c/p\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e43\u003c/p\u003e \u003cp\u003e35\u003c/p\u003e \u003cp\u003e160\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.52 (1.11\u0026ndash;2.07)\u003c/p\u003e \u003cp\u003e1.82 (1.31\u0026ndash;2.54)\u003c/p\u003e \u003cp\u003e0.91 (0.53\u0026ndash;1.56)\u003c/p\u003e \u003cp\u003e1.28 (0.88\u0026ndash;1.86)\u003c/p\u003e \u003cp\u003e1.86 (1.24\u0026ndash;2.78)\u003c/p\u003e \u003cp\u003e1.06 (1.02\u0026ndash;1.09)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64\u003c/p\u003e \u003cp\u003e49\u003c/p\u003e \u003cp\u003e39\u003c/p\u003e \u003cp\u003e10\u003c/p\u003e \u003cp\u003e31\u003c/p\u003e \u003cp\u003e17\u003c/p\u003e \u003cp\u003e112\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.11 (0.76\u0026ndash;1.61)\u003c/p\u003e \u003cp\u003e1.29 (0.86\u0026ndash;1.94)\u003c/p\u003e \u003cp\u003e0.71 (0.36\u0026ndash;1.39)\u003c/p\u003e \u003cp\u003e1.10 (0.71\u0026ndash;1.69)\u003c/p\u003e \u003cp\u003e1.08 (0.63\u0026ndash;1.86)\u003c/p\u003e \u003cp\u003e1.01 (0.96\u0026ndash;1.06)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003cp\u003e13\u003c/p\u003e \u003cp\u003e13\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e10\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e33\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.00 (0.49\u0026ndash;2.04)\u003c/p\u003e \u003cp\u003e1.43 (0.70\u0026ndash;2.94)\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e1.15 (0.53\u0026ndash;2.50)\u003c/p\u003e \u003cp\u003e0.73 (0.11\u0026ndash;1.49)\u003c/p\u003e \u003cp\u003e0.95 (0.83\u0026ndash;1.09)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e54\u003c/p\u003e \u003cp\u003e27\u003c/p\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e81\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.72 (0.45\u0026ndash;1.15)\u003c/p\u003e \u003cp\u003e0.60 (0.34\u0026ndash;1.06)\u003c/p\u003e \u003cp\u003e1.01 (0.52\u0026ndash;1.94)\u003c/p\u003e \u003cp\u003e0.65 (0.37\u0026ndash;1.15)\u003c/p\u003e \u003cp\u003e0.89 (0.46\u0026ndash;1.72)\u003c/p\u003e \u003cp\u003e0.98 (0.92\u0026ndash;1.06)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003cp\u003e0.03\u003c/p\u003e \u003cp\u003e0.80\u003c/p\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eETP use\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNever use\u003c/p\u003e \u003cp\u003eEver use\u003c/p\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003cp\u003eFormer\u003c/p\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003ePer 1 yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e392\u003c/p\u003e \u003cp\u003e237\u003c/p\u003e \u003cp\u003e208\u003c/p\u003e \u003cp\u003e29\u003c/p\u003e \u003cp\u003e152\u003c/p\u003e \u003cp\u003e84\u003c/p\u003e \u003cp\u003e628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.35 (1.14\u0026ndash;1.59)\u003c/p\u003e \u003cp\u003e1.61 (1.36\u0026ndash;1.91)\u003c/p\u003e \u003cp\u003e0.62 (0.43\u0026ndash;0.91)\u003c/p\u003e \u003cp\u003e1.38 (1.14\u0026ndash;1.67)\u003c/p\u003e \u003cp\u003e1.28 (1.01\u0026ndash;1.62)\u003c/p\u003e \u003cp\u003e1.02 (1.00\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82\u003c/p\u003e \u003cp\u003e62\u003c/p\u003e \u003cp\u003e54\u003c/p\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e30\u003c/p\u003e \u003cp\u003e31\u003c/p\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.74 (1.24\u0026ndash;2.44)\u003c/p\u003e \u003cp\u003e2.15 (1.51\u0026ndash;3.05)\u003c/p\u003e \u003cp\u003e0.77 (0.37\u0026ndash;1.60)\u003c/p\u003e \u003cp\u003e1.42 (0.93\u0026ndash;2.18)\u003c/p\u003e \u003cp\u003e2.16 (1.42\u0026ndash;3.29)\u003c/p\u003e \u003cp\u003e1.07 (1.04\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64\u003c/p\u003e \u003cp\u003e37\u003c/p\u003e \u003cp\u003e31\u003c/p\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e23\u003c/p\u003e \u003cp\u003e14\u003c/p\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.23 (0.81\u0026ndash;1.86)\u003c/p\u003e \u003cp\u003e1.44 (0.93\u0026ndash;2.22)\u003c/p\u003e \u003cp\u003e0.71 (0.30\u0026ndash;1.64)\u003c/p\u003e \u003cp\u003e1.27 (0.78\u0026ndash;2.05)\u003c/p\u003e \u003cp\u003e1.15 (0.64\u0026ndash;2.08)\u003c/p\u003e \u003cp\u003e1.02 (0.97\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.25 (0.59\u0026ndash;2.64)\u003c/p\u003e \u003cp\u003e1.70 (0.80\u0026ndash;3.62)\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e1.60 (0.72\u0026ndash;3.59)\u003c/p\u003e \u003cp\u003e0.63 (0.15\u0026ndash;2.73)\u003c/p\u003e \u003cp\u003e0.95 (0.82\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e54\u003c/p\u003e \u003cp\u003e20\u003c/p\u003e \u003cp\u003e14\u003c/p\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.78 (0.46\u0026ndash;1.31)\u003c/p\u003e \u003cp\u003e0.74 (0.41\u0026ndash;1.33)\u003c/p\u003e \u003cp\u003e0.90 (0.38\u0026ndash;2.11)\u003c/p\u003e \u003cp\u003e0.69 (0.36\u0026ndash;1.32)\u003c/p\u003e \u003cp\u003e0.94 (0.46\u0026ndash;1.92)\u003c/p\u003e \u003cp\u003e0.99 (0.92\u0026ndash;1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003cp\u003e0.05\u003c/p\u003e \u003cp\u003e0.94\u003c/p\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Adjusted for BMI, parity, age at first birth, age at menarche, family history, smoking, physical activity, education\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026nbsp;heterogeneity between intrinsic-like subtypes; Wald test by competing risks analysis\u003c/p\u003e \u003cp\u003eAbbreviations: CI: confidence interval; ETP: estrogen-progestin therapy; HER2: human epidermal growth factor receptor 2; HR: hazard ratio; MHT: menopausal hormone therapy; TNBC: triple-negative breast cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe association with breast cancer mortality increased by 2% per year of EPT use, and \u0026ge;\u0026thinsp;5 years of EPT use was associated with a 2-fold risk of dying from luminal A-like breast cancer (HR 2.16; 95% CI: 1.42\u0026ndash;3.29). No association was observed between MHT use and luminal B-like, HER2-enriched, or TNBC mortality. Relationships between current MHT use and breast cancer mortality varied across intrinsic-like subtypes (\u003cem\u003ep\u003c/em\u003e\u003csub\u003eheterogeneity\u003c/sub\u003e = 0.03). Complete-case analysis results are presented in Supplementary Table\u0026nbsp;5 [see Additional file].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBreast cancer survival\u003c/h2\u003e \u003cp\u003eAmong patients with breast cancer, MHT use was statistically non-significantly associated with increased risk of death from luminal A-like cancer, thus lower 10-year survival compared with non-users (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e; HR death 1.36; 95% CI: 0.94\u0026ndash;1.99 for current EPT use at study entry).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003e\u0026ndash; MHT use at study entry and 10-year survival by intrinsic-like subtypes\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBreast cancer overall\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;634)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eLuminal A-like\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;148)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eLuminal B-like\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;104)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eHER2+\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eTNBC\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csub\u003ehet\u003c/sub\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1,2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1,2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1,2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1,2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHR (95% CI)\u003csup\u003e1,2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMHT use overall\u003c/p\u003e \u003cp\u003eNever use\u003c/p\u003e \u003cp\u003eEver use\u003c/p\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003cp\u003eFormer\u003c/p\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003ePer 1 yr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e356\u003c/p\u003e \u003cp\u003e278\u003c/p\u003e \u003cp\u003e226\u003c/p\u003e \u003cp\u003e52\u003c/p\u003e \u003cp\u003e181\u003c/p\u003e \u003cp\u003e93\u003c/p\u003e \u003cp\u003e630\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.95 (0.81\u0026ndash;1.11)\u003c/p\u003e \u003cp\u003e0.97 (0.82\u0026ndash;1.15)\u003c/p\u003e \u003cp\u003e0.85 (0.63\u0026ndash;1.13)\u003c/p\u003e \u003cp\u003e0.95 (0.79\u0026ndash;1.14)\u003c/p\u003e \u003cp\u003e0.94 (0.74\u0026ndash;1.18)\u003c/p\u003e \u003cp\u003e0.99 (0.97\u0026ndash;1.02)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76\u003c/p\u003e \u003cp\u003e72\u003c/p\u003e \u003cp\u003e58\u003c/p\u003e \u003cp\u003e14\u003c/p\u003e \u003cp\u003e38\u003c/p\u003e \u003cp\u003e32\u003c/p\u003e \u003cp\u003e146\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.20 (0.86\u0026ndash;1.67)\u003c/p\u003e \u003cp\u003e1.28 (0.90\u0026ndash;1.82)\u003c/p\u003e \u003cp\u003e0.95 (0.53\u0026ndash;1.68)\u003c/p\u003e \u003cp\u003e1.04 (0.70\u0026ndash;1.54)\u003c/p\u003e \u003cp\u003e1.43 (0.93\u0026ndash;2.19)\u003c/p\u003e \u003cp\u003e1.03 (0.99\u0026ndash;1.07)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62\u003c/p\u003e \u003cp\u003e42\u003c/p\u003e \u003cp\u003e32\u003c/p\u003e \u003cp\u003e10\u003c/p\u003e \u003cp\u003e26\u003c/p\u003e \u003cp\u003e15\u003c/p\u003e \u003cp\u003e103\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.78 (0.52\u0026ndash;1.17)\u003c/p\u003e \u003cp\u003e0.77 (0.50\u0026ndash;1.19)\u003c/p\u003e \u003cp\u003e0.82 (0.42\u0026ndash;1.62)\u003c/p\u003e \u003cp\u003e0.78 (0.49\u0026ndash;1.25)\u003c/p\u003e \u003cp\u003e0.74 (0.42\u0026ndash;1.32)\u003c/p\u003e \u003cp\u003e0.98 (0.92\u0026ndash;1.04)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19\u003c/p\u003e \u003cp\u003e13\u003c/p\u003e \u003cp\u003e13\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e10\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e32\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.90 (0.44\u0026ndash;1.86)\u003c/p\u003e \u003cp\u003e1.14 (0.55\u0026ndash;2.35)\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e1.05 (0.48\u0026ndash;2.29)\u003c/p\u003e \u003cp\u003e0.65 (0.19\u0026ndash;2.24)\u003c/p\u003e \u003cp\u003e0.93 (0.81\u0026ndash;1.07)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e54\u003c/p\u003e \u003cp\u003e27\u003c/p\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e81\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.56 (0.35\u0026ndash;0.90)\u003c/p\u003e \u003cp\u003e0.41 (0.24\u0026ndash;0.73)\u003c/p\u003e \u003cp\u003e1.13 (0.59\u0026ndash;2.20)\u003c/p\u003e \u003cp\u003e0.52 (0.30\u0026ndash;0.92)\u003c/p\u003e \u003cp\u003e0.66 (0.34\u0026ndash;1.28)\u003c/p\u003e \u003cp\u003e0.95 (0.88\u0026ndash;1.03)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003cp\u003e0.02\u003c/p\u003e \u003cp\u003e0.78\u003c/p\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eETP use\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNever use\u003c/p\u003e \u003cp\u003eEver use\u003c/p\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003cp\u003eFormer\u003c/p\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5 yrs\u003c/p\u003e \u003cp\u003ePer 1 yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e356\u003c/p\u003e \u003cp\u003e201\u003c/p\u003e \u003cp\u003e175\u003c/p\u003e \u003cp\u003e26\u003c/p\u003e \u003cp\u003e126\u003c/p\u003e \u003cp\u003e74\u003c/p\u003e \u003cp\u003e556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.94 (0.79\u0026ndash;1.12)\u003c/p\u003e \u003cp\u003e0.99 (0.82\u0026ndash;1.19)\u003c/p\u003e \u003cp\u003e0.70 (0.47\u0026ndash;1.05)\u003c/p\u003e \u003cp\u003e0.97 (0.79\u0026ndash;1.19)\u003c/p\u003e \u003cp\u003e0.90 (0.70\u0026ndash;1.16)\u003c/p\u003e \u003cp\u003e0.99 (0.96\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76\u003c/p\u003e \u003cp\u003e54\u003c/p\u003e \u003cp\u003e47\u003c/p\u003e \u003cp\u003e7\u003c/p\u003e \u003cp\u003e25\u003c/p\u003e \u003cp\u003e28\u003c/p\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.24 (0.86\u0026ndash;1.77)\u003c/p\u003e \u003cp\u003e1.36 (0.94\u0026ndash;1.99)\u003c/p\u003e \u003cp\u003e0.77 (0.35\u0026ndash;1.67)\u003c/p\u003e \u003cp\u003e1.00 (0.63\u0026ndash;1.58)\u003c/p\u003e \u003cp\u003e1.53 (0.98\u0026ndash;2.39)\u003c/p\u003e \u003cp\u003e1.04 (1.00\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62\u003c/p\u003e \u003cp\u003e31\u003c/p\u003e \u003cp\u003e25\u003c/p\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e19\u003c/p\u003e \u003cp\u003e12\u003c/p\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.78 (0.50\u0026ndash;1.22)\u003c/p\u003e \u003cp\u003e0.78 (0.49\u0026ndash;1.26)\u003c/p\u003e \u003cp\u003e0.79 (0.34\u0026ndash;1.85)\u003c/p\u003e \u003cp\u003e0.83 (0.49\u0026ndash;1.40)\u003c/p\u003e \u003cp\u003e0.71 (0.38\u0026ndash;1.33)\u003c/p\u003e \u003cp\u003e0.98 (0.92\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e1.06 (0.49\u0026ndash;2.26)\u003c/p\u003e \u003cp\u003e1.27 (0.59\u0026ndash;2.72)\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e1.38 (0.61\u0026ndash;3.09)\u003c/p\u003e \u003cp\u003e0.52 (0.12\u0026ndash;2.27)\u003c/p\u003e \u003cp\u003e0.93 (0.79\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e54\u003c/p\u003e \u003cp\u003e20\u003c/p\u003e \u003cp\u003e14\u003c/p\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003cp\u003e0.57 (0.34\u0026ndash;0.96)\u003c/p\u003e \u003cp\u003e0.48 (0.26\u0026ndash;0.87)\u003c/p\u003e \u003cp\u003e1.03 (0.44\u0026ndash;2.44)\u003c/p\u003e \u003cp\u003e0.52 (0.27\u0026ndash;1.01)\u003c/p\u003e \u003cp\u003e0.65 (0.32\u0026ndash;1.34)\u003c/p\u003e \u003cp\u003e0.95 (0.88\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003cp\u003e0.05\u003c/p\u003e \u003cp\u003e0.92\u003c/p\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003e HRs of breast-cancer specific death\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Adjusted for BMI, parity, age at first birth, age at menarche, family history, smoking, physical activity, education\u003c/p\u003e \u003cp\u003e\u003csup\u003e3\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026nbsp;heterogeneity between intrinsic-like subtypes; Wald test by competing risks analysis\u003c/p\u003e \u003cp\u003eAbbreviations: CI: confidence interval; ETP: estrogen-progestin therapy; HER2: human epidermal growth factor receptor 2; HR: hazard ratio; MHT: menopausal hormone therapy; TNBC: triple-negative breast cancer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSimilarly, the duration of EPT use at study entry was associated with an increased risk of death from luminal A-like breast cancer (HR death 1.04; 95% CI: 1.00\u0026ndash;1.09 per year increment). Ever (HR death 0.57; 95% CI: 0.34\u0026ndash;0.96) and current use (HR death 0.48; 95% CI: 0.26\u0026ndash;0.87) of EPT at study entry was associated with decreased risk of dying from TNBC compared with never users. Moreover, current MHT use was differentially associated with survival by intrinsic-like subtypes (\u003cem\u003ep\u003c/em\u003e\u003csub\u003eheterogeneity\u003c/sub\u003e = 0.02). Complete-case analysis findings are presented in Supplementary Table\u0026nbsp;6 [see Additional file].\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this prospective cohort study with 160,881 participants, 7,844 incident breast cancer cases, and 721 breast cancer-specific deaths, MHT use was associated with increased risks of incident and fatal overall and luminal A-like breast cancers. Longer duration of use and higher cumulative doses of estrogen and progestin at study entry were associated with higher risks of overall, luminal A-like, and luminal B-like breast cancers, indicating a dose-response relationship. We observed differences in risk based on recency, where the strongest HRs were observed with current use at study entry. Despite positive associations between MHT use and breast cancer incidence and mortality, we found little evidence that pre-diagnostic MHT use was associated with a higher risk of death from breast cancer among patients with breast cancer. Although based on small numbers, there were indications that MHT and EPT use at study entry was associated with a decreased risk of breast cancer-specific death among patients with TNBC. This study provides insights into the nuanced effects of MHT on etiology and progression of breast cancer subtypes.\u003c/p\u003e \u003cp\u003eOur findings on breast cancer incidence align with the empirically grounded consensus that MHT increases breast cancer risk (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), with effect estimates among current users similar to those of large, prospective studies (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Consistent with previous reports, past use was not associated with increased risk of incident or fatal disease (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Moreover, the association with an increased risk of luminal subtypes is also reflected in previous studies (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). We did not observe any association between general MHT use and HER2-enriched or TNBC subtypes, consistent with several studies (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). However, we observed an association between high cumulative estrogen combined with low cumulative progestin dose and incident TNBC, and increasing cumulative progestin dose and incident HER2-enriched breast cancer. These results are based on small numbers and should be interpreted cautiously. Our results predominantly did not suggest any associations with ET use.\u003c/p\u003e \u003cp\u003eThe findings on overall breast cancer mortality and survival reflect those reported in existing literature. Our results align with reports that MHT is associated with an increased risk of death from breast cancer (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). In contrast, and in agreement with previous publications, pre-diagnostic MHT use at study entry was not associated with an increased risk of death from overall breast cancer among patients with breast cancer, with some indication of inverse associations, though statistically insignificant, as previous studies have disclosed (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR30 CR31 CR32\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Notably, our analyses of mortality and survival, particularly for hormone receptor-negative subtypes, were restricted by low statistical power and should be interpreted accordingly.\u003c/p\u003e \u003cp\u003eControlling for mammography screening in analyses of breast cancer survival and mortality has been advocated (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), as MHT users undergo mammography more frequently than non-users (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e) and screen-detected cancers tend to be of more favorable grade, early stage, and hormone receptor-positive (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). The increased survival observed in previous studies could be attributed to mammography screening, producing lead-time bias due to early detection and length bias owing to the identification of slow-growing tumors. However, increased survival has been reported in studies both controlling for mammography (\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) and those that did not (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Furthermore, it has been argued that increased survival associated with MHT use is not explained by mammographic surveillance but by biological mechanisms (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). We chose not to adjust for mammographic screening in our analysis, as we do not consider it a confounder, but rather a possible intermediate variable in the causal pathway between MHT use and breast cancer subtypes. However, differences in health-seeking behaviors and screening attendance could be related to socioeconomic status (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e), affecting MHT use (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e) and survival rates. Therefore, we adjusted for educational level. We did not adjust for stage or treatment, as these factors do not temporally precede pre-diagnostic MHT use or subtype diagnosis and thus do not qualify as confounding factors. Evidence supporting a biological chronology in which the molecular subtype precedes tumor characteristics, such as stage, is found in studies where intrinsic-like subtypes have been assessed in pre-cancerous lesions (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral factors could explain the opposing results on overall breast cancer mortality and survival observed in our results, as in previous literature. Studies on breast cancer survival begin follow-up at breast cancer diagnosis and tend to adjust for stage, tumor characteristics, and/or treatment (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), whereas mortality studies begin follow-up at study entry and typically adjust for traditional breast cancer risk factors (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Despite similar adjustments, we observed divergent effect estimates for overall breast cancer. One explanation for this result may be the presence of collider bias, introduced when conditioning on an intermediate variable between the exposure and outcome, coupled with unmeasured confounding factors affecting the mediator\u0026rsquo;s impact on the outcome (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). In our scenario, a cancer or subtype-specific cancer diagnosis is an intermediate variable between MHT use and breast cancer survival, and genetic susceptibility to breast cancer represents unmeasured confounding for the effect of a subtype diagnosis and death from breast cancer (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e). We considered this by adjusting for a family history of breast cancer, a surrogate variable for genetic susceptibility. However, we cannot completely rule out residual confounding and selection biases. Hence, these results must be interpreted without drawing causal conclusions.\u003c/p\u003e \u003cp\u003eOur findings indicated a reduced HR of death among patients with TNBC who were MHT users pre-diagnosis. The BCAC pooled analysis also demonstrated increased survival among patients with TNBC, with an HR of 0.64 (95% CI: 0.48\u0026ndash;0.85) of death from TNBC among current EPT users (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). However, unlike this study, they revealed similar effect estimates for all subtypes and did not detect heterogeneity by intrinsic-like subtypes. One study demonstrated an increased risk of incident TNBC with current MHT use (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), aligning with our finding of an association between high cumulative estrogen combined with low cumulative progestin intake and incident TNBC. Potential biological mechanisms linking estrogen and progestin to TNBC include alternative ER/PR pathways, receptor conversion, alternative estrogen-binding receptors, and paracrine pathways (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e). However, the direction of these effects remain unclear. Although several possible mechanisms exist by which MHT use could exert inverse associations in triple-negative tumor initiation and progression, cautious interpretation of these results is warranted.\u003c/p\u003e \u003cp\u003eOur study has some limitations. First, we were limited by small numbers, particularly in the analyses of mortality and survival of the less common receptor-negative subtypes. This was partly due to missing data on receptor status and the small number of breast cancer-specific deaths. We chose not to perform multiple imputations on receptor status because imputing outcome data is a subject of controversy (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). Second, we used self-reported information on MHT use and covariates. Although a potential for misclassification exists, a validation study on MHT use in the NOWAC cohort demonstrated valid information on current MHT use at baseline and menopausal status among women aged 48\u0026ndash;62 (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Third, multiple imputations were performed on missing covariate data under the assumption that these variables were missing at random. Similar effect estimates in sensitivity analyses on complete-case data support the robustness of our assumptions; however, we cannot rule out the possibility that some information was missing not at random; thus, our estimates may not be free from bias. Lastly, as we only had information on the first incident breast cancer subtype, some deaths could have resulted from recurrent subtypes that differed from those identified at the initial diagnosis.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe have demonstrated that MHT use was associated with a small increased risk of incident and fatal overall and luminal breast cancers. However, the relationship between MHT use and breast cancer survival is complex. While pre-diagnostic MHT use was not associated with overall breast cancer survival, it was associated with increased survival among patients with TNBC. These findings underscore the intricate relationship between MHT and breast cancer outcomes across subtypes. Further research is needed to elucidate the mechanisms behind differential effects on breast cancer mortality and survival associated with MHT use.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eER\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEstrogen receptor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eET\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEstrogen therapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEPT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEstrogen-progestin therapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHazard ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHER2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuman epidermal growth factor receptor 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImmunohistochemistry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eISH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eIn situ\u003c/em\u003e hybridization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMHT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMenopausal hormone therapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMICE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMultiple imputation by chained equations\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNETA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNorethisterone acetate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNOWAC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe Norwegian Women and Cancer Study\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgesterone receptor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTriple-negative breast cancer.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e The NOWAC study was approved by the Regional Committees for Medical and Health Research Ethics (REC) and the Norwegian Data Inspectorate. The participants received written information about the study, future linkages to national registers, and invitations to complete a second questionnaire. The return of a completed questionnaire was considered as consent to participate. A second questionnaire was sent to the participants who had agreed to receive one.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eGU is journal editor at Breast Cancer Research. The remaining authors have no conflicts of interest to declare.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNo funding was received for conducting this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMB performed statistical analyses and drafted the manuscript. GU, EL and SC interpreted the results and revised the manuscript. CR supervised the study design, statistical analyses and manuscript preparation.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank the staff and participants in the NOWAC study for their valuable contributions.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eThe datasets used and/or analyzed in this study are available from the corresponding author upon reasonable request and if legal permissions are in place.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eParise CA, Bauer KR, Brown MM, Caggiano V. Breast cancer subtypes as defined by the estrogen receptor (ER), progesterone receptor (PR), and the human epidermal growth factor receptor 2 (HER2) among women with invasive breast cancer in California, 1999\u0026ndash;2004. 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Clin Cancer Res. 2008;14(13):4103\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKregting LM, Olthof EMG, Breekveldt ECH, Aitken CA, Heijnsdijk EAM, Toes-Zoutendijk E, et al. Concurrent participation in breast, cervical, and colorectal cancer screening in the Netherlands. Eur J Cancer. 2022;175:180\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFinley C, Gregg EW, Solomon LJ, Gay E. Disparities in hormone replacement therapy use by socioeconomic status in a primary care population. J Community Health. 2001;26(1):39\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLivasy CA, Perou CM, Karaca G, Cowan DW, Maia D, Jackson S, et al. Identification of a basal-like subtype of breast ductal carcinoma in situ. Hum Pathol. 2007;38(2):197\u0026ndash;204.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMillikan RC, Newman B, Tse CK, Moorman PG, Conway K, Dressler LG, et al. Epidemiology of basal-like breast cancer. Breast Cancer Res Treat. 2008;109(1):123\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCole SR, Hernan MA. Fallibility in estimating direct effects. Int J Epidemiol. 2002;31(1):163\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu C, Hart SN, Gnanaolivu R, Huang H, Lee KY, Na J, et al. A Population-Based Study of Genes Previously Implicated in Breast Cancer. N Engl J Med. 2021;384(5):440\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBreast Cancer Association C, Dorling L, Carvalho S, Allen J, Gonzalez-Neira A, Luccarini C, et al. Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women. N Engl J Med. 2021;384(5):428\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Barele M, Heemskerk-Gerritsen BAM, Louwers YV, Vastbinder MB, Martens JWM, Hooning MJ et al. Estrogens and Progestogens in Triple Negative Breast Cancer: Do They Harm? Cancers (Basel). 2021;13(11).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGroenwold RH, Donders AR, Roes KC, Harrell FE Jr., Moons KG. Dealing with missing outcome data in randomized trials and observational studies. Am J Epidemiol. 2012;175(3):210\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary. tables and figures.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdditional. file.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary Table 1. Clinical descriptives of cases.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary Table 2. Descriptives of cases according to MHT use at study entry.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary Table 3. MHT use at study entry and incidence by intrinsic-like subtypes \u0026ndash; age-adjusted analyses.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary Table 4. MHT use at study entry and incidence by intrinsic-like subtypes- complete-case, MV-adjusted analyses.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary Table 5. MHT use at study entry and breast cancer-specific mortality by intrinsic-like subtypes \u0026ndash; complete-case analyses.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary Table 6. MHT use at study entry and 10-year survival by intrinsic-like subtypes \u0026ndash; complete-case analyses.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary Fig. 1. Flow chart of study sample.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary Fig. 2. Directed acyclic graph on the assumed relations between MHT use and incidence of postmenopausal breast cancer.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary Fig. 3. Directed acyclic graph on the assumed relations between MHT use and mortality of postmenopausal breast cancer.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplementary Fig. 4. Directed acyclic graph on the assumed relations between MHT use and survival of postmenopausal breast cancer.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"breast-cancer-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brcr","sideBox":"Learn more about [Breast Cancer Research](http://breast-cancer-research.biomedcentral.com)","snPcode":"13058","submissionUrl":"https://submission.nature.com/new-submission/13058/3","title":"Breast Cancer Research","twitterHandle":"@BCRJournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"menopausal hormone therapy, breast cancer subtypes, incidence, mortality, survival","lastPublishedDoi":"10.21203/rs.3.rs-4912071/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4912071/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eMenopausal hormone therapy (MHT) is associated with an increased risk of postmenopausal breast cancer, predominantly the luminal A-like subtype. Little is known about the impact of MHT on deaths from breast cancer subtypes. This study aimed to explore associations between MHT use and the incidence, mortality, and survival of intrinsic-like breast cancer subtypes.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/em\u003e Data from 160,881 participants with self-reported MHT use from the prospective Norwegian Women and Cancer Study were analyzed. Among them, 7,844 were incident breast cancer cases, and 721 were breast cancer-specific deaths. Cox proportional hazard regression was performed to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for the association between MHT use and the incidence, mortality, and survival of breast cancer subtypes.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/em\u003e MHT use was associated with increased incidence of overall, luminal A-like, and luminal B-like breast cancer, with respective HRs of 1.44 (95% CI: 1.36–1.52), 1.41 (95% CI: 1.31–1.52), and 1.23 (95% CI: 1.09–1.40) among current estrogen-progestin therapy (EPT) users compared with never users. The risk increased by 4%, 4%, and 2% per year of EPT use for overall, luminal A-like, and luminal B-like breast cancers, respectively. Increased risk of overall and luminal A-like breast cancer mortality was also associated with MHT use, with 61% (95% CI: 1.36–1.91) and 115% (95% CI: 1.51–3.05) increased risk among current EPT users compared with non-users. Among patients with breast cancer, pre-diagnostic MHT use was not associated with overall breast cancer survival but was inversely associated with survival from triple-negative breast cancer (TNBC; HR, 0.41; 95% CI: 0.24–0.73 among current users). Results varied significantly according to tumor subtype (\u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003eheterogeneity\u003c/em\u003e\u003c/sub\u003e = 0.02).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e\u003c/em\u003e Our study suggests that MHT use increases the risk of incident and fatal overall, luminal A-like, and incident luminal B-like breast cancer but does not decrease overall survival among patients with breast cancer. Further research is needed to elucidate the mechanisms underlying the differential associations between MHT use and breast cancer mortality and survival, and to explore whether MHT use among patients with TNBC is indeed free from harm.\u003c/p\u003e","manuscriptTitle":"Menopausal hormone therapy and incidence, mortality, and survival of breast cancer subtypes: A prospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-12 12:23:55","doi":"10.21203/rs.3.rs-4912071/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-06T14:05:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-06T08:37:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-05T18:01:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-05T10:48:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"147957320495049995430635576133138575347","date":"2024-08-20T16:41:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"77424529041058805381196755019614979639","date":"2024-08-20T11:49:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"327299586010084421118579662475645771842","date":"2024-08-20T09:41:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-19T17:04:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-15T09:53:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-15T06:29:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Breast Cancer Research","date":"2024-08-14T08:34:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"breast-cancer-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brcr","sideBox":"Learn more about [Breast Cancer Research](http://breast-cancer-research.biomedcentral.com)","snPcode":"13058","submissionUrl":"https://submission.nature.com/new-submission/13058/3","title":"Breast Cancer Research","twitterHandle":"@BCRJournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"36967d67-913e-44ab-80b4-77efa8efb209","owner":[],"postedDate":"September 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-11T16:06:27+00:00","versionOfRecord":{"articleIdentity":"rs-4912071","link":"https://doi.org/10.1186/s13058-024-01897-4","journal":{"identity":"breast-cancer-research","isVorOnly":false,"title":"Breast Cancer Research"},"publishedOn":"2024-11-04 15:58:10","publishedOnDateReadable":"November 4th, 2024"},"versionCreatedAt":"2024-09-12 12:23:55","video":"","vorDoi":"10.1186/s13058-024-01897-4","vorDoiUrl":"https://doi.org/10.1186/s13058-024-01897-4","workflowStages":[]},"version":"v1","identity":"rs-4912071","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4912071","identity":"rs-4912071","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}