Impact of hormone replacement therapy on all-cause and cancer-specific mortality in colorectal cancer: A systematic review and dose‒response meta-analysis of observational studies

Impact of hormone replacement therapy on all-cause and cancer-specific mortality in colorectal cancer: A systematic review and dose‒response meta-analysis of observational studies | 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 Impact of hormone replacement therapy on all-cause and cancer-specific mortality in colorectal cancer: A systematic review and dose‒response meta-analysis of observational studies Kefeng Liu, Yazhou He, Xianzhuo Zhang, Yongjie Yang, Shusen Sun, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2453698/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Jun, 2024 Read the published version in Journal of Evidence-Based Medicine → Version 1 posted You are reading this latest preprint version Abstract Background The effect of hormone replacement therapy (HRT) on colorectal cancer (CRC) mortality and all-cause mortality remains unclear. We conducted a systematic review and dose‒response meta-analysis to determine the effects of HRT on CRC mortality and all-cause mortality. Methods We searched the PubMed, Embase, and Cochrane Library electronic databases for all relevant studies published until June 2022 to investigate the effects of HRT exposure on survival rates for patients with CRC. Two reviewers independently extracted individual study data and evaluated THE risk of bias among the studies using the Newcastle‒Ottawa Scale. To examine a potential nonlinear relationship between the year of HRT use and CRC mortality, we performed a two-stage random effects dose‒response meta-analysis. RESULTS Ten cohort studies encompassing 480,628 individuals were included. The meta-analysis revealed that HRT was inversely associated with the risk of CRC mortality [hazard ratios (HR) = 0.77, 95% CI (0.68, 0.87), I 2 = 69.5%, P < 0.05]. Pooled results from seven cohort studies revealed a significant association between HRT and the risk of all-cause mortality [HR = 0.71, 95% CI (0.54, 0.92), I 2 = 89.6%, p < 0.05]. A linear (P for nonlinearity = 0.34) dose‒response analysis showed a 3% decrease in the risk of CRC for each additional year of HRT use; this decrease was significant [HR = 0.97, 95% CI(0.94, 0.99), P < 0.05]. An additional linear (P for nonlinearity = 0.88) dose‒response analysis showed a nonsignificantly decrease in the risk of all-cause mortality for each additional year of HRT use. CONCLUSIONS This study suggests that the use of HRT is inversely associated with all-cause and colorectal cancer mortality, thus causing a significant decrease in mortality rates over time. Further studies are warranted to confirm this association. hormone replacement therapy colorectal cancer mortality dose‒response meta-analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Colorectal cancer (CRC) is the third-most common cancer worldwide and the third leading cause of cancer-related deaths for women in the United States 1 – 3 . The majority of CRC patients have sporadic cancer, and approximately 75% of patients with rectal cancer and 80% of patients diagnosed with sporadic colon cancer are ≥ 60 years old 4 , 5 . The incidence rate of colorectal cancer is lower in women (14.3 per 100,000 individuals) than in men (20.6 per 10,000) 6 . In the United States, the cumulative lifetime risk of developing CRC is approximately 6% 7 . Despite advances in treating this disease, the five-year survival rate in the United States is only 62% 8 . The lower incidence of CRC in women indicates that female hormones may exhibit protective effects 9 . Several RCTs and cohort studies have confirmed the inverse relationship between hormone replacement therapy (HRT) and CRC 10 – 15 . Despite the well-established association between HRT use and lower CRC risk, the influence of postmenopausal HTR use on the survival of patients with established CRC remains uncertain. Previous literature has explored this relationship and indicated better survival after a CRC diagnosis in some cases, but the results are still conflicting 16 , 17 . To date, the dose‒response relationship between the duration of HRT use and all-cause mortality has not been reported. Therefore, we conducted an exhaustive systematic review and dose‒response meta-analysis of observational studies and randomized controlled trials to estimate the summary hazard ratios for associations between HRT exposure and the risk of CRC mortality and all-cause mortality. Methods Data sources and search strategy In accordance with the Cochrane Handbook for Systematic Reviews 18 and Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines 19 , we searched the PubMed, Embase, and Cochrane Library electronic databases for all relevant studies published until June 2022 to investigate the effects of HRT exposure on survival rates for patients with CRC ( Appendix 1 in the supplement ). We also searched the reference lists of the included studies to identify additional research that could have been missed during the literature search and selection. We did not apply language restrictions. We also searched Google Scholar using similar keywords. Study Selection and Inclusion Criteria Two independent investigators read all citations identified by the literature search for potentially relevant studies. We cross-checked the selected relevant articles for possible inclusion, and disagreements were resolved through discussion or by conferring with senior investigators. Articles were included for meta-analysis if they met the following inclusion criteria: 1) they were observational studies (including prospective or retrospective cohorts) that explored the association between HRT and prognostic outcomes for patients with CRC; and 2) they reported hazard ratios and 95% confidence intervals or provided indirect data for their calculations. We did not exclude non-English language studies or studies that were abstracts. Articles (i.e., reviews, meta-analyses, commentaries, case series, editorials, and letters) without original survival data were excluded. The primary outcome measures were all-cause mortality and CRC mortality. Data Extraction and Quality Assessment Data extraction was performed by two independently trained reviewers using standardized forms. The following variables were extracted from each study: first author, publication year, research country, number of cases, CRC stage, follow-up period, sample origin, type of HRT, survival endpoints, adjusted variables, hazard ratios (HRs), and 95% CIs with and without adjustment for confounding factors. Study quality was assessed using the Newcastle‒Ottawa Scale (NOS) for observational studies 20 , 21 . Studies with scores of 6 or below were considered to have a high risk of bias (low study quality), and studies with scores of 7 or above were considered to have a low risk of bias (high study quality) 22 , 23 . Conflicts between reviewers were resolved by discussion. Data Synthesis and Analysis All statistical analyses were performed using Stata version 14.0 (Stata Corp LP, College Station, TX, USA). Because of the inherent heterogeneity in our study, we applied DerSimonian and Laird random effects models 24 . Statistical heterogeneity was estimated using the I 2 statistic, with a P value less than 0.05. An I 2 value above 50% indicated significant heterogeneity 25 . We assumed the width of the category to be the same as the adjacent category when the highest category was open-ended and set the lower boundary to zero when the lowest category was open-ended. To examine a potential nonlinear relationship between the duration of HRT use and CRC mortality, we performed a two-stage random effects dose‒response meta-analysis 26 , 27 . We modelled the year of HRT use using restricted cubic splines limited by four knots at fixed percentiles (5%, 35%, 65%, and 95%) of the distribution. In the first stage, considering the correlation within each set of published HRs, a restricted cubic spline model with three spline transformations (four knots minus one) was fitted, and in the second stage, we combined the three regression coefficients estimated in each study and the variance/covariance matrix and used the multivariate extension of the method of moments in the multivariate random effects meta-analysis 28 . We calculated the overall P value by testing the three regression coefficients to be zero at the same time and calculated the nonlinear P value by testing whether the coefficient of the third spline was equal to zero 29 . To explore the sources of heterogeneity, we carried out a series of subgroup analyses based on study design (prospective cohort or retrospective cohort), region (USA, Sweden), patient age ( 5 years), location (colon, rectal), study setting (population-based, hospital-based), research centre (single, multicentre), HRT type (oestrogen, oestrogen + progestin, contraceptive), and HRT use time (former, current). We assessed publication bias using Begg's rank correlation test 30 and Egger's linear regression test 31 , with a P value < 0.1 indicating the existence of publication bias. For both all-cause mortality and CRC mortality, we performed sensitivity analyses to apply the leave-one-out method. All P value s were two-sided, and a P value < 0.05 was considered statistically significant. Results In the preliminary analysis, the search strategy yielded a total of 4,277 studies. After removing duplicates, 3886 studies remained for title and abstract screening. During this process, we excluded 3837 irrelevant citations, and 29 potentially relevant studies remained for full-text review. After excluding reviews, meta-analyses or studies that did not report outcome data, ten studies were found to be eligible for inclusion in this systematic review and dose‒response meta-analysis. Figure 1 shows the results of the study selection. Data from 10 studies were included in the final analysis, involving 480,628 participants 32 – 41 . One study was hospital-based, while the remaining nine were population-based studies. Seven of the included studies were from the United States, and three were from Sweden. The median follow-up period ranged from 5.4 to 13 years (two studies did not provide the median follow-up period). Details of the included studies are provided in Table 1 . Ten of the included cohort studies were found to have a low risk of bias (NOS score ≥ 7). Detailed results of the risk of bias assessments for each study are provided in Appendix 2 in the supplement . Associations between HRT use and the risk of CRC mortality Ten cohort studies 32 – 41 were included in our analysis of the association between HRT use and CRC mortality. The meta-analysis showed that HRT was associated with a 23% reduction in the risk for CRC mortality [HR = 0.77, 95% CI (0.68, 0.87), I 2 = 69.5%, P < 0.05], Fig. 2 . A dose‒response analysis showed strong evidence of a linear (P for nonlinearity = 0.34) association between HRT and CRC mortality based on five cohort studies, such that each additional year of HRT use was associated with a 3% reduction in the risk of CRC mortality; this decrease was statistically significant [HR = 0.97, 95% CI(0.94–0.99), P < 0.05], Fig. 3 . Subgroup analysis Given the significant heterogeneity in the meta-analysis of all the included studies, we performed subgroup analyses to identify the sources of the heterogeneity. We conducted subgroup analyses based on study design, study region, research centre, study setting, use time, location, age and HRT type for CRC mortality in cohort studies. Seven cohort studies showed that HRT may reduce colon cancer mortality [HR = 0.79, 95% CI (0.68, 0.92), I 2 = 69.1%, p < 0.05], and four cohort studies showed that HRT does not reduce rectal cancer mortality [HR = 0.78, 95% CI (0.55, 1.09), I 2 = 58.1%, p = 0.15]. Compared with those with no HRT exposure, four cohort studies indicated that current HRT use [HR = 0.57, 95% CI (0.42,0.77), I 2 = 39.5%, p < 0.05] has benefits for CRC mortality in women. The results are shown in Table 2 . The decreased risk remained constant among other subgroups stratified by study design, study region, research centre, study setting, use time, location, age and HRT type. Moreover, the results of subgroup analyses showed significant between-group differences by study design, study region, research centre, study setting, use time, location and HRT type ( P for between-group difference < 0.05). Table 2 Subgroup analyses in a subset of included studies for risk of CRC mortality Variables RR 95% CI I 2 (%) P No. of studies P for interaction Overall 0.77 0.68 to 0.87 66.4 < 0.001 10 NA Study design 0.001 Prospective cohort 0.75 0.68 to 0.81 0 < 0.001 4 Retrospective cohort 0.80 0.65 to 0.97 73.5 0.023 6 Study region 0.001 USA 0.77 0.66 to 0.90 69 0.01 8 Sweden 0.73 0.63 to 0.85 0 < 0.001 2 Research centre 0.001 Single 0.72 0.62 to 0.84 0 < 0.001 3 Multicentre 0.78 0.67 to 0.91 76.5 0.015 7 Study setting 0.001 Population-based 0.78 0.68 to 0.89 70.6 < 0.001 9 Hospital-based 0.60 0.40 to 0.90 62.5 0.014 1 HRT type < 0.001 Oestrogen 0.78 0.60 to 1.02 77.6 0.066 5 Oestrogen + progestin 0.78 0.46 to 1.33 90.1 0.359 3 Contraceptive 0.92 0.74 to 1.14 0 0.432 2 Location 0.003 Colon 0.79 0.68 to 0.92 69.1 0.003 7 rectal 0.78 0.55 to 1.09 58.2 0.148 4 HRT use 0.002 former 0.89 0.75 to 1.05 54.3 0.164 4 Current 0.57 0.42 to 0.77 54.5 5 0.70 0.59 to 0.83 32.1 < 0.001 5 Age 0.131 70 1.01 0.88 to 1.36 0 0.394 2 Note: HR: hazard ratio; HRT: hormone replacement therapy; CI: confidence interval. Associations between HRT use and the risk of all-cause mortality Meta-analyses for all-cause mortality included seven cohort studies 33,36−41 . The meta-analysis of seven cohort studies showed that HRT was associated with a 29% reduction in the risk for all-cause mortality [HR = 0.71, 95% CI (0.54, 0.92), I 2 = 89.6%, p < 0.05], Fig. 4 . A linear (P for nonlinearity = 0.88) dose‒response analysis of three cohort studies showed that each additional year of HRT use was associated with a 2% decrease in the risk of all-cause mortality; this finding was not statistically significant [HR = 0.98, 95% CI(0.97, 1.01), P = 0.08], Fig. 5 . Subgroup analysis Given the significant heterogeneity in the meta-analysis of all the included studies, we performed subgroup analyses to better understand the heterogeneity. The decreased risk remained constant among other subgroups stratified by study design, study region, research centre, study setting, use time, age and HRT type. Moreover, the results of subgroup analyses showed significant between-group differences by study design, study region, research centre, study setting, use time, age and HRT type ( P for between-group difference < 0.05). The results are shown in Table 3 . Table 3 Subgroup analyses in a subset of included studies for risk of all-cause mortality Variables RR 95% CI I2(%) P No. of studies P for interaction Overall 0.71 0.54 to 0.92 89.6 0.01 9 NA Study design < 0.001 Prospective cohort 0.46 0.21 to 1.06 92.5 0.067 2 Retrospective cohort 0.83 0.68 to 1.02 79.4 0.082 5 Study region < 0.001 USA 0.71 0.51 to 0.99 90.1 0.041 7 Sweden 0.70 0.60 to 0.82 0 < 0.001 1 Research centre < 0.001 Single 0.71 0.62 to 0.81 0 < 0.001 2 Multicentre 0.70 0.46 to 1.05 91.8 0.085 5 Study setting < 0.001 Population-based 0.71 0.53 to 0.96 91.1 0.024 6 Hospital-based 0.70 0.52 to 0.94 0 0.525 1 HRT type 0.002 Oestrogen 0.86 0.66 to 1.11 84.6 0.25 3 Oestrogen + progestin 1.03 0.90 to 1.18 0 0.607 2 contraceptive 0.88 0.65 to 1.18 47.8 0.385 2 HRT use < 0.001 former 0.97 0.83 to 1.13 47.7 0.688 3 Current 0.60 0.35 to 1.02 95.3 0.061 4 Years of use 5 0.89 0.80 to 0.98 4.3 0.021 3 Age 0.001 < 50 0.78 0.65 to 0.95 30.5 0.013 2 50–59 0.95 0.83 to 1.09 0 0.456 3 60–69 0.79 0.70 to 0.90 81.4 70 1.12 0.99 to 1.26 0 0.071 2 Note: CI: confidence interval; HRT: hormone replacement therapy; HR: hazard ratio; Sensitivity analyses and publication bias The results of sensitivity analyses for the outcomes of CRC mortality and all-cause mortality were consistent with those of primary analyses based on cohort studies ( Fig. 6 A, B ) . Sensitivity analyses were performed using the leave-one-out method to further examine the stability of the results. We found that no individual study significantly altered the summary HR [lowest RR = 0.75, 95% CI(0.69,0.80); highest RR = 0.78, 95% CI(0.68, 0.89)] ( Appendix 3 in the supplement ). Funnel plots for CRC mortality demonstrate specific evidence of publication bias as determined by Begg's test (p = 0.82) and Egger’s test (p = 0.38) (Fig. 7 A). Funnel plots for all-cause mortality also demonstrate evidence of publication bias as determined by Begg's test (p = 0.92) and Egger's test (p = 0.25) ( Fig. 7 B). However, there was no evidence of significant publication bias according to Begg’s test and Egger’s test. Discussion This systematic review and dose‒response meta-analysis represents the most comprehensive review to date on the association between HRT use and CRC. We included a total of ten cohort studies encompassing 480,628 individuals. The primary purpose of this study was to determine whether HRT use was associated with survival outcomes in CRC. The 10 included studies suggested that HRT was associated with a 29% reduction in the risk of total all-cause mortality and a 23% reduction in the risk of CRC-specific mortality. Our subgroup analysis showed inconsistent results, however, when considering different study types and HRT estimates. Several extensive observational studies suggest that using hormones can reduce CRC mortality. Specifically, current use of HRT was associated with a significant reduction in the risk of CRC mortality, but former HRT use was not associated with reduced risk of CRC mortality. Additionally, our study found that the use of HRT can reduce the risk of CRC mortality but not the risk of rectal cancer mortality. Finally, our dose‒response meta-analysis suggests that HRT use was associated with a significant decrease in CRC and all-cause mortality rates over time. The mechanism of the effect of HRT on CRC is not known. HRT may reduce colorectal neoplasia, including direct or indirect reductions in secondary bile acid production and inhibition of insulin-like growth factor I 42 . There are also several other mechanisms through which hormone use may protect against the development of CRC and improve survival after diagnosis. Exogenous oestrogens could lead to slower disease progression. Several studies have confirmed that oestrogen inhibits cell growth in human CRC cell lines and that loss of oestrogen results in increased proliferation of normal colonic cells 43 – 45 . In addition, exogenous oestrogens have been associated with changes that prevent methylation, inactivate oestrogen receptors and lead to increased cell growth 46 . Alternatively, oestrogens may inhibit cancer progression through other mechanisms. HRT can reduce the occurrence of colorectal tumours, including through direct or indirect reduction of secondary bile acid production and inhibition of insulin-like growth factor I. In contrast, insulin-like growth factor I seems to stimulate epithelial cell proliferation 42 , 47 . A systematic review 48 published in 2019 showed that the current use of HRT was associated with lower risks of CRC and overall mortality. An earlier systematic review 49 published in 1999 showed that the summary relative risk for death from colon cancer in HRT users was 0.72 (95% CI 0.64, 0.81) compared with nonusers. Our findings show that the use of HRT can reduce the risk of CRC mortality. Additionally, our study included more articles and performed a subgroup analysis. Our study has several strengths. First, to the best of our knowledge, this is the first dose‒response meta-analysis that incorporates cohort studies exploring whether hormones can reduce CRC mortality and all-cause mortality. We investigated the linear relationship between the duration of hormone use and CRC mortality and all-cause mortality by dose‒response meta-analysis. Second, the large sample size of 480,628 allowed us to quantitatively assess the relationship between HRT and CRC, making this the most powerful and comprehensive synthesis of evidence on this issue to date. Third, almost all of the included studies were from nationwide cohorts or population-based cohorts, thereby minimizing the risk of selection bias originating from the study design. Fourth, we developed a detailed and simultaneous search strategy for each database with the help of a professional librarian, thereby maximizing the possibility of identifying all relevant research. Fifth, several approaches, including subgroup analyses and sensitivity analyses, have been applied to thoroughly determine sources of heterogeneity based on the abstracted study-level baseline characteristics. Limitations The present meta-analysis has some limitations. First, significant heterogeneity was found among the included studies, which is predictable and may be partly due to the differences in population baseline characteristics (age, location, HRT type, HRT use time, etc.), and statistical methods (adjustment for confounders). Although several techniques were applied to adjust the results, a substantial moderate to high level of heterogeneity still existed. Nevertheless, given that the results of most subgroup analyses and sensitivity analyses are highly consistent with the main results, we believe that heterogeneity has a limited impact on the main results of the study. Second, the statistical analysis of publication bias was insufficiently powered due to the small number of included studies. Third, some of the subgroup analyses found nonsignificant results, which we consider may result from a relatively small sample size with low statistical power. More evidence from high-quality prospective cohort studies on the effect of HRT on CRC mortality is desirable. Finally, meta-analyses were carried out limited to studies published in English language in peer-reviewed journals. We may have missed articles published in other languages or articles published in journals included other than the three databases we searched. In addition, unpublished grey literature was not included. However, the three major databases – PubMed, Embase and the Cochrane Library – published more than 80–90% of all available reports. Bias may occur when including unpublished literature that has not been peer reviewed. The clinical implications of our study suggest that the use of hormone therapy both before and after CRC diagnosis was associated with a decreased risk of CRC mortality and all-cause mortality. Additional efforts to understand the mechanisms through which HRT influences colorectal carcinogenesis and cancer progression are warranted. Conclusions This dose‒response meta-analysis of cohort studies suggests that the use of HRT is inversely associated with all-cause and colorectal cancer mortality and results in a significant decrease in mortality rates over time. However, whether taking postmenopausal hormones can reduce CRC mortality remains to be further studied. Declarations Author contributions Study concept and design (Shusen Sun, Zubing Mei, Jie Zhao); Acquisition of data (Kefeng Liu, Yazhou He, Xianzhuo Zhang and Yongjie Yang); Analysis and interpretation of data (Kefeng Liu, Yazhou He, Yongjie Yang); Drafting of the manuscript (Kefeng Liu, Yazhou He, Shusen Sun, Zubing Mei and Jie Zhao); Critical revision of the manuscript for important intellectual content (all authors); Study supervision (Yazhou He and Kefeng Liu). Conflict of interest The authors declare that there are no conflicts of interest. Data availability All data generated or analysed during this study are included in this published article and its supplementary information files. Funding This work was supported by the Natural Science Foundation of Sichuan (grant no. 2022NSFSC1314) and Henan Province Medical Science and Technology Research Program Joint Construction Project (grant no. 2022LHGJ20220390) Supplemental material All supplemental material for this article is available online. Ethics approval and consent to participate Not applicable Consent for publication Not applicable Acknowledgements Not applicable References Kuipers EJ, Grady WM, Lieberman D, Seufferlein T, Sung JJ, Boelens PG, van de Velde CJ, Watanabe T. Colorectal cancer. Nat Rev Dis Primers. 2015 Nov;5:1:15065. Luan NN, Wu L, Gong TT, Wang YL, Lin B, Wu QJ. Nonlinear reduction in risk for colorectal cancer by oral contraceptive use: a meta-analysis of epidemiological studies. Cancer Causes Control. 2015 Jan;26(1):65–78. 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Simin J, Liu Q, Wang X, Fall K, Williams C, Callens S, Engstrand L, Brusselaers N. Prediagnostic use of estrogen-only therapy is associated with improved colorectal cancer survival in menopausal women: a Swedish population-based cohort study. Acta Oncol. 2021 Jul;60(7):881–7. Hawk ET, Levin B. Colorectal cancer prevention. J Clin Oncol. 2005 Jan;10(2):378–91. Tutton PJ, Barkla DH. Steroid hormones as regulators of the proliferative activity of normal and neoplastic intestinal epithelial cells (review). Anticancer Res . 1988 May-Jun;8(3):451-6. Lointier P, Wildrick DM, Boman BM. The effects of steroid hormones on a human colon cancer cell line in vitro. Anticancer Res. 1992 Jul-Aug;12(4):1327–30. Singh S, Paraskeva C, Gallimore PH, Sheppard MC, Langman MJ. Differential growth response to oestrogen of premalignant and malignant colonic cell lines. Anticancer Res. 1994 May-Jun;14(3A):1037–41. Issa JP, Ottaviano YL, Celano P, Hamilton SR, Davidson NE, Baylin SB. Methylation of the oestrogen receptor CpG island links ageing and neoplasia in human colon. Nat Genet. 1994 Aug;7(4):536–40. Borgelt L, Umland E. Benefits and challenges of hormone replacement therapy. J Am Pharm Assoc (Wash). 2000 Sep-Oct;40(5 Suppl 1):S30-1. Jang YC, Huang HL, Leung CY. Association of hormone replacement therapy with mortality in colorectal cancer survivor: a systematic review and meta-analysis. BMC Cancer. 2019 Dec;9(1):1199. Nanda K, Bastian LA, Hasselblad V, Simel DL. Hormone replacement therapy and the risk of colorectal cancer: a meta-analysis. Obstet Gynecol. 1999 May;93(5 Pt 2):880–8. Tables Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files 20230125Supplement.docx Table1.docx Cite Share Download PDF Status: Published Journal Publication published 20 Jun, 2024 Read the published version in Journal of Evidence-Based Medicine → Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-2453698","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":170492831,"identity":"8be22f0b-8751-4584-b7d5-8e738a654051","order_by":0,"name":"Kefeng Liu","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kefeng","middleName":"","lastName":"Liu","suffix":""},{"id":170492832,"identity":"d0fbb635-a463-48ba-a151-d49f722eafba","order_by":1,"name":"Yazhou He","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yazhou","middleName":"","lastName":"He","suffix":""},{"id":170492833,"identity":"6e282b3a-ddaa-458a-b4b3-07dabfa1c024","order_by":2,"name":"Xianzhuo Zhang","email":"","orcid":"","institution":"Lanzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xianzhuo","middleName":"","lastName":"Zhang","suffix":""},{"id":170492834,"identity":"560d62f0-b7b0-4875-8471-6a4553cf1b8b","order_by":3,"name":"Yongjie Yang","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yongjie","middleName":"","lastName":"Yang","suffix":""},{"id":170492835,"identity":"5273aa79-707d-4eae-9c52-e1dbf1cad703","order_by":4,"name":"Shusen Sun","email":"","orcid":"","institution":"Western New England University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shusen","middleName":"","lastName":"Sun","suffix":""},{"id":170492836,"identity":"93540d84-811b-4d50-a032-7352190dd6b4","order_by":5,"name":"Zubing Mei","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYBACAziLvbHxwQfStPAcbjacQZoWifQ2aQ5itJiz9z77dKPmsJz5zIcN0gwMdnK6DQS0WPYcN56dc+ywscztxAbjAoZkY7MDhBx2I42ZOYftcOIM6cSG5BkMBxK3EdRy/xlQyz+gFsmDDYd5iNJyg42ZObcNqEWCsbGZOC1ngA7L7Us3luBJbGacYUCMX44fAzrsm7WcBPvx5z8+VNjJEdQCBc0wE4hTDgJ1xCsdBaNgFIyCkQcACktBf4DBSt0AAAAASUVORK5CYII=","orcid":"","institution":"Shanghai University of Traditional Chinese Medicine, Anorectal Disease Institute of Shuguang Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Zubing","middleName":"","lastName":"Mei","suffix":""},{"id":170492837,"identity":"cbe1561d-3125-40d1-a30f-d49cbb9fbb5a","order_by":6,"name":"Jie Zhao","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Zhao","suffix":""}],"badges":[],"createdAt":"2023-01-07 14:44:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2453698/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2453698/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1111/jebm.12622","type":"published","date":"2024-06-20T13:32:16+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":32231366,"identity":"7de75094-03c8-439b-91a9-541aa8b0e03e","added_by":"auto","created_at":"2023-01-30 21:22:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27328,"visible":true,"origin":"","legend":"\u003cp\u003eFlow Diagram of Study Selection\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2453698/v1/f7961d8cf42ea0ff386fecfd.png"},{"id":32231063,"identity":"d48e98af-0fb6-4676-99ee-154ba090eeec","added_by":"auto","created_at":"2023-01-30 21:14:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":68046,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots for meta-analysis of the effect of HRT use onthe risk of CRC mortality\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2453698/v1/3266bff8f0fb20270024e8cd.png"},{"id":32231061,"identity":"2f3d0bbb-ace8-4b0c-bb1b-f3b44a96a6fc","added_by":"auto","created_at":"2023-01-30 21:14:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":41025,"visible":true,"origin":"","legend":"\u003cp\u003eDose‒response meta-analysis of HRT use time and risk of CRC mortality based on cohort studies\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-2453698/v1/a98d062e194e5ad51279a26d.png"},{"id":32231060,"identity":"d14e2283-4870-4d7a-b40a-ae335c9a3664","added_by":"auto","created_at":"2023-01-30 21:14:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":60484,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots for meta-analysis of the effect of HRT use on the risk of all-cause mortality\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-2453698/v1/42d4f41e4bb20cf48cb6084e.png"},{"id":32231367,"identity":"4138b1f3-0656-4a72-aeae-fecc8ec58b6e","added_by":"auto","created_at":"2023-01-30 21:22:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":41347,"visible":true,"origin":"","legend":"\u003cp\u003eDose‒response meta-analysis of HRT use time and risk of all-cause mortality based on cohort studies\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-2453698/v1/68038a8ef34cf0a863fdea73.png"},{"id":32231662,"identity":"b87a294b-873b-4fbc-9a15-70602ac8b8a7","added_by":"auto","created_at":"2023-01-30 21:30:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":81441,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity analysis based on cohort studies\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-2453698/v1/f8bbb2d3d90dae5a25299976.png"},{"id":32231369,"identity":"262b9a92-8748-488a-9ce7-605c4726c2f6","added_by":"auto","created_at":"2023-01-30 21:22:23","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":46684,"visible":true,"origin":"","legend":"\u003cp\u003eAssessment of publication bias based on cohort studies\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-2453698/v1/d49e4647cde46e939c2fd1b0.png"},{"id":59323780,"identity":"7293ed31-3a58-4daa-87fa-f9862ea78ca7","added_by":"auto","created_at":"2024-06-29 13:32:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1168445,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2453698/v1/043d93ab-1df5-401a-b040-af64001f221c.pdf"},{"id":32231057,"identity":"cbc1b0ca-afd5-4d75-8969-89afc303ad42","added_by":"auto","created_at":"2023-01-30 21:14:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":40708,"visible":true,"origin":"","legend":"","description":"","filename":"20230125Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-2453698/v1/abecabea0c34a7edf15c5b41.docx"},{"id":32231055,"identity":"603c2f05-5664-4498-b008-a80d294200ab","added_by":"auto","created_at":"2023-01-30 21:14:23","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":18763,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-2453698/v1/6572a041e4a45a111b36c857.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of hormone replacement therapy on all-cause and cancer-specific mortality in colorectal cancer: A systematic review and dose‒response meta-analysis of observational studies","fulltext":[{"header":"Introduction","content":"\u003cp\u003eColorectal cancer (CRC) is the third-most common cancer worldwide and the third leading cause of cancer-related deaths for women in the United States\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The majority of CRC patients have sporadic cancer, and approximately 75% of patients with rectal cancer and 80% of patients diagnosed with sporadic colon cancer are \u0026ge;\u0026thinsp;60 years old\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The incidence rate of colorectal cancer is lower in women (14.3 per 100,000 individuals) than in men (20.6 per 10,000) \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. In the United States, the cumulative lifetime risk of developing CRC is approximately 6%\u003csup\u003e7\u003c/sup\u003e. Despite advances in treating this disease, the five-year survival rate in the United States is only 62%\u003csup\u003e8\u003c/sup\u003e. The lower incidence of CRC in women indicates that female hormones may exhibit protective effects\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Several RCTs and cohort studies have confirmed the inverse relationship between hormone replacement therapy (HRT) and CRC\u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDespite the well-established association between HRT use and lower CRC risk, the influence of postmenopausal HTR use on the survival of patients with established CRC remains uncertain. Previous literature has explored this relationship and indicated better survival after a CRC diagnosis in some cases, but the results are still conflicting\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. To date, the dose‒response relationship between the duration of HRT use and all-cause mortality has not been reported. Therefore, we conducted an exhaustive systematic review and dose‒response meta-analysis of observational studies and randomized controlled trials to estimate the summary hazard ratios for associations between HRT exposure and the risk of CRC mortality and all-cause mortality.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData sources and search strategy\u003c/h2\u003e \u003cp\u003eIn accordance with the Cochrane Handbook for Systematic Reviews\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, we searched the PubMed, Embase, and Cochrane Library electronic databases for all relevant studies published until June 2022 to investigate the effects of HRT exposure on survival rates for patients with CRC (\u003cb\u003eAppendix 1 in the supplement\u003c/b\u003e). We also searched the reference lists of the included studies to identify additional research that could have been missed during the literature search and selection. We did not apply language restrictions. We also searched Google Scholar using similar keywords.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Selection and Inclusion Criteria\u003c/h2\u003e \u003cp\u003eTwo independent investigators read all citations identified by the literature search for potentially relevant studies. We cross-checked the selected relevant articles for possible inclusion, and disagreements were resolved through discussion or by conferring with senior investigators. Articles were included for meta-analysis if they met the following inclusion criteria: 1) they were observational studies (including prospective or retrospective cohorts) that explored the association between HRT and prognostic outcomes for patients with CRC; and 2) they reported hazard ratios and 95% confidence intervals or provided indirect data for their calculations. We did not exclude non-English language studies or studies that were abstracts. Articles (i.e., reviews, meta-analyses, commentaries, case series, editorials, and letters) without original survival data were excluded. The primary outcome measures were all-cause mortality and CRC mortality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData Extraction and Quality Assessment\u003c/h2\u003e \u003cp\u003eData extraction was performed by two independently trained reviewers using standardized forms. The following variables were extracted from each study: first author, publication year, research country, number of cases, CRC stage, follow-up period, sample origin, type of HRT, survival endpoints, adjusted variables, hazard ratios (HRs), and 95% CIs with and without adjustment for confounding factors. Study quality was assessed using the Newcastle‒Ottawa Scale (NOS) for observational studies\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Studies with scores of 6 or below were considered to have a high risk of bias (low study quality), and studies with scores of 7 or above were considered to have a low risk of bias (high study quality)\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Conflicts between reviewers were resolved by discussion.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Synthesis and Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using Stata version 14.0 (Stata Corp LP, College Station, TX, USA). Because of the inherent heterogeneity in our study, we applied DerSimonian and Laird random effects models\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Statistical heterogeneity was estimated using the I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e statistic, with a \u003cem\u003eP\u003c/em\u003e value less than 0.05. An I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e value above 50% indicated significant heterogeneity\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe assumed the width of the category to be the same as the adjacent category when the highest category was open-ended and set the lower boundary to zero when the lowest category was open-ended. To examine a potential nonlinear relationship between the duration of HRT use and CRC mortality, we performed a two-stage random effects dose‒response meta-analysis\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. We modelled the year of HRT use using restricted cubic splines limited by four knots at fixed percentiles (5%, 35%, 65%, and 95%) of the distribution. In the first stage, considering the correlation within each set of published HRs, a restricted cubic spline model with three spline transformations (four knots minus one) was fitted, and in the second stage, we combined the three regression coefficients estimated in each study and the variance/covariance matrix and used the multivariate extension of the method of moments in the multivariate random effects meta-analysis\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. We calculated the overall P value by testing the three regression coefficients to be zero at the same time and calculated the nonlinear P value by testing whether the coefficient of the third spline was equal to zero\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo explore the sources of heterogeneity, we carried out a series of subgroup analyses based on study design (prospective cohort or retrospective cohort), region (USA, Sweden), patient age (\u0026lt;\u0026thinsp;50 years, 50\u0026ndash;59 years, 60\u0026ndash;69 years or \u0026ge;\u0026thinsp;70 years), duration of HRT use (\u0026le;\u0026thinsp;5 years or \u0026gt;\u0026thinsp;5 years), location (colon, rectal), study setting (population-based, hospital-based), research centre (single, multicentre), HRT type (oestrogen, oestrogen\u0026thinsp;+\u0026thinsp;progestin, contraceptive), and HRT use time (former, current). We assessed publication bias using Begg's rank correlation test\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e and Egger's linear regression test\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, with a \u003cem\u003eP value\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1 indicating the existence of publication bias. For both all-cause mortality and CRC mortality, we performed sensitivity analyses to apply the leave-one-out method. All \u003cem\u003eP value\u003c/em\u003es were two-sided, and a \u003cem\u003eP value\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eIn the preliminary analysis, the search strategy yielded a total of 4,277 studies. After removing duplicates, 3886 studies remained for title and abstract screening. During this process, we excluded 3837 irrelevant citations, and 29 potentially relevant studies remained for full-text review. After excluding reviews, meta-analyses or studies that did not report outcome data, ten studies were found to be eligible for inclusion in this systematic review and dose‒response meta-analysis. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the results of the study selection. Data from 10 studies were included in the final analysis, involving 480,628 participants\u003csup\u003e\u003cspan additionalcitationids=\"CR33 CR34 CR35 CR36 CR37 CR38 CR39 CR40\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. One study was hospital-based, while the remaining nine were population-based studies. Seven of the included studies were from the United States, and three were from Sweden. The median follow-up period ranged from 5.4 to 13 years (two studies did not provide the median follow-up period). Details of the included studies are provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Ten of the included cohort studies were found to have a low risk of bias (NOS score\u0026thinsp;\u0026ge;\u0026thinsp;7). Detailed results of the risk of bias assessments for each study are provided in \u003cb\u003eAppendix 2 in the supplement\u003c/b\u003e.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAssociations between HRT use and the risk of CRC mortality\u003c/h2\u003e \u003cp\u003eTen cohort studies\u003csup\u003e\u003cspan additionalcitationids=\"CR33 CR34 CR35 CR36 CR37 CR38 CR39 CR40\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e were included in our analysis of the association between HRT use and CRC mortality. The meta-analysis showed that HRT was associated with a 23% reduction in the risk for CRC mortality [HR\u0026thinsp;=\u0026thinsp;0.77, 95% CI (0.68, 0.87), I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;69.5%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05], Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A dose‒response analysis showed strong evidence of a linear (P for nonlinearity\u0026thinsp;=\u0026thinsp;0.34) association between HRT and CRC mortality based on five cohort studies, such that each additional year of HRT use was associated with a 3% reduction in the risk of CRC mortality; this decrease was statistically significant [HR\u0026thinsp;=\u0026thinsp;0.97, 95% CI(0.94\u0026ndash;0.99), P\u0026thinsp;\u0026lt;\u0026thinsp;0.05], Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003cp\u003eGiven the significant heterogeneity in the meta-analysis of all the included studies, we performed subgroup analyses to identify the sources of the heterogeneity. We conducted subgroup analyses based on study design, study region, research centre, study setting, use time, location, age and HRT type for CRC mortality in cohort studies. Seven cohort studies showed that HRT may reduce colon cancer mortality [HR\u0026thinsp;=\u0026thinsp;0.79, 95% CI (0.68, 0.92), I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;69.1%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05], and four cohort studies showed that HRT does not reduce rectal cancer mortality [HR\u0026thinsp;=\u0026thinsp;0.78, 95% CI (0.55, 1.09), I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;58.1%, p\u0026thinsp;=\u0026thinsp;0.15]. Compared with those with no HRT exposure, four cohort studies indicated that current HRT use [HR\u0026thinsp;=\u0026thinsp;0.57, 95% CI (0.42,0.77), I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;39.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05] has benefits for CRC mortality in women. The results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The decreased risk remained constant among other subgroups stratified by study design, study region, research centre, study setting, use time, location, age and HRT type. Moreover, the results of subgroup analyses showed significant between-group differences by study design, study region, research centre, study setting, use time, location and HRT type (\u003cem\u003eP\u003c/em\u003e for between-group difference\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\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\u003eSubgroup analyses in a subset of included studies for risk of CRC mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eI\u003csup\u003e2\u003c/sup\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo. of studies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP for interaction\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 to 0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 to 0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrospective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65 to 0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66 to 0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSweden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63 to 0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eResearch centre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62 to 0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulticentre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 to 0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy setting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePopulation-based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 to 0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital-based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40 to 0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHRT type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOestrogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60 to 1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOestrogen\u0026thinsp;+\u0026thinsp;progestin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46 to 1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContraceptive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74 to 1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 to 0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erectal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55 to 1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHRT use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eformer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75 to 1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.42 to 0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears of use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 to 1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59 to 0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56 to 0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84 to 1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74 to 0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88 to 1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNote: HR: hazard ratio; HRT: hormone replacement therapy; CI: confidence interval.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eAssociations between HRT use and the risk of all-cause mortality\u003c/h2\u003e \u003cp\u003eMeta-analyses for all-cause mortality included seven cohort studies\u003csup\u003e33,36\u0026minus;41\u003c/sup\u003e. The meta-analysis of seven cohort studies showed that HRT was associated with a 29% reduction in the risk for all-cause mortality [HR\u0026thinsp;=\u0026thinsp;0.71, 95% CI (0.54, 0.92), I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;89.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05], Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. A linear (P for nonlinearity\u0026thinsp;=\u0026thinsp;0.88) dose‒response analysis of three cohort studies showed that each additional year of HRT use was associated with a 2% decrease in the risk of all-cause mortality; this finding was not statistically significant [HR\u0026thinsp;=\u0026thinsp;0.98, 95% CI(0.97, 1.01), P\u0026thinsp;=\u0026thinsp;0.08], Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003cp\u003eGiven the significant heterogeneity in the meta-analysis of all the included studies, we performed subgroup analyses to better understand the heterogeneity. The decreased risk remained constant among other subgroups stratified by study design, study region, research centre, study setting, use time, age and HRT type. Moreover, the results of subgroup analyses showed significant between-group differences by study design, study region, research centre, study setting, use time, age and HRT type (\u003cem\u003eP\u003c/em\u003e for between-group difference\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The results are shown in 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\u003eSubgroup analyses in a subset of included studies for risk of all-cause mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eI2(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo. of studies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP for interaction\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.54 to 0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21 to 1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrospective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 to 1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.51 to 0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSweden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60 to 0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eResearch centre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62 to 0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulticentre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46 to 1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy setting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePopulation-based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53 to 0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital-based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52 to 0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHRT type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOestrogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66 to 1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOestrogen\u0026thinsp;+\u0026thinsp;progestin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.90 to 1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003econtraceptive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65 to 1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHRT use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eformer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83 to 1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35 to 1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears of use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60 to 1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80 to 0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65 to 0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83 to 1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70 to 0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99 to 1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNote: CI: confidence interval; HRT: hormone replacement therapy; HR: hazard ratio;\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analyses and publication bias\u003c/h2\u003e \u003cp\u003eThe results of sensitivity analyses for the outcomes of CRC mortality and all-cause mortality were consistent with those of primary analyses based on cohort studies \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, B\u003cb\u003e)\u003c/b\u003e. Sensitivity analyses were performed using the leave-one-out method to further examine the stability of the results. We found that no individual study significantly altered the summary HR [lowest RR\u0026thinsp;=\u0026thinsp;0.75, 95% CI(0.69,0.80); highest RR\u0026thinsp;=\u0026thinsp;0.78, 95% CI(0.68, 0.89)] ( \u003cb\u003eAppendix 3 in the supplement\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eFunnel plots for CRC mortality demonstrate specific evidence of publication bias as determined by Begg's test (p\u0026thinsp;=\u0026thinsp;0.82) and Egger\u0026rsquo;s test (p\u0026thinsp;=\u0026thinsp;0.38) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Funnel plots for all-cause mortality also demonstrate evidence of publication bias as determined by Begg's test (p\u0026thinsp;=\u0026thinsp;0.92) and Egger's test (p\u0026thinsp;=\u0026thinsp;0.25) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). However, there was no evidence of significant publication bias according to Begg\u0026rsquo;s test and Egger\u0026rsquo;s test.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis systematic review and dose‒response meta-analysis represents the most comprehensive review to date on the association between HRT use and CRC. We included a total of ten cohort studies encompassing 480,628 individuals. The primary purpose of this study was to determine whether HRT use was associated with survival outcomes in CRC. The 10 included studies suggested that HRT was associated with a 29% reduction in the risk of total all-cause mortality and a 23% reduction in the risk of CRC-specific mortality. Our subgroup analysis showed inconsistent results, however, when considering different study types and HRT estimates. Several extensive observational studies suggest that using hormones can reduce CRC mortality. Specifically, current use of HRT was associated with a significant reduction in the risk of CRC mortality, but former HRT use was not associated with reduced risk of CRC mortality. Additionally, our study found that the use of HRT can reduce the risk of CRC mortality but not the risk of rectal cancer mortality. Finally, our dose‒response meta-analysis suggests that HRT use was associated with a significant decrease in CRC and all-cause mortality rates over time.\u003c/p\u003e \u003cp\u003eThe mechanism of the effect of HRT on CRC is not known. HRT may reduce colorectal neoplasia, including direct or indirect reductions in secondary bile acid production and inhibition of insulin-like growth factor I\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. There are also several other mechanisms through which hormone use may protect against the development of CRC and improve survival after diagnosis. Exogenous oestrogens could lead to slower disease progression. Several studies have confirmed that oestrogen inhibits cell growth in human CRC cell lines and that loss of oestrogen results in increased proliferation of normal colonic cells\u003csup\u003e\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. In addition, exogenous oestrogens have been associated with changes that prevent methylation, inactivate oestrogen receptors and lead to increased cell growth\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Alternatively, oestrogens may inhibit cancer progression through other mechanisms. HRT can reduce the occurrence of colorectal tumours, including through direct or indirect reduction of secondary bile acid production and inhibition of insulin-like growth factor I. In contrast, insulin-like growth factor I seems to stimulate epithelial cell proliferation\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA systematic review\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e published in 2019 showed that the current use of HRT was associated with lower risks of CRC and overall mortality. An earlier systematic review\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e published in 1999 showed that the summary relative risk for death from colon cancer in HRT users was 0.72 (95% CI 0.64, 0.81) compared with nonusers. Our findings show that the use of HRT can reduce the risk of CRC mortality. Additionally, our study included more articles and performed a subgroup analysis.\u003c/p\u003e \u003cp\u003eOur study has several strengths. First, to the best of our knowledge, this is the first dose‒response meta-analysis that incorporates cohort studies exploring whether hormones can reduce CRC mortality and all-cause mortality. We investigated the linear relationship between the duration of hormone use and CRC mortality and all-cause mortality by dose‒response meta-analysis. Second, the large sample size of 480,628 allowed us to quantitatively assess the relationship between HRT and CRC, making this the most powerful and comprehensive synthesis of evidence on this issue to date. Third, almost all of the included studies were from nationwide cohorts or population-based cohorts, thereby minimizing the risk of selection bias originating from the study design. Fourth, we developed a detailed and simultaneous search strategy for each database with the help of a professional librarian, thereby maximizing the possibility of identifying all relevant research. Fifth, several approaches, including subgroup analyses and sensitivity analyses, have been applied to thoroughly determine sources of heterogeneity based on the abstracted study-level baseline characteristics.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe present meta-analysis has some limitations. First, significant heterogeneity was found among the included studies, which is predictable and may be partly due to the differences in population baseline characteristics (age, location, HRT type, HRT use time, etc.), and statistical methods (adjustment for confounders). Although several techniques were applied to adjust the results, a substantial moderate to high level of heterogeneity still existed. Nevertheless, given that the results of most subgroup analyses and sensitivity analyses are highly consistent with the main results, we believe that heterogeneity has a limited impact on the main results of the study. Second, the statistical analysis of publication bias was insufficiently powered due to the small number of included studies. Third, some of the subgroup analyses found nonsignificant results, which we consider may result from a relatively small sample size with low statistical power. More evidence from high-quality prospective cohort studies on the effect of HRT on CRC mortality is desirable. Finally, meta-analyses were carried out limited to studies published in English language in peer-reviewed journals. We may have missed articles published in other languages or articles published in journals included other than the three databases we searched. In addition, unpublished grey literature was not included. However, the three major databases \u0026ndash; PubMed, Embase and the Cochrane Library \u0026ndash; published more than 80\u0026ndash;90% of all available reports. Bias may occur when including unpublished literature that has not been peer reviewed.\u003c/p\u003e \u003cp\u003eThe clinical implications of our study suggest that the use of hormone therapy both before and after CRC diagnosis was associated with a decreased risk of CRC mortality and all-cause mortality. Additional efforts to understand the mechanisms through which HRT influences colorectal carcinogenesis and cancer progression are warranted.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis dose‒response meta-analysis of cohort studies suggests that the use of HRT is inversely associated with all-cause and colorectal cancer mortality and results in a significant decrease in mortality rates over time. However, whether taking postmenopausal hormones can reduce CRC mortality remains to be further studied.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy concept and design (Shusen Sun, Zubing Mei, Jie Zhao);\u003c/p\u003e\n\u003cp\u003eAcquisition of data (Kefeng Liu, Yazhou He, Xianzhuo Zhang and Yongjie Yang);\u003c/p\u003e\n\u003cp\u003eAnalysis and interpretation of data (Kefeng Liu, Yazhou He,\u0026nbsp;Yongjie Yang);\u003c/p\u003e\n\u003cp\u003eDrafting of the manuscript (Kefeng Liu, Yazhou He, Shusen Sun, Zubing Mei and Jie Zhao);\u003c/p\u003e\n\u003cp\u003eCritical revision of the manuscript for important intellectual content (all authors);\u003c/p\u003e\n\u003cp\u003eStudy supervision (Yazhou He\u0026nbsp;and\u0026nbsp;Kefeng Liu).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there\u0026nbsp;are\u0026nbsp;no\u0026nbsp;conflicts\u0026nbsp;of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by\u0026nbsp;the\u0026nbsp;Natural Science Foundation of Sichuan (grant no. 2022NSFSC1314) and Henan Province Medical Science and Technology Research Program Joint Construction Project (grant no. 2022LHGJ20220390)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplemental material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll supplemental material for this article is available online.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKuipers EJ, Grady WM, Lieberman D, Seufferlein T, Sung JJ, Boelens PG, van de Velde CJ, Watanabe T. 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Association of hormone replacement therapy with mortality in colorectal cancer survivor: a systematic review and meta-analysis. BMC Cancer. 2019 Dec;9(1):1199.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNanda K, Bastian LA, Hasselblad V, Simel DL. Hormone replacement therapy and the risk of colorectal cancer: a meta-analysis. Obstet Gynecol. 1999 May;93(5 Pt 2):880\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"hormone replacement therapy, colorectal cancer, mortality, dose‒response, meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-2453698/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2453698/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe effect of hormone replacement therapy (HRT) on colorectal cancer (CRC) mortality and all-cause mortality remains unclear. We conducted a systematic review and dose‒response meta-analysis to determine the effects of HRT on CRC mortality and all-cause mortality.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe searched the PubMed, Embase, and Cochrane Library electronic databases for all relevant studies published until June 2022 to investigate the effects of HRT exposure on survival rates for patients with CRC. Two reviewers independently extracted individual study data and evaluated THE risk of bias among the studies using the Newcastle‒Ottawa Scale. To examine a potential nonlinear relationship between the year of HRT use and CRC mortality, we performed a two-stage random effects dose‒response meta-analysis.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eTen cohort studies encompassing 480,628 individuals were included. The meta-analysis revealed that HRT was inversely associated with the risk of CRC mortality [hazard ratios (HR)\u0026thinsp;=\u0026thinsp;0.77, 95% CI (0.68, 0.87), I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;69.5%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05]. Pooled results from seven cohort studies revealed a significant association between HRT and the risk of all-cause mortality [HR\u0026thinsp;=\u0026thinsp;0.71, 95% CI (0.54, 0.92), I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;89.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05]. A linear (P for nonlinearity\u0026thinsp;=\u0026thinsp;0.34) dose‒response analysis showed a 3% decrease in the risk of CRC for each additional year of HRT use; this decrease was significant [HR\u0026thinsp;=\u0026thinsp;0.97, 95% CI(0.94, 0.99), P\u0026thinsp;\u0026lt;\u0026thinsp;0.05]. An additional linear (P for nonlinearity\u0026thinsp;=\u0026thinsp;0.88) dose‒response analysis showed a nonsignificantly decrease in the risk of all-cause mortality for each additional year of HRT use.\u003c/p\u003e\u003ch2\u003eCONCLUSIONS\u003c/h2\u003e \u003cp\u003eThis study suggests that the use of HRT is inversely associated with all-cause and colorectal cancer mortality, thus causing a significant decrease in mortality rates over time. Further studies are warranted to confirm this association.\u003c/p\u003e","manuscriptTitle":"Impact of hormone replacement therapy on all-cause and cancer-specific mortality in colorectal cancer: A systematic review and dose‒response meta-analysis of observational studies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-30 21:14:17","doi":"10.21203/rs.3.rs-2453698/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b06172d9-ecf7-4f3e-8ddb-a63736422ad6","owner":[],"postedDate":"January 30th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-06-29T13:32:16+00:00","versionOfRecord":{"articleIdentity":"rs-2453698","link":"https://doi.org/10.1111/jebm.12622","journal":{"identity":"journal-of-evidencebased-medicine","isVorOnly":true,"title":"Journal of Evidence-Based Medicine"},"publishedOn":"2024-06-20 13:32:16","publishedOnDateReadable":"June 20th, 2024"},"versionCreatedAt":"2023-01-30 21:14:17","video":"","vorDoi":"10.1111/jebm.12622","vorDoiUrl":"https://doi.org/10.1111/jebm.12622","workflowStages":[]},"version":"v1","identity":"rs-2453698","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2453698","identity":"rs-2453698","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}