Use of statins and risks of ovarian, uterine, and cervical diseases: a cohort study in the UK Biobank

Purpose To examine the associations between use of statins and risks of various ovarian, uterine, and cervical diseases, including ovarian cancer, endometrial cancer, cervical cancer, ovarian cyst, polycystic ovarian syndrome, endometriosis, endometrial hyperplasia, endometrial polyp, and cervical polyp.

We conducted a cohort study among female participants in the UK Biobank. Information on the use of statins was collected through verbal interview. Outcome information was obtained by linking to national cancer registry data and hospital inpatient data. We used Cox proportional hazards regression to examine the associations.

A total of 180,855 female participants (18,403 statin users and 162,452 non-users) were included. Use of statins was significantly associated with increased risks of cervical cancer (adjusted hazard ratio (HR), 1.55; 95% confidence interval (95% CI), 1.05–2.30) and polycystic ovarian syndrome (adjusted HR, 4.39; 95% CI, 1.68–11.49). However, we observed no significant association between use of statins and risk of ovarian cancer, endometrial cancer, ovarian cyst, endometriosis, endometrial hyperplasia, endometrial polyp, or cervical polyp.

Our findings suggest that use of statins is associated with increased risks of cervical cancer and polycystic ovar- ian syndrome, but is not associated with increased or decreased risk of ovarian cancer, endometrial cancer, ovarian cyst, endometriosis, endometrial polyp, or cervical polyp.

Statins · Cohort study · Risk · Cervical cancer · Polycystic ovarian syndrome

Statins, as inhibitors of 3-hydroxy-3-methyl-glutaryl coen - zyme A (HMG-CoA) reductase, function by impeding the biosynthesis of cholesterol through the inhibition of the conversion of HMG-CoA to mevalonate. Consequently, they are primarily used in the treatment of hypercholesterolemia and for the secondary prevention of coronary artery diseases. Statins are among the most widely prescribed drugs world- wide [1, 2]. For example, in the United States, an estimated * Wei Zhang [email protected] * Xiaoxi Zeng [email protected] * Lingli Zhang [email protected] 1 Department of Pharmacy, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China 2 Evidence-Based Pharmacy Center, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China 3 NMPA Key Laboratory for Technical Research On Drug Products In Vitro and In Vivo Correlation, Chengdu, Sichuan, China 4 Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, Sichuan, China 5 West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China 6 Medical Big Data Center, Sichuan University, Chengdu, Sichuan, China 7 Division of Nephrology, Kidney Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China 8 Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China 856 European Journal of Clinical Pharmacology (2024) 80:855–867 38.7 million persons, about 12% of the population, were tak- ing a statin [3]. In addition to their lipid-lowering effect, statins exhibit other pleiotropic effects. For example, some experimental studies of human cell lines and animal models suggest that statins may have beneficial effects in the prevention and treat- ment of several ovarian and uterine diseases, such as ovarian cancer, endometrial cancer, polycystic ovary syndrome, and endometriosis [4, 5]. However, clinical studies regarding this issue are scarce and have yielded inconsistent results [5]. On the other hand, the pleiotropic effects of statins are not always considered beneficial in previous studies. For exam- ple, some other experimental studies of human cell lines and animal models have reported the toxic effects of statins on the ovary and uterus. These toxic effects include antiprolif- erative and pro-apoptotic effects on ovarian and endometrial cells, inhibition of ovarian steroidogenesis, morphological and histological changes in the ovary, antiangiogenic effects, and reduced fertility [6, 7]. Moreover, in our prior pharmacovigi- lance study, by disproportionality analyses using the FDA Adverse Event Reporting System (FAERS) database, we found that use of statins might be associated with increased risks of ovarian cancer, endometrial cancer, cervical cancer, ovarian cyst, polycystic ovarian syndrome, endometriosis, endometrial hyperplasia, endometrial polyp, and cervical polyp [8]. How- ever, the results of disproportionality analyses could only dem- onstrate statistical associations and not causations and should be verified by further cohort studies [9]. The UK Biobank is a large-scale database containing exten- sive sociodemographic, lifestyle, and clinical data on half a million participants. Leveraging this database, we conducted a cohort study to comprehensively examine the associations between use of statins and risks of ovarian cancer, endometrial cancer, cervical cancer, ovarian cyst, polycystic ovarian syn- drome, endometriosis, endometrial hyperplasia, endometrial polyp, and cervical polyp.

Data source The UK Biobank comprises 502,507 volunteer participants aged 37–73 from England, Scotland, and Wales who were recruited between 2006 and 2010. Details of the design and survey methods for UK Biobank have been described in previous studies [10, 11]. At baseline assessment visit and repeat assessment visits, participants completed a touchscreen questionnaire and a verbal interview, which collected information on sociodemographic characteris- tics, lifestyle, medical history, medication history, and reproductive factors. Repeat assessment visits were con- ducted every 2–3 years during the follow-up period, at which participants underwent a repetition of the baseline assessment visit. Thus, repeat assessment visits could enrich, confirm, and calibrate the data collected at base- line assessment visit. Moreover, touchscreen questionnaire validation was performed in two ways. First, some ques - tions (especially medical questions) in the touchscreen questionnaire would be asked again and confirmed in the subsequent verbal interview. Second, the touchscreen questionnaire incorporated a number of logic checks on the data that were entered, such as checking for contra- dictory answers and impossible or improbable numeric values [12]. In addition, the collected data were linked to hospital inpatient data, national cancer registry data, and national death registry data, which enabled long-term follow-up of participants and their health-related outcomes. Hospital inpatient data on participants in England, Scotland, and Wales were received from their respective databases: the Hospital Episode Statistics for England (HES), the Scot- tish Morbidity Record (SMR), and the Patient Episode Database for Wales (PEDW) [9 ]. National cancer registry data and national death registry data were acquired from the National Health Service (NHS) Digital (for partici - pants in England or Wales) and the NHS Central Register (for participants in Scotland) [13]. Study design and population We conducted a cohort study of female participants in the UK Biobank. We excluded females who had a his- tory of cancer (except for non-melanoma skin cancer) [14], ovarian cyst, polycystic ovarian syndrome, endo- metriosis, endometrial hyperplasia, endometrial polyp, cervical polyp, ovariectomy, hysterectomy, or cervice- ctomy at baseline, or who had withdrawn from the UK Biobank. The required information was collected through touchscreen questionnaire/verbal interview and linkage to hospital inpatient data and national cancer registry data. Details of the variable name, data field, and data coding in the UK Biobank are given in Supplemental Table 1. Exposure Information on the use of statins was self-reported and col- lected through verbal interview. If the participant indicated in the touchscreen that they were taking cholesterol-lowering drugs, then the interviewer was prompted to record the name of the drug. Use of statins was defined as continuous use of statins for months or years. It did not include the use of statins for a few days or a week, or prescribed statins that were not taken [15]. Based on treatment with a statin or not, the participants were divided into statin users and non-users. 857European Journal of Clinical Pharmacology (2024) 80:855–867 The statins recorded in the UK Biobank included simvasta- tin, atorvastatin, rosuvastatin, and pravastatin (Supplemental Table 2). Specific data on usage, dosage, and duration were not recorded. Outcome The outcomes were first diagnoses of ovarian cancer, endo- metrial cancer, cervical cancer, ovarian cyst, polycystic ovarian syndrome, endometriosis, endometrial hyperplasia, endometrial polyp, and cervical polyp during the follow-up period. Cases of incident ovarian cancer, endometrial cancer, and cervical cancer were ascertained by linking to national cancer registry data and hospital inpatient data, and incident ovarian cyst, polycystic ovarian syndrome, endometriosis, endometrial hyperplasia, endometrial polyp, and cervical polyp were ascertained by linking to hospital inpatient data. We also obtained the first diagnosis date from national can- cer registry data and hospital inpatient data. The correspond- ing variable name, data field, and data coding in the UK Biobank are presented in Supplemental Table 3. Follow‑up time When assessing cancer outcomes, female participants were followed from baseline visit until the first diagnosis of the outcome, the diagnosis of other cancer (except for non- melanoma skin cancer), death, or the last linkage date with national cancer registry data and hospital inpatient data (31 December 2016 for national cancer registry data, 31 March 2017 for HES, 31 October 2016 for SMR, or 29 February 2016 for PEDW), whichever came first [13, 16]. In addition, when assessing non-cancer outcomes, female participants were followed from baseline visit until the first diagnosis of the outcome, death, or the last linkage date with hospital inpatient data (31 March 2017 for HES, 31 October 2016 for SMR or 29 February 2016 for PEDW), whichever came first [13, 16]. The required information was obtained by linking to national cancer registry data, hospital inpatient data, and national death registry data. Covariates The covariates included age, race (white or others), Townsend deprivation index (quintiles), smoking status (never, past, or current), alcohol use (daily or almost daily, three or four times a week, once or twice a week, one to three times a month, special occasions only, or never), vig- orous physical activity (low, moderate, or high), number of childbirth, number of abortion, comorbidities at baseline (hyperlipidemia, ischemic heart disease, ischemic cerebro- vascular disease, hypertension, diabetes, obesity, or pelvic inflammatory disease), and oral contraceptive. These covari- ates were factors known to be correlated with risks of all outcomes according to previous literatures, or indications for use of statins [4]. Moreover, for each outcome, we included extra related covariates which were correlated solely with risk of this outcome according to previous literatures (Sup- plemental Table 4). All these covariates were collected through touchscreen questionnaire/verbal interview and link- age to hospital inpatient data. Details of the variable name, data field and data coding in the UK Biobank are given in Supplemental Table 5. The Townsend deprivation index was widely used as a measure of socioeconomic deprivation, with higher scores indicating greater deprivation [17]. The number of childbirth was derived from the number of live births and stillbirths. In addition, the number of abortion was derived from the number of spontaneous miscarriages and pregnancy terminations. Furthermore, obesity was defined as body mass index (BMI) ≥ 30. Missing data were coded as a missing indicator category for categorical variables and with mean values for continuous variables. Statistical analysis Baseline analysis Comparisons were made between satin users and non-users for the following variables at baseline: age, race, Townsend deprivation index, smoking status, alcohol use, vigorous physical activity, number of childbirth, number of abor - tion, comorbidities (hyperlipidemia, ischemic heart disease, ischemic cerebrovascular disease, hypertension, diabetes, obesity, and pelvic inflammatory disease), and oral con- traceptive. Continuous variables were presented as mean (standard deviation (SD)) and analyzed by using the Stu- dent’s t-test or median (interquartile range (IQR)) and by Wilcoxon rank-sum test, as appropriate. Categorical vari- ables were presented as counts and percentages and evalu- ated by chi-square test, Fisher’s exact test, or rank-sum test as appropriate. Main analysis We used Cox proportional hazards regression to analyze the associations between use of statins and risks of ovarian, uterine, and cervical diseases, with results expressed as hazard ratios (HRs) and 95% confidence intervals (95% CI). Time since baseline visit was used as the underlying timescale. We developed a multivariable model with adjustment for age, race, Townsend deprivation index, smoking status, alcohol use, vigorous physical activity, number of childbirth, number of abortion, any comorbidity at baseline (hyperlipidemia, ischemic heart 858 European Journal of Clinical Pharmacology (2024) 80:855–867 disease, ischemic cerebrovascular disease, hypertension, diabetes, obesity, or pelvic inflammatory disease), and oral contraceptive. Moreover, for better control of some outcome-specific confounders, we included extra related covariates in the Cox proportional hazards model for each outcome (Supplemental Table 4). Furthermore, the analyses of ovarian cyst, polycystic ovarian syndrome, and endometriosis were restricted to the premenopausal female cohort because these diseases are less likely to develop after menopause. Subgroup analysis We used Schoenfeld residuals to test the proportional haz- ards assumption and found that the assumption was vio- lated for age. Thus, we performed subgroup analysis strati- fied by age to assess if change in result was noteworthy. We performed subgroup analysis stratified by the median age (age (≤ 56 or > 56 years) for ovarian cancer, endometrial cancer, cervical cancer, endometrial hyperplasia, endome- trial polyp, and cervical polyp; age (≤ 46 or > 46 years) for ovarian cyst, polycystic ovarian syndrome, and endome- triosis). In addition, to assess the potential modification effects by statin type, we performed subgroup analysis among different statins. Sensitivity analysis We conducted several sensitivity analyses to confirm the robustness of the results. First, to minimize the potential for reverse causality, we performed a sensitivity analysis by excluding the first year of follow-up (for all individuals). Second, to minimize indication bias, we performed a sensi- tivity analysis by restricting the study population to females with hyperlipidemia, ischemic heart disease, ischemic cer - ebrovascular disease, hypertension, diabetes, or obesity (all these diseases are indications for use of statins or common comorbidities in statin users). Third, as the average age of menopause in UK women is 51 years [18], we performed a sensitivity analysis by censoring the follow-up at age 51 for the outcomes of ovarian cyst, polycystic ovarian syndrome, and endometriosis. All data analyses were conducted using R version 3.6.3. Statistical significance was set at P < 0.05 using two-sided tests. However, as the threshold of P < 0.05 is conventional and arbitrary, it does not convey any meaningful evidence of clinical significance or the size of the effect. Thus, we comprehensively examined the precise P values, the esti- mates of the effect sizes, and the confidence intervals, to interpret the statistical analyses and evaluate the clinical significances [19].

Our study identified 273,314 female participants in the UK Biobank. Among these, 92,459 were excluded because of having a history of cancer (except for non-melanoma skin cancer), ovarian cyst, polycystic ovarian syndrome, endome- triosis, endometrial hyperplasia, endometrial polyp, cervical polyp, ovariectomy, hysterectomy, or cervicectomy at base- line. In total, 180,855 female participants were included in analysis (18,403 statin users and 162,452 non-users) (Fig. 1). The median age of the included participants was 56 years (IQR, 49–62) at baseline. Among them, 54,359 participants (1510 statin users and 52,849 non-users) were premenopau- sal females, and their median age was 46 years (IQR, 43–49) at baseline. Table  1 describes the baseline characteristics of participants according to use of statins. Compared with non-users, statin users were more likely to be older, socio- economically deprived, and smokers. They also had higher number of childbirth and more comorbidities. Moreover, sta- tin users were less likely to be white and physical active, yet had fewer alcohol consumption, lower number of abortion, and less use of oral contraceptives. In addition, when we restricted the study population to premenopausal females, there were no significant differences between statin users and non-users in smoking status, number of childbirth, or number of abortion, while the characteristics of other covari- ates were similar to the whole study population (Supplemen- tal Table 6). Table  2 shows the results of main analysis. During a median follow-up of 8–9 years, the numbers of female par - ticipants with a first diagnosis of ovarian cancer, endometrial cancer, cervical cancer, ovarian cyst, polycystic ovarian syn- drome, endometriosis, endometrial hyperplasia, endometrial polyp, and cervical polyp were 599, 849, 363, 601, 32, 528, 397, 3166, and 814, respectively. The crude incidence per 1000 person-years among non-users and statin users was 0.41 compared to 0.56 for ovarian cancer, 0.55 compared to 1.09 for endometrial cancer, 0.26 compared to 0.24 for cervical cancer, 1.37 compared to 1.39 for ovarian cyst, 0.06 compared to 0.49 for polycystic ovarian syndrome, 1.20 compared to 1.23 for endometriosis, 0.26 compared to 0.39 for endometrial hyperplasia, 2.15 compared to 2.58 for endometrial polyp, and 0.56 compared to 0.52 for cervical polyp. After adjustment for the covariates, use of statins was significantly associated with increased risks of cervical cancer (adjusted HR, 1.55; 95% CI, 1.05–2.30) and polycystic ovarian syndrome (adjusted HR, 4.39; 95% CI, 1.68–11.49). However, we observed no significant association between use of statins and risk of ovar- ian cancer (adjusted HR, 0.94; 95% CI, 0.73–1.22), endome- trial cancer (adjusted HR, 1.06; 95% CI, 0.88–1.28), ovarian cyst (adjusted HR, 0.92; 95% CI, 0.56–1.52), endometriosis 859European Journal of Clinical Pharmacology (2024) 80:855–867 (adjusted HR, 0.84; 95% CI, 0.49–1.42), endometrial hyper- plasia (adjusted HR, 1.04; 95% CI, 0.77–1.40), endometrial polyp (adjusted HR, 0.99; 95% CI, 0.88–1.11), or cervical polyp (adjusted HR, 0.99; 95% CI, 0.76–1.28). Figure  2 shows stratified analyses by statin type. The numbers of simvastatin, atorvastatin, rosuvastatin, and pravastatin users in the subgroups were 13,426, 3873, 905, and 664, respectively. When we restricted the study population to premenopausal females, the numbers of sim- vastatin, atorvastatin, rosuvastatin, and pravastatin users in the subgroups were 1107, 337, 67, and 47, respectively. For cervical cancer, use of pravastatin was significantly associated with increased risk of cervical cancer (adjusted HR, 4.31; 95% CI, 1.36–13.63), use of simvastatin was borderline associated with increased risk of cervical can- cer (adjusted HR, 1.55; 95% CI, 0.98–2.42), whereas use of atorvastatin was not significantly associated with risk of cervical cancer. For polycystic ovarian syndrome, uses of simvastatin (adjusted HR, 3.90; 95% CI, 1.27–11.94) and atorvastatin (adjusted HR, 7.00; 95% CI, 1.55–31.58) were all significantly associated with increased risk of polycys- tic ovarian syndrome. For endometrial hyperplasia, use of pravastatin (adjusted HR, 2.50; 95% CI, 1.03–6.10) was significantly associated with increased risk of endometrial hyperplasia, whereas use of other types of statins was not significantly associated with risk of endometrial hyper - plasia. For other outcomes, use of simvastatin, atorvasta- tin, rosuvastatin, or pravastatin was all not significantly Fig. 1 Flow chart of study population 860 European Journal of Clinical Pharmacology (2024) 80:855–867 associated with risk of ovarian cancer, endometrial cancer, ovarian cyst, endometriosis, endometrial polyp, or cervi- cal polyp. Figure  3 shows stratified analyses by the median age. There remained no significant association between use of statins and risk of ovarian cancer, endometrial cancer, Table 1 Baseline characteristics of participants by use of statins IQR interquartile range. Data are n (%) unless otherwise indicated Characteristics Non-users (n = 162,452) Statin users (n = 18,403) P value Age, years, median (IQR) 55 (48–61) 62 (57–66) < 0.001 Race < 0.001     White 152,657 (94.0) 17,118 (93.0)     Others 8972 (5.5) 1202 (6.5)     Missing 823 (0.5) 83 (0.5) Townsend deprivation index (quintiles) < 0.001     1 (least deprived) 33,061 (20.4) 3104 (16.9)     2 32,757 (20.2) 3333 (18.1)     3 32,536 (20.0) 3588 (19.5)     4 32,352 (19.9) 3773 (20.5)     5 (most deprived) 31,537 (19.4) 4589 (24.9)     Missing 209 (0.1) 16 (0.1) Smoking status < 0.001     Never 99,523 (61.3) 10,158 (55.2)     Past 48,284 (29.7) 6384 (34.7)     Current 13,802 (8.5) 1752 (9.5)     Missing 843 (0.5) 109 (0.6) Alcohol use < 0.001     Daily or almost daily 26,988 (16.6) 2657 (14.4)     Three or four times a week 35,612 (21.9) 3055 (16.6)     Once or twice a week 42,661 (26.3) 4206 (22.9)     One to three times a month 20,931 (12.9) 2360 (12.8)     Special occasions only 22,209 (13.7) 3539 (19.2)     Never 13,571 (8.4) 2528 (13.7)     Missing 480 (0.3) 58 (0.3) Vigorous physical activity < 0.001     Low 22,797 (14.0) 2911 (15.8)     Moderate 55,190 (34.0) 5849 (31.8)     High 49,685 (30.6) 4655 (25.3)     Missing 34,780 (21.4) 4988 (27.1) Number of childbirth, median (IQR) 2 (1–2) 2 (1–3) < 0.001 Number of abortion, median (IQR) 0 (0–1) 0 (0–1) < 0.001 Comorbidities     Hyperlipidemia 3944 (2.4) 12,767 (69.4) < 0.001     Ischemic heart disease 1827 (1.1) 2680 (14.6) < 0.001     Ischemic cerebrovascular disease 860 (0.5) 1153 (6.3) < 0.001     Hypertension 29,333 (18.1) 11,024 (59.9) < 0.001     Diabetes 2408 (1.5) 3719 (20.2) < 0.001     Obesity 32,385 (19.9) 6992 (38.0) < 0.001     Pelvic inflammatory disease 1759 (1.1) 161 (0.9) 0.010 Oral contraceptive < 0.001     Yes 134,183 (82.6) 13,259 (72.0)     No 27,398 (16.9) 5031 (27.3)     Missing 871 (0.5) 113 (0.6) 861European Journal of Clinical Pharmacology (2024) 80:855–867 ovarian cyst, endometriosis, endometrial hyperplasia, endometrial polyp, or cervical polyp in all age groups. A tendency toward increased risk of cervical cancer was observed in statin users aged > 56 years (adjusted HR, 1.62; 95% CI, 0.94–2.79), but this tendency was not observed in users aged ≤ 56 years (adjusted HR, 1.39; 95% CI, 0.75–2.55). Moreover, increased risk for poly - cystic ovarian syndrome from use of statins was seen in premenopausal females aged ≤ 46 years (adjusted HR, 7.74; 95% CI, 2.52–23.79), whereas no significant asso- ciation was seen in premenopausal females aged > 46 years (adjusted HR, 1.46; 95% CI, 0.18–12.02). In our sensitivity analyses, the associations between use of statins and risks of all outcomes remained: (1) when we excluded the first year of follow-up (for all individu- als) (Fig.  4A); (2) when we restricted the study population to females with hyperlipidemia, ischemic heart disease, ischemic cerebrovascular disease, hypertension, diabetes, or obesity (Fig.  4B); and (3) when we censored the follow- up of premenopausal females at age 51 (Fig.  4C).

Principal findings In this large-scale cohort study, we found that use of statins was significantly associated with increased risks of cervi- cal cancer and polycystic ovarian syndrome, but was not significantly associated with risk of ovarian cancer, endo- metrial cancer, ovarian cyst, endometriosis, endometrial hyperplasia, endometrial polyp, or cervical polyp. We also noticed the potential modifying effects of statin type and age on the aforementioned associations. For instance, use of simvastatin was significantly associated with increased risk of polycystic ovarian syndrome and was borderline associated with increased risk of cervical cancer; use of atorvastatin was significantly associated with increased risk of polycystic ovarian syndrome; use of pravastatin was significantly associated with increased risks of cervical cancer and endometrial hyperplasia. Moreover, when we stratified by the median age, increased risk for polycystic Table 2 The associations between use of statins and risks of ovarian cancer, endometrial cancer, cervical cancer, ovarian cyst, polycystic ovarian syndrome, endometriosis, endometrial hyperplasia, endometrial polyp, and cervical polyp HR hazard ratio, CI confidence interval *Adjusted for age, race, Townsend deprivation index, smoking status, alcohol use, vigorous physical activity, number of childbirth, number of abortion, any comorbidity at baseline (hyperlipidemia, ischemic heart disease, ischemic cerebrovascular disease, hypertension, diabetes, obesity, or pelvic inflammatory disease), oral contraceptive, and extra outcome-specific covariates. Moreover, the analyses of ovarian cyst, polycystic ovarian syndrome, and endometriosis were restricted to the premenopausal female cohort Outcome Non-users Statin users Adjusted* No. of participants No. of outcome Incidence per 1000 person- years No. of participants No. of outcome Incidence per 1000 person- years HR (95% CI) P Ovarian cancer 162,452 519 0.41 18,403 80 0.56 0.94 (0.73– 1.22) 0.665 Endometrial cancer 162,452 693 0.55 18,403 156 1.09 1.06 (0.88– 1.28) 0.541 Cervical cancer 162,452 329 0.26 18,403 34 0.24 1.55 (1.05– 2.30) 0.028 Ovarian cyst 52,849 584 1.37 1510 17 1.39 0.92 (0.56– 1.52) 0.758 Polycystic ovarian syn- drome 52,849 26 0.06 1510 6 0.49 4.39 (1.68– 11.49) 0.003 Endometriosis 52,849 513 1.20 1510 15 1.23 0.84 (0.49– 1.42) 0.503 Endometrial hyperplasia 162,452 340 0.26 18,403 57 0.39 1.04 (0.77– 1.40) 0.819 Endometrial polyp 162,452 2790 2.15 18,403 376 2.58 0.99 (0.88– 1.11) 0.883 Cervical polyp 162,452 738 0.56 18,403 76 0.52 0.99 (0.76– 1.28) 0.926 862 European Journal of Clinical Pharmacology (2024) 80:855–867 863European Journal of Clinical Pharmacology (2024) 80:855–867 ovarian syndrome from use of statins was only seen in premenopausal females aged ≤ 46 years. Compared with previous studies The relationship between use of statins and risks of ovar - ian cancer and endometrial cancer is an intensely disputed topic. Some case–control studies found that use of statins was associated with reduced risks of ovarian cancer and endometrial cancer, which suggests that statins might have preventive effects on ovarian cancer and endometrial cancer [20, 21]. However, in recent years, more and more cohort and case–control studies showed that use of statins was not associated with risk of ovarian cancer or endometrial cancer [22–24]. Our study also found no association between use of statins and risk of ovarian cancer or endometrial cancer and does not support that use of statins may prevent ovarian cancer or endometrial cancer. Our study indicated that use of statins was associated with increased risk of cervical cancer, which is inconsistent with a prior cohort study conducted by Kim et al. Kim et al.’s study is the only clinical study to date exploring the asso- ciation between use of statins and risk of cervical cancer. That study used health insurance claims data and found that use of statins was associated with reduced risk of cervical cancer [22]. We cannot completely explain the discrepancies Fig. 2 The associations between use of statins and risks of ovarian cancer, endometrial cancer, cervical cancer, ovarian cyst, polycystic ovarian syndrome, endometriosis, endometrial hyperplasia, endome- trial polyp, and cervical polyp stratified by statin type. HR hazard ratio, CI confidence interval; —, the sample size was too small to enable statistical analysis. *Adjusted for age, race, Townsend depri- vation index, smoking status, alcohol use, vigorous physical activity, number of childbirth, number of abortion, any comorbidity at base- line (hyperlipidemia, ischemic heart disease, ischemic cerebrovascu- lar disease, hypertension, diabetes, obesity, or pelvic inflammatory disease), oral contraceptive, and extra outcome-specific covariates. Moreover, the analyses of ovarian cyst, polycystic ovarian syndrome, and endometriosis were restricted to the premenopausal female cohort ◂ Fig. 3 The associations between use of statins and risks of ovarian cancer, endometrial cancer, cervical cancer, ovarian cyst, polycystic ovarian syndrome, endometriosis, endometrial hyperplasia, endome- trial polyp, and cervical polyp stratified by the median age. HR haz- ard ratio, CI confidence interval. *Adjusted for race, Townsend depri- vation index, smoking status, alcohol use, vigorous physical activity, number of childbirth, number of abortion, any comorbidity at base- line (hyperlipidemia, ischemic heart disease, ischemic cerebrovascu- lar disease, hypertension, diabetes, obesity, or pelvic inflammatory disease), oral contraceptive, and extra outcome-specific covariates. Moreover, the analyses of ovarian cyst, polycystic ovarian syndrome and endometriosis were restricted to the premenopausal female cohort 864 European Journal of Clinical Pharmacology (2024) 80:855–867 between Kim et al.’s study and our study, but it should be noted that some differences in study design exist. Due to the limited information contained in health insurance claims data, Kim et al.’s study only analyzed the potential con- founding effects of age, comorbidities, and co-medication and was unable to analyze the potential confounding effects of other sociodemographic, lifestyle, and clinical factors. In our study, UK Biobank contains extensive sociodemo- graphic, lifestyle, and clinical information. Thus, compared with Kim et al.’s study, we further analyzed the potential confounding effects of Townsend deprivation index, smok- ing status, alcohol use, vigorous physical activity, num- ber of childbirth, number of abortion, lifetime number of sexual partners, age first had sexual intercourse, and oral Fig. 4 Sensitivity analyses for the associations between use of statins and risks of ovarian cancer, endometrial cancer, cervical cancer, ovar- ian cyst, polycystic ovarian syndrome, endometriosis, endometrial hyperplasia, endometrial polyp, and cervical polyp by excluding the first year of follow-up (A), restricting the study population to females with hyperlipidemia, ischemic heart disease, ischemic cerebrovascu- lar disease, hypertension, diabetes, or obesity (B), and censoring the follow-up of premenopausal females at age 51 (C). HR hazard ratio, CI confidence interval. *Adjusted for age, race, Townsend depriva- tion index, smoking status, alcohol use, vigorous physical activity, number of childbirth, number of abortion, any comorbidity at base- line (hyperlipidemia, ischemic heart disease, ischemic cerebrovascu- lar disease, hypertension, diabetes, obesity, or pelvic inflammatory disease), oral contraceptive, and extra outcome-specific covariates. Moreover, the analyses of ovarian cyst, polycystic ovarian syndrome, and endometriosis were restricted to the premenopausal female cohort 865European Journal of Clinical Pharmacology (2024) 80:855–867 contraceptive. All these factors have been reported to be cor- related with the occurrence of cervical cancer. For example, socioeconomic deprivation, smoking, alcohol use, multiple sexual partners, early age at first intercourse, and use of oral contraceptives are important risk factors for cervical cancer [25–27], while multiple childbirth is a protective fac- tor for cervical cancer [28]. By adjusting for these potential confounding factors, our study might provide more reliable

than Kim et al.’s study. Several possible mechanisms might explain the increased risk of cervical cancer associ- ated with use of statins. First, inhibition of serum cholesterol levels by statins may be associated with increased risk of cancer [ 29]. Second, statins could enhance mitotic abnor - malities, which may interfere with centromere development and function, leading to increased risk of mutations and cancer [30]. Third, statins could increase regulatory T cell numbers, which may impair the antitumor immune response of the host [31]. Our study also found that use of statins was associated with increased risk of polycystic ovarian syndrome and was not associated with risk of endometriosis. These find- ings are inconsistent with previous experimental studies of human cell lines and animal models. For example, previ- ous experimental studies suggest that statins might prevent polycystic ovarian syndrome by reducing steroid hormone synthesis and inhibiting the growth of theca-interstitial cells in ovaries [4 , 5]. In addition, previous experimen- tal studies also suggest that statins might prevent endo- metriosis due to their antiproliferative and pro-apoptotic effects on endometrial and endometriotic cells, their abil- ity to reduce cell viability and migration, the inhibition of angiogenesis, and anti-inflammatory activities [5 , 6]. As it is possible that the effects of statins in patients may be different from those observed in cell culture or animal models, our cohort study provides more credible results than previous experimental studies. Explain unexpected findings For cervical cancer, when we performed subgroup analysis stratified by statin type or the median age, the association was attenuated in most subgroups, which may be due to the decreased sample size. However, the association with cervical cancer risk was enhanced in the pravastatin sub- group. Similarly, some previous clinical studies also found that pravastatin was more likely to increase cancer risk than other types of statins. For example, a cohort study by Desai et al. indicated that use of pravastatin was associated with increased risk of ovarian cancer, whereas use of other types of statins was not [32]. In addition, a record-linkage study by Haukka et al. showed that use of pravastatin was associated with increased risk of non-melanoma skin cancer, whereas use of other types of statins was not [ 33]. The mechanism why pravastatin is more likely to increase cancer risk than other types of statins is unclear, but may be related to the highly hydrophilic property of pravastatin. Based on their solubility, statins can be chemically classified as lipophilic statins and hydrophilic statins. Lipophilic statins enter cells through passive diffusion, whereas hydrophilic statins enter cells through active transport. It is postulated that the cel - lular uptake pattern of statins might be related to their effect on tumor growth [32]. For polycystic ovarian syndrome, we found that increased risk for polycystic ovarian syndrome from use of statins was seen in premenopausal females aged ≤ 46 years, whereas no significant association was seen in pre- menopausal females aged > 46 years. Polycystic ovarian syndrome mainly occurs in reproductive aged females (12–45 years) and is less likely to occur in females aged > 46 years [34]. Similarly, in our study, only 10 poly- cystic ovarian syndrome cases occurred in premenopausal females aged > 46 years, and the result for this subgroup was imprecise (with wide confidence interval) and may be a false negative. Thus, further studies are needed to verify this finding and explore the underlying mechanism. For endometrial hyperplasia, we found that use of pravastatin was significantly associated with increased risk of endometrial hyperplasia, whereas use of other types of statins was not. Currently, there is no clear explanation for this finding. Besides, as the sample size of pravastatin users (664) was relatively small, we could not rule out the possibility that the increased risk for endometrial hyper - plasia from use of pravastatin was due to chance. Thus, further studies are also needed to confirm this finding and explore the possible mechanism. Strengths and limitations Our study has several strengths. First, the UK Biobank con- tains extensive sociodemographic, lifestyle, and clinical information, which enabled us to adjust for a wide range of confounders and conduct multiple subgroup analyses. Sec- ond, most subgroup and sensitivity analyses showed consist- ent results with the main analysis, which further confirmed the robustness of our results. Third, the prospective design limited recall bias on the assessment of statins. Our study also has some limitations. First, use of statins and some covariates were assessed by self-report, which might induce misclassification. Such misclassification is likely non-differential between individuals with and with- out outcome events, which would attenuate the association toward null. However, this cannot flip a protective effect (HR 1). Second, we did not have information on duration or dosage of statins, and it may take time for statins to have effects on outcome events. Further studies are needed to evaluate the impacts of these 866 European Journal of Clinical Pharmacology (2024) 80:855–867 factors on results. Third, the diagnosis information of ovar- ian cyst, polycystic ovarian syndrome, endometriosis, endo- metrial hyperplasia, endometrial polyp, and cervical polyp was obtained by linking to hospital inpatient data. That said, these diseases diagnosed at the outpatient clinic and asymptomatic/undiagnosed ones were not captured in our data. This misclassification might be differential between statin users and non-users because users have more fre- quent healthcare visits and are subject to surveillance bias. Fourth, potential reverse causality may exist in our study as it takes years for outcome events to develop. However, the results remained unchanged when we excluded the first year of follow-up. Fifth, although we adjusted for all main indications for statins in the statistical model and further performed sensitivity analysis, indication bias could not be completely avoided.

and clinical and  research implications In conclusion, in this cohort study of UK Biobank female participants, use of statins was associated with increased risks of cervical cancer and polycystic ovarian syndrome, but was not associated with increased or decreased risk of ovarian cancer, endometrial cancer, ovarian cyst, endome - triosis, endometrial polyp, or cervical polyp. Unlike some previous studies, our findings do not support that use of statins may prevent ovarian cancer, endometrial cancer, cer- vical cancer, polycystic ovarian syndrome, or endometriosis. Moreover, according to our findings, the potential risks of cervical cancer and polycystic ovarian syndrome associated with use of statins are of great importance and should be closely monitored in future clinical practice. However, our findings should be interpreted with cautions due to indica- tion and surveillance biases. Abbreviations HMG-CoA: 3-Hydroxy-3-methyl-glutaryl coenzyme A; FAERS: FDA Adverse Event Reporting System; HES: Hospital Episode Statistics for England; SMR: Scottish Morbidity Record; PEDW: Patient Episode Database for Wales; NHS: National Health Service; SD: Standard deviation; IQR: Interquartile range; HRs: Hazard ratios; 95% CI: 95% Confidence intervals Supplementary Information The online version contains supplemen- tary material available at https:// doi. org/ 10. 1007/ s00228- 024- 03656-y.

This work uses data provided by patients and collected by the NHS as part of their care and support. This research used data assets made available by National Safe Haven as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref: MC_PC_20029 and MC_PC_20058). Moreover, this research has been conducted using the UK Biobank Resource under Application 54803. We thank the team members involved in West China Biomedical Big Data Center for their support. Author contribution X.F.J., L.Z., X.Z., and W.Z. were responsible for the study concept and design. H.Y., Y.H., Y.Q., and W.C. did the data and project management. X.F.J. did the data cleaning and analysis. X.F.J. and H.L. made the figures and tables. L.Z. and Y.S. interpreted the data. X.F.J. drafted the manuscript. X.Z. and L.L.Z. revised the manuscript. All the authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. Funding This study was supported by Natural Science Foundation of Sichuan Province (grant number 2022NSFSC0644). Data availability Data from the UK Biobank (http:// www. ukbio bank. ac. uk/) are available to all researchers upon making an application. Part of this research was conducted using the UK Biobank Resource under Application 54803. Declarations Ethics approval and informed consent The UK Biobank has full ethical approval from the NHS National Research Ethics Service (16/NW/0274), and this study was approved by the biomedical research ethics committee of West China Hospital (2019.1171). All the UK Biobank participants provided written informed consent before data collection. Competing interests The authors have no competing interests. Disclaimer The funders had no role in the development of this article (i.e., in the study design; collection, analysis, and interpretation of data; report writing; or decision to submit the paper for publication). Open Access This article is licensed under a Creative Commons Attri- bution 4.0 International License, which permits use, sharing, adapta- tion, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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