Abstract
Aims
The incidence of postmenopausal bleeding (PMB) has been increasing over the past years. Little is known about the risk of PMB after COVID‐19 vaccination. Our study aimed to investigate this based on routine general practitioner (GP) healthcare data from the Netherlands.
Methods
A retrospective self‐controlled cohort study was performed, which included women aged ≥50 years who received at least 1 COVID‐19 vaccination in 2021 and were registered in the GP databases of Nivel (the Nivel Primary Care Database, Nivel‐PCD) or PHARMO by 1 January 2021. GP consultations for PMB in the exposed period (28 days after each COVID‐19 vaccination) were compared with the nonexposed period (all‐time outside the exposed period). Incidence rate ratios (IRRs) were calculated using Poisson regression, adjusting for SARS‐CoV‐2 infection during the study follow‐up period.
Results
A total of 692 760 COVID‐19 vaccinated women aged ≥50 years were included. No increased GP consultations for PMB was observed for all COVID‐19 vaccines together, as well as when stratifying the results by vaccine type (mRNA vs. vector) and vaccine brand (Pfizer/BioNTech, Moderna, AstraZeneca, Johnson & Johnson). After the second Moderna dose an adjusted IRR of 1.47 (95% confidence interval: 0.93–2.32) was observed and after the third Pfizer/BioNTech dose an adjusted IRR of 1.33 (95% confidence interval: 0.92–1.93); however, these results were not statistically significant.
Conclusion
No increased number of GP consultations for PMB in primary care was observed after COVID‐19 vaccination in general, nor for any of the COVID‐19 vaccine brands, vaccine doses or potential risk groups.
Keywords: cohort study, COVID‐19, general practitioner, postmenopausal bleeding, primary healthcare data, vaccination
What is already known about this subject
There are limited studies that describe the association between postmenopausal bleeding (PMB) and COVID‐19 vaccination, which, in addition, show inconsistent results.
In March 2024, the Pharmacovigilance Risk Assessment Committee concluded that there was insufficient evidence of a causal association between PMB and the Pfizer/BioNTech and Moderna COVID‐19 vaccines.
What this study adds
This study showed no increased risk (based on general practitioner consultations) of PMB after COVID‐19 vaccination, for none of the vaccination doses, vaccine types, vaccine brands or potential risk groups.
However, a possible relation between PMB and COVID‐19 vaccination should not be ruled out, as some of the sub‐analyses might not have had sufficient power to identify a possible relation and the risk of PMB might be underreported based on a diagnosis‐approach. Further research could elaborate on this.
1. INTRODUCTION
Postmenopausal bleeding (PMB) is defined as vaginal blood loss that occurs ≥1 year after the last menstrual bleeding. PMB is usually caused by benign gynaecological conditions such as endometrial polyps. However, in around 10% it is a sign of malignancy, for example uterine cancer or endometrial cancer. The risk of PMB due to a malignancy increases with age. 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 Based on general practitioner (GP) data, the incidence of PMB in the Netherlands increased from 3.2 per 1000 inhabitants in 2019 to 3.3 per 1000 inhabitants in 2020 and 3.5 per 1000 inhabitants in 2021 and 2022. 9
On 18 January 2021, the first case of PMB after COVID‐19 vaccination was reported to the spontaneous reporting system of Lareb, the national pharmacovigilance centre in the Netherlands. Lareb identifies possible risks associated with the use of vaccines and medicines and is the knowledge centre for adverse drugs reactions. From the start of the vaccination campaign until 8 February 2022, Lareb had received 669 spontaneous reports of PMB associated with a COVID‐19 vaccine, with the highest reporting rate observed among the age group 50–54 years (except for the third dose of Pfizer/BioNTech). The highest overall reporting rate was seen after Johnson & Johnson vaccination, i.e. 21.4 reports per 100 000 vaccinations. 10 However, due to the analyses based on spontaneous reports do not include a control group, further signal evaluation is often necessary. In addition, limited studies are available on the risk of PMB after COVID‐19 vaccination, in which the majority of studies did not include a control group, had a relatively small sample size and/or the study designs used (e.g. cross‐sectional or descriptive) did not allow for a precise estimation of PMB after COVID‐19 vaccination. 11 , 12 , 13 , 14 , 15 , 16 , 17 Also, the increase of incidence of PMB over the past years could be due to various possible reasons such as an increase of malignancies or hormone replacement therapy (HRT) use causing PMB, but the COVID‐19 pandemic (i.e. SARS‐CoV‐2 infection and/or COVID‐19 vaccination) could also have played a role.
Therefore, the current study was performed, which was part of a larger pilot project in which an infrastructure was built to perform in depth analyses based on Electronic Health Record data, among which the analysis on the risk of PMB after COVID‐19 vaccination. In this study, we aimed to use routine GP healthcare data from the Netherlands: (i) to investigate the risk of PMB after COVID‐19 vaccination (by vaccine type, vaccine brands and vaccine doses); and (ii) to identify potential risk groups with an increased risk of PMB after COVID‐19 vaccination.
2. METHODS
2.1. Study population
This study included women from the Netherlands aged ≥50 years who received at least 1 COVID‐19 vaccination in 2021 and who were registered in the GP databases of Nivel (the Nivel Primary Care Database, Nivel‐PCD) and PHARMO by 1 January 2021. Women were excluded: (i) if they consulted the GP for PMB in the 6 months before cohort entry; (ii) if no data were available in the 6 months before cohort entry; and (iii) if they consulted the GP for menstrual disorders in 2021, meaning that these women had not yet reached the menopause.
2.2. Study design
A retrospective self‐controlled cohort study was performed. All included women were followed from 1 January 2021 (cohort entry date) until the first GP consult for PMB in 2021 (cohort exit date), until deregistration at the GP practise in 2021 due to for example relocation or death (cohort exit date), or until 31 December 2021 was reached (cohort exit date), whichever came first. Only the first GP consult for PMB in 2021 was included, since multiple consults in the same year are most likely to be related to the same event. The follow‐up period, which is the time between cohort entry date and cohort exit date, was then divided into the exposed period and nonexposed period. The exposed period was set at 28 days after each vaccination. This cut‐off was based on the time‐to‐onset information from spontaneous reports received by Lareb and previous research, 10 , 11 , 14 as well as on the expectation that women with PMB will consult the GP within a relatively short time. If the second vaccination was given in <28 days, the exposed period of the first vaccination was truncated as soon as the second vaccination was administered. The nonexposed period was defined as the follow‐up period minus the exposed period and can consist of: (i) the period from 1 January 2021 until the first vaccination; (ii) the period of >28 days between each vaccination; and (iii) the period of >28 days after the last vaccination until the cohort exit date. A person can contribute to both the exposed and nonexposed period or to either the exposed period (if vaccination was given at cohort entry and the cohort exit date was reached within this exposed period) or nonexposed period (if the cohort exit date was reached before vaccination was given). See Figure 1 for a visualization of the self‐controlled cohort study design with some (of the many) examples of different exposed periods, nonexposed periods and cohort exit dates.
FIGURE 1.
Examples of time frames of the self‐controlled cohort study design.
2.3. GP databases
Data regarding age, sex, PMB, SARS‐CoV‐2 infection, HRT and comorbidity (cardiovascular disease, chronic lung disease, diabetes, malignancy, psoriasis, obesity, inflammatory bowel disease, chronic kidney disease, HIV) were collected over the years 2016–2021 from the Nivel (Nivel‐PCD) and PHARMO GP databases. These variables (except age and sex) were defined based on International Classification of Primary Care (ICPC) codes, Anatomical Therapeutic Chemical (ATC) codes, or a combination of ICPC and ATC codes. See Table S2 for the definition of covariates and risk groups.
Nivel‐PCD covers around 8–10% of the Dutch population 18 and the PHARMO GP database around 20% of the Dutch population. 19 Around 5% of persons were overlapping, i.e. present in both the Nivel and PHARMO database. This percentage was based on the source databases that were received from Nivel and PHARMO (as part of the pilot project described in the introduction) that included all persons aged ≥12 years who were registered in the respective databases in the year 2021. For the overlapping persons present in both the Nivel and PHARMO databases, the information from the PHARMO database was used. The PHARMO database also used free text fields to collect data, which could result in more complete data.
2.4. COVID‐19 vaccination data
Vaccinations were administered by several institutions in the Netherlands, but mainly by Municipal Health Services, GPs and in nursing homes. The National Institute for Public Health and the Environment (RIVM) collects all these vaccination data on a national level in the COVID Vaccination Information and Monitoring System (CIMS) database. 20 Persons that did not consent to share their data with the RIVM, i.e. around 6% of the Dutch vaccinated persons, are not included in CIMS. 21 From CIMS, data were collected on the vaccination date and vaccination brand per vaccination doses over the year 2021. This was supplemented with COVID‐19 vaccination data from the 2 GP databases of Nivel (Nivel‐PCD) and PHARMO, which allowed to obtain more complete COVID‐19 vaccination data. If a person had vaccination data available in both the GP databases and in CIMS, the vaccination data from CIMS was used. Several criteria were applied to clean the COVID‐19 vaccination data received from CIMS and the GP databases (Table S1).
2.5. PMB
PMB is defined as vaginal bleeding that occurs ≥1 year after the last menstrual period. The ICPC code ‘X12 Postmenopausal bleeding’ was used to collect data regarding PMB from the GP databases. The ICPC codes ‘R83.03 SARS‐CoV‐2 (COVID‐19)’ and ‘R83.04 Long COVID‐19’ were used to collect data regarding SARS‐CoV‐2 infection from the GP databases. All the above described data were received anonymized for data analyses.
2.6. Statistical analyses
Incidence rates (IR) and 95% confidence interval (CI) were calculated per 100 000 persons‐years for the exposed and nonexposed periods. The IR ratio (IRR) and 95% CI was then calculated by dividing the IR in the exposed period by the IR in the nonexposed period, using Poisson regression. Results were adjusted for SARS‐CoV‐2 infection, which was included as a time‐varying confounder during the follow‐up period in 2021.
COVID‐19 vaccines were analysed together, and results were then stratified by vaccine type (mRNA vs. vector vaccines) and vaccine brand (Pfizer/BioNTech, Moderna, AstraZeneca, and Johnson & Johnson). For the stratifications by vaccine type and vaccine brand, persons with a heterogeneous vaccine sequential (i.e. different vaccine types or vaccine brands administered over time for the same person) were excluded due to PMB may occur in the overlapping period between the vaccinations, which makes it not possible to determine to which vaccine type/brand this was attributed. Results were also stratified by the potential risk groups: age (categorized in 50–54, 55–64, 65–74 and ≥75 years) and HRT use (yes/no). Solely information on the prescription date of HRT was available and no information on for example the actual start date, duration of use or dosing. All data cleaning and data‐analysis was performed in RStudio version 4.2.2. P‐values < .05 were considered statistically significant.
3. RESULTS
A total of 692 760 COVID‐19 vaccinated women aged ≥50 years were included. The median age was 65 (interquartile range: 16) years. The majority of women were in the age category 55–64 years (n = 226 988; 32.8%), followed by 65–74 years (n = 19 672; 28.4%), ≥75 years (n = 152 453; 22%) and 50–54 years (n = 116 647; 16.8%). Also, the majority of women had cardiovascular disease (n = 270 274; 39%) and chronic lung disease (n = 147 492; 21.3%), see Table 1.
TABLE 1.
Characteristics of vaccinated women aged ≥50 years from the GP databases of Nivel and PHARMO from the year 2021.
| COVID‐19 vaccinated women aged ≥50 years (n = 692 760) | |
|---|---|
| Median age (IQR) | 65 (16) |
| Age in categories (years), n (%) | |
| 50–54 | 116 647 (16.8%) |
| 55–64 | 226 988 (32.8%) |
| 65–74 | 196 672 (28.4%) |
| ≥75 | 152 453 (22.0%) |
| Comorbidity, n (%) | |
| Cardiovascular disease | 270 274 (39%) |
| Chronic lung disease | 147 492 (21.3%) |
| Diabetes | 77 616 (11.2%) |
| Malignancy | 76 161 (11.0%) |
| Psoriasis | 20 598 (3.0%) |
| Obesity | 15 143 (2.2%) |
| Inflammatory Bowel Disease | 6505 (0.9%) |
| Chronic kidney disease | 1376 (0.2%) |
| HIV | 410 (0.0%) |
| Number of vaccinations per person, n (%) | |
| 1 | 38 407 (5.5%) |
| 2 | 252 040 (36.4%) |
| 3 | 402 279 (58.1%) |
| 4 | 34 (0.0%) |
| Total number of vaccinations by vaccine brand, n (%) | 1 749 460 (100.0%) |
| Pfizer/BioNTech | 1 118 882 (64.0%) |
| Moderna | 369 446 (21.1%) |
| AstraZeneca | 232 999 (13.3%) |
| Johnson & Johnson | 25 040 (1.4%) |
| Unknown | 3093 (0.2%) |
| Total number of vaccinations by age group and vaccine brand, n (%) | |
| 50–54 years | 245 768 (100.0%) |
| Pfizer/BioNTech | 158 439 (64.5%) |
| Moderna | 49 258 (20.0%) |
| AstraZeneca | 16 090 (6.5%) |
| Johnson & Johnson | 21 541 (8.8%) |
| Unknown | 440 (0.2%) |
| 55–64 years | 561 262 (100.0%) |
| Pfizer/BioNTech | 254 077 (45.3%) |
| Moderna | 110 069 (19.6%) |
| Astrazeneca | 192 836 (34.4%) |
| Johnson & Johnson | 3034 (0.5%) |
| Unknown | 1246 (0.2%) |
| 65–74 years | 523 320 (100.0%) |
| Pfizer/BioNTech | 386 721 (73.9%) |
| Moderna | 117 577 (22.5%) |
| AstraZeneca | 18 124 (3.5%) |
| Johnson & Johnson | 322 (0.0%) |
| Unknown | 576 (0.1%) |
| ≥75 years | 419 110 (100.0%) |
| Pfizer/BioNTech | 319 645 (76.3%) |
| Moderna | 92 542 (22.1%) |
| AstraZeneca | 5949 (1.4%) |
| Johnson & Johnson | 143 (0.0%) |
| Unknown | 831 (0.2%) |
| Total number of persons with a heterogeneous/homogeneous vaccine sequential based on vaccine type (mRNA vs. vector), n (%) | |
| Heterogeneous | 91 227 (13.2%) |
| Homogeneous | 601 533 (86.8%) |
| Total number of persons with a heterogeneous/homogeneous vaccine sequential based on vaccine brand (Pfizer/BioNTech, Moderna, AstraZeneca, Johnson & Johnson), n (%) | |
| Heterogeneous | 332 087 (47.9%) |
| Homogeneous | 360 673 (52.1%) |
| Follow‐up time in 2021, n (%) | |
| >0–3 months | 9326 (1.3%) |
| >3–6 months | 9412 (1.4%) |
| >6–9 months | 8872 (1.3%) |
| >9–12 months | 665 150 (96.0%) |
Abbreviations: HIV, human immunodeficiency virus; IQR, interquartile range.
Most of the women received 3 COVID‐19 vaccinations in 2021, in which Pfizer/BioNTech was the most administered vaccine brand (n = 1 118 882 vaccinations; 64%), followed by Moderna (n = 369 446 vaccinations; 21.1%), AstraZeneca (n = 232 999 vaccinations; 13.3%), and Johnson & Johnson (n = 25 040 vaccinations; 1.4%). With respect to vaccine type (mRNA vs. vector), n = 601 533 (86.8%) persons received a homogeneous vaccine sequence. With respect to vaccine brand (Pfizer/BioNTech, Moderna, AstraZeneca, Johnson & Johnson), n = 360 673 (52.1%) persons received a homogeneous vaccine sequence, see Table 1.
3.1. Risk of PMB after COVID‐19 vaccination by vaccination dose, vaccine type and vaccine brand
The analysis regarding all COVID‐19 vaccines showed no increase in GP consultations for PMB after COVID‐19 vaccination. When stratifying by vaccine type (i.e. mRNA vs. vector vaccine), also no increase in GP consultations was observed for PMB after the mRNA or vector vaccines. We then stratified by vaccine brand (Pfizer/BioNTech, Moderna, AstraZeneca, and Johnson & Johnson) and this analysis showed, although not statistically significant, the highest adjusted IRR after Moderna dose 2 (adjusted IRR: 1.47, 95% CI: 0.93–2.32) and Pfizer/BioNTech dose 3 (adjusted IRR: 1.33, 95% CI: 0.92–1.93; Table 2). Dose 2 of Johnson & Johnson, as well as dose 3 of Johnson & Johnson and AstraZeneca could not be analysed, as there were no persons in the study population who received this number of doses for these vaccine types).
TABLE 2.
IR and IRR with corresponding 95% CI for PMB in COVID‐19 vaccinated women aged ≥50 years, stratified by vaccine dose, vaccine type and vaccine brand.
| n | PY exposed | Events in exposed period | PY nonexposed | Events in nonexposed period (IR per 100 000 PY) | Unadjusted IRR (95% CI) | Adjusted IRR (95% CI)* | |
|---|---|---|---|---|---|---|---|
| (IR per 100 000 PY) | |||||||
| All COVID‐19 vaccines (including any and unknown vaccine brand) | |||||||
| Total, all vaccine doses | 692 760 | 114 192 | 687 (602) | 558 774 | 3464 (620) | 0.97 (0.89–1.05) | 0.95 (0.87–1.03) |
| Dose 1 † | 692 760 | 51 534 | 308 (598) | 558 774 | 3464 (620) | 0.96 (0.86–1.08) | 0.94 (0.83–1.05) |
| Dose 2 ‡ | 654 353 | 48 099 | 311 (647) | 524 878 | 3186 (607) | 1.07 (0.95–1.20) | 1.04 (0.92–1.16) |
| Dose 3 § | 402 313 | 14 557 | 68 (467) | 317 234 | 1743 (549) | 0.85 (0.67–1.08) | 0.85 (0.67–1.08) |
| By vaccine type, i.e. mRNA (Pfizer/BioNTech and Moderna) vs. vector vaccines (AstraZeneca and Johnson & Johnson) | |||||||
| mRNA vaccines, (≥1 vaccine) | |||||||
| Total, all vaccine doses | 544 167 | 91 730 | 541 (590) | 436 343 | 2674 (613) | 0.96 (0.88–1.06) | 0.94 (0.86–1.03) |
| Dose 1 † | 544 167 | 40 336 | 229 (568) | 436 343 | 2674 (613) | 0.93 (0.81–1.06) | 0.90 (0.79–1.03) |
| Dose 2 ‡ | 525 014 | 38 915 | 253 (650) | 419 605 | 2536 (604) | 1.08 (0.95–1.22) | 1.05 (0.92–1.19) |
| Dose 3 § | 327 720 | 12 468 | 59 (473) | 257 676 | 1378 (535) | 0.88 (0.68–1.15) | 0.88 (0.68–1.15) |
| Vector vaccines, (≥1 vaccine) | |||||||
| Total, all vaccine doses | 57 366 | 7305 | 51 (698) | 48 579 | 310 (638) | 1.09 (0.81–1.47) | 1.01 (0.76–1.37) |
| Dose 1 † | 57 366 | 4319 | 33 (764) | 48 579 | 310 (638) | 1.20 (0.84–1.71) | 1.11 (0.77–1.59) |
| Dose 2 ‡ | 39 781 | 2986 | 18 (603) | 32 858 | 179 (545) | 1.11 (0.68–1.80) | 1.02 (0.63–1.66) |
| Dose 3 § | NA | NA | NA | NA | NA | NA | NA |
| By vaccine brand, i.e. Pfizer/BioNTech, Moderna, AstraZeneca, Johnson & Johnson | |||||||
| Pfizer/BioNTech (≥1 vaccine) | |||||||
| Total, all vaccine doses | 275 105 | 43 176 | 301 (697) | 221 773 | 1523 (687) | 1.02 (0.90–1.15) | 0.97 (0.86–1.10) |
| Dose 1 † | 275 105 | 20 135 | 130 (646) | 221 773 | 1523 (687) | 0.94 (0.79–1.12) | 0.90 (0.75–1.07) |
| Dose 2 ‡ | 258 493 | 19 136 | 141 (737) | 207 292 | 1401 (676) | 1.09 (0.92–1.30) | 1.04 (0.87–1.23) |
| Dose 3 § | 84 750 | 3905 | 30 (768) | 64 965 | 373 (574) | 1.34 (0.92–1.94) | 1.33 (0.92–1.93) |
| Moderna (≥1 vaccine) | |||||||
| Total, all vaccine doses | 28 205 | 4111 | 30 (730) | 23 263 | 170 (731) | 1.00 (0.68–1.47) | 0.96 (0.65–1.41) |
| Dose 1 † | 28 205 | 2081 | 9 (432) | 23 263 | 170 (731) | 0.59 (0.30–1.16) | 0.57 (0.29–1.11) |
| Dose 2 ‡ | 25 664 | 1899 | 21 (1106) | 21 006 | 154 (733) | 1.51 (0.96–2.38) | 1.47 (0.93–2.32) |
| Dose 3 § | 7536 | 130 | NA | 6130 | 49 (799) | NA | NA |
| AstraZeneca (≥1 vaccine) | |||||||
| Total, all vaccine doses | 42 425 | 6183 | 39 (631) | 35 100 | 191 (544) | 1.16 (0.82–1.64) | 1.08 (0.76–1.52) |
| Dose 1 † | 42 425 | 3198 | 21 (657) | 35 100 | 191 (544) | 1.21 (0.77–1.89) | 1.11 (0.71–1.75) |
| Dose 2 ‡ | 39 774 | 2986 | 18 (603) | 32 852 | 179 (545) | 1.11 (0.68–1.80) | 1.02 (0.63–1.66) |
| Dose 3 § | NA | NA | NA | NA | NA | NA | NA |
| Johnson & Johnson (≥1 vaccine) ǁ | |||||||
| Total, all vaccine doses | 14 938 | 1.122 | 12 (1070) | 13 477 | 119 (883) | 1.21 (0.67–2.19) | 1.14 (0.63–2.06) |
Abbreviations: 95% CI: 95% confidence interval; IR: incidence rate; IRR: IR ratio; NA: not applicable due to zero cell counts; PY: person‐years. For dose 3 of the vector vaccines and AstraZeneca, this is due to that there were no persons in the study population that had received 3 doses of a vector vaccine or 3 AstraZeneca doses.
Adjusted for SARS‐CoV‐2 infection as time‐varying confounder during follow‐up in 2021.
Including only persons who received the first dose.
Including only persons who received the second dose.
Including only persons who received the third dose.
Although a single dose was required for Johnson & Johnson, there were n = 4 persons who received 2 doses.
3.2. Potential risk groups for PMB after COVID‐19 vaccination
We analysed whether age (in categories) and HRT users (yes/no) were potential risk groups for experiencing PMB after COVID‐19 vaccination. In line with the previous analysis, the data were first analysed for all COVID‐19 vaccines together and were then stratified by vaccine type and vaccine brand. In general, slightly more GP consultations for PMB after COVID‐19 vaccination were observed for HRT users (except for Moderna); however, none of the results were statistically significant. In addition, none of the age categories showed statistically significant increased GP consultations for PMB after COVID‐19 vaccination (Table 3).
TABLE 3.
IR and IRR with corresponding 95% CI for PMB in COVID‐19 vaccinated women aged ≥50 years, stratified by the potential risk groups (age in category and HRT), and by vaccine type and vaccine brand.
| n | PY exposed | Events in exposed period | PY nonexposed | Events in nonexposed period (IR per 100 000 PY) | Unadjusted IRR (95% CI) | Adjusted IRR (95% CI)* | |
|---|---|---|---|---|---|---|---|
| (IR per 100 000 PY) | |||||||
| All COVID‐19 vaccines (including any and unknown vaccine brand) | |||||||
| 50–54 years | 116 647 | 16 414 | 163 (993) | 97 403 | 969 (995) | 1.00 (0.85–1.18) | 0.96 (0.81–1.13) |
| 55–64 years | 226 988 | 36 254 | 250 (690) | 185 292 | 1241 (670) | 1.03 (0.90–1.18) | 1.00 (0.87–1.14) |
| 65–74 years | 196 672 | 33 266 | 145 (436) | 158 716 | 743 (468) | 0.93 (0.78–1.11) | 0.91 (0.76–1.09) |
| ≥75 years | 152 453 | 28 259 | 129 (456) | 117 363 | 511 (435) | 1.05 (0.86–1.27) | 1.04 (0.86–1.27) |
| HRT yes | 100 835 | 16 066 | 177 (1102) | 81 807 | 876 (1071) | 1.03 (0.88–1.21) | 1.01 (0.86–1.18) |
| HRT no | 591 925 | 98 125 | 510 (520) | 476 967 | 2588 (543) | 0.96 (0.87–1.05) | 0.94 (0.85–1.03) |
| By vaccine type, i.e. mRNA (Pfizer/BioNTech and Moderna) vs. vector vaccines (AstraZeneca and Johnson & Johnson) | |||||||
| mRNA vaccines, (≥1 vaccine) | 544 167 | ||||||
| 50–54 years | 86 388 | 13 094 | 132 (1008) | 71 185 | 726 (1020) | 0.99 (0.82–1.19) | 0.95 (0.79–1.14) |
| 55–64 years | 123 031 | 19 306 | 148 (767) | 100 662 | 764 (759) | 1.01 (0.85–1.20) | 0.98 (0.82–1.17) |
| 65–74 years | 186 427 | 31 644 | 137 (433) | 150 371 | 691 (460) | 0.94 (0.78–1.13) | 0.92 (0.76–1.10) |
| ≥75 years | 148 321 | 27 685 | 124 (448) | 114 126 | 493 (432) | 1.04 (0.85–1.26) | 1.03 (0.85–1.26) |
| HRT yes | 78 800 | 12.953 | 143 (1104) | 63 478 | 692 (1090) | 1.01 (0.85–1.21) | 0.99 (0.83–1.19) |
| HRT no | 465 367 | 78.776 | 398 (505) | 372 865 | 1982 (532) | 0.95 (0.85–1.06) | 0.93 (0.84–1.04) |
| Vector vaccines, (≥1 vaccine) | 57 366 | ||||||
| 50–54 years | 16 538 | 1464 | 16 (1093) | 14 697 | 131 (891) | 1.23 (0.73–2.06) | 1.14 (0.68–1.92) |
| 55–64 years | 35 643 | 5141 | 32 (622) | 29 668 | 150 (506) | 1.23 (0.84–1.80) | 1.14 (0.78–1.67) |
| 65–74 years | 3319 | 457 | < 5 (437) | 2743 | 20 (729) | 0.60 (0.14–2.57) | 0.60 (0.14–2.58) |
| ≥75 years | 1866 | 244 | < 5 (411) | 1472 | 9 (611) | 0.67 (0.09–5.30) | 0.63 (0.08–4.99) |
| HRT yes | 8881 | 995 | 11 (1105) | 7656 | 67 (875) | 1.26 (0.67–2.39) | 1.17 (0.62–2.22) |
| HRT no | 48 485 | 6310 | 40 (634) | 40 923 | 243 (594) | 1.07 (0.76–1.49) | 1.00 (0.71–1.40) |
| By vaccine brand, i.e. Pfizer/BioNTech, Moderna, AstraZeneca, Johnson & Johnson | |||||||
| Pfizer/BioNTech (≥1 vaccine) | 275 105 | ||||||
| 50–54 years | 60 225 | 8957 | 98 (1094) | 49 752 | 528 (1061) | 1.03 (0.83–1.28) | 0.98 (0.79–1.22) |
| 55–64 years | 77 740 | 11 907 | 88 (739) | 63 837 | 485 (760) | 0.97 (0.78–1.22) | 0.94 (0.75–1.18) |
| 65–74 years | 78 034 | 12 239 | 60 (490) | 63 613 | 295 (464) | 1.06 (0.80–1.40) | 0.99 (0.75–1.31) |
| ≥75 years | 59 106 | 10 074 | 55 (546) | 44 572 | 215 (482) | 1.13 (0.84–1.52) | 1.10 (0.82–1.49) |
| HRT yes | 43 499 | 6766 | 83 (1227) | 35 247 | 403 (1143) | 1.07 (0.85–1.36) | 1.04 (0.82–1.32) |
| HRT no | 231 606 | 36 410 | 218 (599) | 186 527 | 1120 (600) | 1.00 (0.86–1.15) | 0.96 (0.83–1.11) |
| Moderna (≥1 vaccine) | 28 205 | ||||||
| 50–54 years | 11 614 | 1700 | 11 (647) | 9671 | 83 (858) | 0.75 (0.40–1.41) | 0.73 (0.39–1.37) |
| 55–64 years | 13 154 | 1945 | 14 (720) | 10 921 | 70 (641) | 1.12 (0.63–1.99) | 1.07 (0.60–1.90) |
| 65–74 years | 1979 | 281 | < 5 (712) | 1601 | 12 (750) | 0.95 (0.21–4.24) | 0.87 (0.19–3.88) |
| ≥75 years | 1485 | 185 | < 5 (1623) | 1070 | 5 (467) | 3.69 (0.84–16.14) | 3.69 (0.84–16.14) |
| HRT yes | 6601 | 979 | < 5 (408) | 5466 | 54 (988) | 0.41 (0.15–1.14) | 0.39 (0.14–1.09) |
| HRT no | 21 604 | 3.131 | 26 (830) | 17 798 | 116 (652) | 1.27 (0.83–1.95) | 1.23 (0.80–1.89) |
| AstraZeneca (≥1 vaccine) | 42 425 | ||||||
| 50–54 years | 3087 | 452 | 5 (1105) | 2555 | 19 (744) | 1.49 (0.56–3.98) | 1.30 (0.48–3.50) |
| 55–64 years | 34 547 | 5.06 | 31 (613) | 28 685 | 143 (99) | 1.23 (0.83–1.81) | 1.14 (0.77–1.68) |
| 65–74 years | 3041 | 437 | < 5 (458) | 2492 | 20 (802) | 0.57 (0.13–2.44) | 0.57 (0.13–2.43) |
| ≥75 years | 1750 | 235 | < 5 (426) | 1367 | 9 (658) | 0.65 (0.08–5.11) | 0.61 (0.08–4.81) |
| HRT yes | 4649 | 677 | 7 (1034) | 3833 | 32 (835) | 1.24 (0.55–2.80) | 1.14 (0.50–2.58) |
| HRT no | 37 776 | 5.506 | 32 (581) | 31 267 | 159 (509) | 1.14 (0.78–1.67) | 1.07 (0.73–1.56) |
| Johnson & Johnson (≥1 vaccine) † | 14 938 | ||||||
| 50–54 years | 13 451 | 1.011 | 11 (1088) | 12 141 | 112 (922) | 1.18 (0.63–2.19) | 1.11 (0.60–2.06) |
| 55–64 years | 1093 | 81 | < 5 (1235) | 980 | 7 (714) | 1.73 (0.21–14.05) | 1.56 (0.19–12.65) |
| 65–74 years | 278 | 21 | NA | 251 | NA | NA | NA |
| ≥75 years | 116 | 9 | NA | 105 | NA | NA | NA |
| HRT yes | 4232 | 318 | < 5 (1257) | 3824 | 35 (915) | 1.37 (0.49–3.87) | 1.29 (0.46–3.63) |
| HRT no | 10 706 | 804 | 8 (996) | 9654 | 84 (870) | 1.14 (0.55–2.36) | 1.08 (0.52–2.23) |
Abbreviations: 95% CI: 95% confidence interval; HRT, hormone replacement therapy; IR: incidence rate; IRR: IR ratio; NA: not applicable due to zero cell counts; PY: person‐years.
Adjusted for SARS‐CoV‐2 infection as time‐varying confounder during follow‐up in 2021.
Although a single dose was required for Johnson & Johnson, there were n = 4 persons who received 2 doses.
4. DISCUSSION
In this self‐controlled cohort study, based on 2 representative GP databases and the national COVID‐19 vaccination database from the Netherlands, we did not find an increase in GP consultations for PMB after COVID‐19 vaccination. No increase was observed for any vaccine dose (dose 1, 2 or 3), vaccine type (mRNA vs. vector vaccine) or vaccine brand (Pfizer/BioNTech, Moderna, AstraZeneca, and Johnson & Johnson), and neither for any of the potential risk groups (age groups and HRT use).
The association between PMB and COVID‐19 vaccination has rarely been described, and the limited published studies show inconsistent results. A few studies found increased risks of PMB after COVID‐19 vaccination. For example, a Norwegian study 11 that used self‐reported data from questionnaires to investigate the association between COVID‐19 vaccination and PMB in 2021 showed that there was a 2–3 times higher risk of PMB in the 4 weeks after COVID‐19 vaccination compared to the prevaccination period, especially after the first dose and after Pfizer/BioNTech vaccination. Interestingly, this study showed that only 30.6% of postmenopausal women sought medical help and more interestingly, women more rarely sought medical help when bleeding occurred during the first 4 weeks after vaccination, as compared to before vaccination. 11 This means that lower risk estimates are expected from a diagnosis‐based approach compared to a self‐reported approach, which could explain why in our study (which is based on GP consultations) we did not observe an increased risk of PMB after COVID‐19 vaccination. In addition, we cannot rule out that PMB was underreported to some extend based on GP data if women were referred to a specialist doctor.
Another large cohort study 15 from Sweden among 1 561 429 postmenopausal women aged 45–74 years, showed increased risks of PMB after the second and third COVID‐19 dose (after a risk window of 8–90 days), with the highest risk after the third COVID‐19 vaccination dose both in the 1–7 days risk window (adjusted hazard ratio [HR] 1.28, 95% CI 1.01–1.62) and the 8–90 days risk window (adjusted HR 1.25, 95% CI 1.04–1.50. When stratified by vaccine brand, a 23–33% increased risk of PMB was observed after the third dose of Pfizer/BioNTech and Moderna (after a risk window of 8–90 days), while for AstraZeneca a 17% increased risk was seen after the first dose (after a risk window of 8–90 days). 15 These results were based on healthcare contacts registered as outpatient specialist visits or inpatient stays from the Swedish national patient register. However, in an additional analysis which was restricted to a subpopulation (i.e. 590 271 postmenopausal women aged 45–74 years living in the 2 largest metropolitan areas, approximately 40% of total population) with primary healthcare data, risks were in general lower and not significant, which was in line with findings from our study. Although the authors did not elaborate on this, it could possibly be due to the relatively small sample size used in the subpopulation analysis, which was similar to the sample used in our study. Considering the number of included persons in our study, there was 80% power to find an IRR of 1.1 in the exposed period compared to the nonexposed period.
By contrast, Kauffman et al. 14 investigated the incidence of PMB diagnosis based on electronic healthcare data (i.e. outpatient, urgent care, emergency department or hospital setting) in the periods before and after COVID‐19 vaccination introduction. The study did not find an increased risk of PMB after COVID‐19 vaccination, which was in line with our study. In March 2024 the Pharmacovigilance Risk Assessment Committee, which is the safety committee of the European Medicines Agency, concluded that there was insufficient evidence of a causal association between PMB and the COVID‐19 vaccines Pfizer/BioNTech and Moderna. 22 This conclusion was made after assessing all available data, including findings from literature and available postmarketing spontaneous reports of suspected adverse reactions.
While HRT can be used to treat symptoms of menopause, like hot flashes and night sweats, it can also cause vaginal bleeding. 23 , 24 However, studies show inconsistent results on the risk of PMB after COVID‐19 vaccination among HRT users and nonusers. Although not statistically significant, in our study slightly increased GP consultations for PMB after COVID‐19 vaccination were observed among women that used HRT (except for women vaccinated with Moderna). In Ljung et al., 15 when restricting the analyses to women without prior hormone treatment, increased risks were still observed after the second and third COVID‐19 vaccination dose (after a risk window of 8–90 days), with slightly higher estimates than in the main analyses which included the total study population. Blix et al., 11 showed that the risk of PMB after COVID‐19 vaccination was similar between postmenopausal women using hormone therapy (adjusted HR: 2.8, 95% CI: 1.5–5.2) vs. nonusers (adjusted HR: 2.9, 95% CI: 1.7–4.9).
In around 10% of postmenopausal women, the underlying cause of vaginal bleeding is attributed to a (malignant) cause, such as uterine cancer, cervical cancer or uterine polyps. 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 Unfortunately, we were not able to investigate this since this information is probably highly underreported in GP databases, as the symptom code of PMB is not always replaced with a more precise code describing the actual cause of PMB in the GP database (especially not if no serious underlying cause is found and the symptoms have disappeared or symptom severity has decreased).
A strength of our study is the use of a large, well‐designed cohort study design based on 2 representative GP databases from the Netherlands. 18 , 25 An advantage of such a self‐controlled study design is that it automatically controls for all fixed and unknown/unmeasured confounders. It remains necessary to control for time‐varying confounders, such as SARS‐CoV‐2 infection or changes in HRT. A limitation of our study is that data on SARS‐CoV‐2 infection is probably underreported in the GP databases. This is because a person needs to give permission to share these data with their GP or report this to their GP themselves, due to a COVID‐19 specific ICPC code not being available until mid‐2020, and because a positive test taken at home may not always have been confirmed with a PCR test. In addition, it is estimated that the CIMS COVID‐19 database misses around 6% of the Dutch vaccinated persons who did not give permission to share their data with the RIVM. 21 There could be selection bias in who gave permission and who did not. However, in order to have more complete COVID‐19 vaccination data, we collected these data from the GP databases in addition to the CIMS database.
Also, we were unable to correct for possible changes in HRT, as we solely had information on the prescription date and not on for example changes in HRT dosing.
Primary healthcare is organized differently around the world. In the Netherlands, the GP is the first point of contact for any health issues, and patients are only referred to secondary specialist care when medically necessary. As a result, women generally do not have direct access to gynaecological specialists solely for routine women's health concerns. This contrasts with other countries, where women might regularly see a gynaecologist through private practices or specialized clinics outside the GP system. Menopausal complaints are diagnosed by the GP based on the patient's history and a physical examination. Testing for follicle stimulating hormone, luteinizing hormone and oestradiol is not recommended, as it does not improve the accuracy of the diagnosis or help predict the age of menopause. 26 This approach may differ from the diagnostic procedure by gynaecologists.
Some misclassification of the reproductive stages may be present, similar to what has been described in the study by Blix et al. 11 Women who have entered menopause earlier, due to various health or genetic conditions, may have been missed. By contrast, not all women in the youngest age group may have reached the menopause, thus menopausal women can be overestimated in this age group.
In conclusion, in our retrospective self‐controlled cohort study based on primary healthcare data from 2 large GP databases from the Netherlands, we did not observe an increase in GP consultations for PMB after COVID‐19 vaccination. No increased GP consultations for PMB were observed for any of the COVID‐19 vaccine brands and vaccine doses, nor for the potential risk groups. However, a possible relation between PMB and COVID‐19 vaccination could in reality be plausible taken into account that some of the subanalyses might not have sufficient power to identify a possible risk and that women with PMB might not seek medical help, meaning the risk is underreported based on a diagnosis approach. Further studies could elaborate on this.
AUTHOR CONTRIBUTIONS
Jajou, R.: conceptualization, methodology, software, data curation, formal analysis, investigation, visualization, project administration, writing—original draft, writing—review and editing. van Puijenbroek, E.P.: conceptualization, writing—review and editing. Overbeek, J.A.: conceptualization, data curation, writing—review and editing. Veldkamp, R.: conceptualization, data curation, writing—review and editing. Van Hunsel, F.P.A.M.: conceptualization, writing—review and editing. Kant, A.C.: conceptualization, writing—review and editing.
CONFLICT OF INTEREST STATEMENT
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
ETHICS APPROVAL STATEMENT AND PATIENT CONSENT STATEMENT
Obtaining informed consent from patients or approval by a medical ethics committee is not obligatory for observational studies containing no directly identifiable data (Dutch Civil Law, Article 7: 458). The study was approved according to the governance code of Nivel‐PCD (number: NZR‐00322.008) and by the institutional review board of STIZON, Utrecht, Netherlands (document number: CC2022–13).
PERMISSION TO REPRODUCE MATERIAL FROM OTHER SOURCES
Permission must be obtained from the corresponding author to reproduce material from the manuscript by third parties.
Supporting information
TABLE S1 Criteria applied to clean the COVID‐19 vaccination data received from the COVID Vaccination Information and Monitoring System (CIMS) and the GP databases.
TABLE S2 Definition of covariates and risk groups based on ICPC codes or a combination of ICPC and ATC codes, extracted from the GP systems over the years 2016–2021.
ACKNOWLEDGEMENTS
We would like to thank Erik Mulder, data‐scientist at the Netherlands Pharmacovigilance Centre Lareb, for helping in preparing the data analyses file.
Jajou R, van Puijenbroek EP, Veldkamp R, Overbeek JA, van Hunsel FPAM, Kant AC. General practitioner consultation for postmenopausal bleeding after COVID‐19 vaccination—a self‐controlled cohort study. Br J Clin Pharmacol. 2025;91(8):2352‐2362. doi: 10.1002/bcp.70045
Funding information This research was part of a project which received funding from the Ministry of Health, Welfare and Sport (grant number SP332956). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
DATA AVAILABILITY STATEMENT
The data that support the findings are not publicly available due to privacy reasons.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
TABLE S1 Criteria applied to clean the COVID‐19 vaccination data received from the COVID Vaccination Information and Monitoring System (CIMS) and the GP databases.
TABLE S2 Definition of covariates and risk groups based on ICPC codes or a combination of ICPC and ATC codes, extracted from the GP systems over the years 2016–2021.
Data Availability Statement
The data that support the findings are not publicly available due to privacy reasons.