Regular Use of Proton Pump Inhibitor and Risk of Rheumatoid Arthritis in Women

A Prospective Cohort Study

Jinqiu Yuan; Changhua Zhang; Jeffrey A. Sparks; Susan Malspeis; Kelvin Kam-Fai Tsoi; Jean H. Kim; Benjamin A. Fisher; Fang Gao; Tim Sumerlin; Yan Liu; Yuxing Liu; Yihang Pan; Yulong He; Joseph J.Y. Sung

Disclosures

Aliment Pharmacol Ther. 2020;52(3):449-458. 

In This Article

Methods

Study Population

The NHS originally enrolled 121 700 female nurses from 11 US states aged 30–55 years in 1976. The NHS II, established in 1989, included 116 430 younger female registered nurses who were between the ages of 25 and 42 years from 14 states in the US. The participants have received a biennial questionnaire since baseline to collect data on demographics, health-related behaviours, medical history and newly diagnosed diseases, with a follow-up completion rate of over 90% for each questionnaire cycle. The recruitment and data collection in NHS and NHS II have been reported in detail previously.[16] In the present study, we included women who reported PPI use data and excluded those with a self-report of RA. We also excluded systemic lupus erythematosus (SLE) which is another rheumatic autoimmune disease evaluated in nurse health studies. The NHS and NHS II were approved by the Human Research Committee at the Brigham and Women's Hospital, Boston, MA. The study protocol was approved by the Institutional Review Board (IRB) of the Brigham and Women's Hospital, and the IRB allowed participants' completion of questionnaires to be considered as implied consent.

Assessment of PPI/H2 Receptor Antagonist (H2RA) use

In the 2000, 2002 questionnaire in NHS, and the 2001, 2003 questionnaire in NHS II, participants were asked whether, over the previous 2 years, they had regularly used "Prilosec or Prevacid". In the biennial surveys after 2002 for NHS and after 2003 for NHS II, participants were asked whether, over the previous 2 years, they had regularly used "Prilosec, Prevacid (lansoprazole), Protonix, Nexium, or Aciphex." In the 2000 questionnaire in NHS, and the 2001 questionnaire in NHS II, participants were asked whether, over the previous 2 years, they "had regularly used cimetidine or other H2 receptor antagonist (H2RAs; e.g. Zantac, Pepcid, etc.)." In the biennial surveys after 2000 for NHS and after 2001 for NHS II, the participants were asked whether they "had regularly used any H2RAs (e.g. Zantac, cimetidine, Pepcid, Axid, etc.)". Data about the dose, brand or type of PPI were not collected.

Ascertainment of RA

The ascertainment of RA was reported in previous studies.[17,18] In brief, we identified RA cases by sending a connective tissue disease screening questionnaire[19] to those who self-reported a diagnosis of RA. For those who screened positive, we checked the medical records to confirm the diagnosis and collect symptom/diagnosis dates and serological status. Two board-certified rheumatologists reviewed the medical records to confirm RA according to the 1987 or 2010 American College of Rheumatology classification criteria.[20,21] Seropositive RA was defined by the presence of either rheumatoid factor (RF) or anti-cyclic citrullinated peptide (anti-CCP) antibodies, and seronegative RA by the absence of a positive test. The end of follow-up was 1 June 2014 for the NHS and 1 June 2015 for the NHS II.

Assessment of Covariates

We selected covariates that may confound the association based on review of previous literature.[8,22] In the baseline and biennial follow-up questionnaires, we obtained updated information on age, ethnicity, family history of RA, body mass index (BMI), smoking, alcohol intake, menopausal status and postmenopausal hormone use, parity, breastfeeding, comorbidities (hypertension, diabetes, hypercholesterolemia, cancer, gastric or duodenal ulcer, and gastro-oesophageal reflux disease) and drugs that are likely related to PPI and RA (H2RAs, non-steroidal anti-inflammatory drugs (NSAIDs), and steroids). We calculated the 2010 Alternative Healthy Eating Index (AHEI-2010) to assess overall diet quality. Physical activity was measured by weekly expenditure of metabolic equivalents (METs) which has been validated in a previous study.[23]

Statistical Analysis

We calculated person-years from the date of return of the baseline questionnaire to the date of diagnosis of RA, death or the end of follow-up, whichever came first. We evaluated the hazard ratios (HRs) and 95% confidence intervals (CIs) with multivariable time-dependent Cox proportional hazards models accounting for potential time-varying effects in the exposure and covariates. We tested the assumption of proportional hazards by evaluating the interaction between age and main exposure in the age, period-stratified model. PPI use data were collected since 2000 in NHS and 2001 in NHS II and the baseline was 2002 for NHS and 2003 for NHS II. We lagged the exposure for 2 years to reduce the potential influence that subclinical RA symptoms may be related to PPI use and allow a time window for RA risk development. The time-dependent Cox models lagged the exposure by testing the associations between exposure of each biennial surveys (e.g. 2000) with the RA observed 2 years later (e.g. 2002–2004). Because the number of events, particularly for seronegative RA cases, was low in each individual cohort, we pooled the effect of NHS and NHS II with a one-step method[24] (directly evaluate the effect based on individual data of the two cohorts) to achieve adequate model convergence. The Cox-regression models were stratified by age, period and study to control the potential influence.

We coded the participants with missing covariate data to the reference group or median value group when the missing rate was low (<1%). When the rate of missing data was ≥1%, a separate missing response category was created. In the basic model, we stratified the analyses jointly by age (months), the year that the questionnaire was returned and cohort (NHS and NHS II). In the multivariable-adjusted model 1, we adjusted for race, history of RA in a first-degree relative, BMI, menopausal status and postmenopausal hormone use, number of parity, breastfeeding. Because PPIs were often prescribed along with other drugs, we also included regular use of NSAIDs, steroids in model 1 to control the potential confounding effects. To control the potential confounding from comorbidities, we additionally adjusted for hypertension, diabetes, hypercholesterolemia, cancer, gastric or duodenal ulcer, and gastro-oesophageal reflux disease in the multivariable-adjusted model 2. In the multivariable-adjusted model 3, we additionally controlled for lifestyle factors, including pack of cigarettes per years, days with alcohol drinking per week, physical activity and overall diet quality.

To test whether the association between PPI use and RA might be due to its effect on gastric acid suppression, we evaluated regular use of H2RA, a less potent acid suppressor with similar indications as PPI, and risk of RA. If acid suppression plays a role in RA development, it is expected that H2RA would have less or no effect on RA risk.[25] To verify if the association between PPI and RA was confounded by unknown factors, we used falsification analyses by testing implausible associations (basal cell skin cancer, squamous cell skin cancer and cervical cancer).[26] If PPI also showed associations with these implausible endpoints, its association with RA may be confounded by unknown factors.

To verify potential interaction effects, we undertook subgroup analysis according to cohort, age, BMI, family history of RA, menopausal status, breastfeeding time for their children, smoking and regular use of NSAIDs. Additionally, we performed a number of sensitivity analyses to check the robustness of the primary results. First, we lagged the exposure for even longer time (4 years) to further address potential reverse causation. Second, we pooled the effect of NHS and NHS II with a two-step method (evaluating the effect within each cohort and then pooling effect with inverse variance weighted random effect meta-analyses).[24] Third, to investigate the potential bias from healthcare utilisation (i.e. the participants with better healthcare utilisation are likely to have a better access to PPIs and lower chance to be undiagnosed if they had RA), we adjusted physical examination in the previous 2 years (yes or no) as a surrogate indicator. Fourth, we adjusted any use of antibiotics (yes or no) to investigate the effects of other medications that may have major influence on gut microbiota. Antibiotic use could also be considered as a surrogate indicator for infections that might be linked with RA. Fifth, we used different methods for missing data (multiple imputation and complete case analysis). Sixth, to investigate potential time-varying confounding in the primary model, we analysed the association with marginal structural model.[27,28] Last, to reduce the variability of underlying diseases requiring PPIs therapy, we restricted the analysis in women with gastro-oesophageal reflux disease, which is the most common indication for PPIs. We performed the analyses using SAS software, version 9.4 (SAS Institute).

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