Evaluating the use of methods to mitigate bias from non-transient medications in the case-crossover design: A systematic review

PURPOSE

The case-crossover design is a self-controlled study design used to compare exposure immediately preceding an event occurrence with exposure in earlier control periods. The design is most suitable for transient exposures in order to avoid biases that can be problematic when using the case-crossover design for non-transient (i.e., chronic) exposures. Our goal was to conduct a systematic review of case-crossover studies and its variants (case-time-control and case-case-time-control) in order to compare design and analysis choices by medication type.

METHODS

We conducted a systematic search to identify recent case-crossover, case-time-control, and case-case-time-control studies focused on medication exposures. Articles indexed in MEDLINE and EMBASE using these study designs that were published between January 2015 and December 2021 in the English language were identified. Reviews, methodological studies, commentaries, articles without medications as the exposure of interest, and articles with no available full text were excluded. Study characteristics including study design, outcome, risk window, control window, reporting of discordant pairs, and inclusion of sensitivity analyses were summarized overall and by medication type. We further evaluated the implementation of recommended methods to account for biases introduced by non-transient exposures among articles that used the case-crossover design on a non-transient exposure.

RESULTS

Of the 2036 articles initially identified, 114 articles were included. The case-crossover was the most common study design (88%), followed by the case-time-control (17%), and case-case-time-control (3%). Fifty-three percent of the articles included only transient medications, 35% included only non-transient medications, and 12% included both. Across years, the proportion of case-crossover articles evaluating a non-transient medication ranged from 30% in 2018 to 69% in 2017. We found that 41% of the articles that evaluated a non-transient medication did not apply any of the recommended methods to account for biases and more than half of which were conducted by authors with no previous publication history of case-crossover studies.

CONCLUSION

Using the case-crossover design to evaluate a non-transient medication remains common in pharmacoepidemiology. Researchers should apply appropriate design and analysis choices when opting to use a case-crossover design with non-transient medication exposures.

Medications influencing the risk of fall-related injuries in older adults: case-control and case-crossover design studies

BACKGROUND

Medications influencing the risk of fall-related injuries (FRIs) in older adults have been inconsistent in previous guidelines. This study employed case-control design to assess the association between FRIs and medications, and an additional case-crossover design was conducted to examine the consistency of the associations and the transient effects of the medications on FRIs.

METHODS

This study was conducted using a national claims database (2002-2015) in Korea. Older adults (≥ 65 years) who had their first FRI between 2007 and 2015 were matched with non-cases in 1:2 ratio. Drug exposure was examined for 60 days prior to the date of the first FRI (index date) in the case-control design. The hazard period (1-60 days) and two control periods (121-180 and 181-240 days prior to the index date) were investigated in the case-crossover design. The risk of FRIs with 32 medications was examined using conditional logistic regression after adjusting for other medications that were significant in the univariate analysis. In the case-crossover study, the same conditional model was applied.

RESULTS

In the case-control design, the five medications associated with the highest risk of FRIs were muscle relaxants (adjusted odd ratio(AOR) = 1.35, 95% confidence interval (CI) = 1.31-1.39), anti-Parkinson agents (AOR = 1.30, 95%CI = 1.19-1.40), opioids (AOR = 1.23, 95%CI = 1.19-1.27), antiepileptics (AOR = 1.19, 95%CI = 1.12-1.26), and antipsychotics (AOR = 1.16, 95%CI = 1.06-1.27). In the case-crossover design, the five medications associated with the highest risk of FRIs were angiotensin II antagonists (AOR = 1.87, 95%CI = 1.77-1.97), antipsychotics (AOR = 1.63, 95%CI = 1.42-1.83), anti-Parkinson agents (AOR = 1.58, 95%CI = 1.32-1.85), muscle relaxants (AOR = 1.42, 95%CI = 1.35-1.48), and opioids (AOR = 1.35, 95%CI = 1.30-1.39).

CONCLUSIONS

Anti-Parkinson agents, opioids, antiepileptics, antipsychotics, antidepressants, hypnotics and sedatives, anxiolytics, muscle relaxants, and NSAIDs/antirheumatic agents increased the risk of FRIs in both designs among older adults. Medications with a significant risk only in the case-crossover analysis, such as antithrombotic agents, calcium channel blockers, angiotensin II antagonists, lipid modifying agents, and benign prostatic hypertrophy agents, may have transient effects on FRIs at the time of initiation. Corticosteroids, which were only associated with risk of FRIs in the case-control analysis, had more of cumulative than transient effects on FRIs.

Risk of parkinsonism and related movement disorders with gabapentinoids or tramadol: A case-crossover study

INTRODUCTION

A safety signal concerning parkinsonism and related movement disorders with gabapentinoids (gabapentin and pregabalin) or tramadol was detected by reviewing individual case reports and data mining in spontaneous report databases. Well-designed pharmacoepidemiological studies are needed to assess the signal.

OBJECTIVE

This study aimed to investigate the association of exposure to gabapentinoids or tramadol with the risk of parkinsonism and related movement disorders.

METHODS

We conducted a case-crossover study using a Japanese electronic medical records database. Patients with newly diagnosed parkinsonism or related movement disorders between January 1, 2007, and April 14, 2019, were identified. The diagnosis date of outcomes was defined as the index date. We assessed the exposure of each patient to gabapentinoids or tramadol during a 90-day hazard period ending 1 day before the index date and in three 90-day reference periods. Multivariable conditional logistic regression models were employed to estimate adjusted odds ratios (aORs) and 95% confidence intervals (CIs). To confirm the robustness of the primary findings, we also performed sensitivity analyses using a case-case-time-control design, a different time window for hazard and reference periods, a different definition of outcome, and different number of reference periods.

RESULTS

A total of 28,972 eligible cases were included in the primary analysis. Exposure to gabapentinoids (aOR, 2.12; 95% CI, 1.73-2.61) and tramadol (aOR, 2.04; 95% CI, 1.57-2.64) was associated with increased risk. Results were consistent across sensitivity analyses.

CONCLUSION

Our findings serve as a caution to physicians who prescribe gabapentinoids or tramadol in routine clinical practice.

Risk of drug-induced interstitial lung disease in hospitalised patients: a nested case-control study

INTRODUCTION

Information on drug-induced interstitial lung disease (DILD) is limited due to its low incidence. This study investigated the frequencies of drug categories with potential risk in patients developing DILD during hospitalisation and analysed the risk of developing DILD associated with each of these drugs.

METHODS

Using a Japanese national inpatient database, we identified patients without interstitial pneumonia on admission who developed DILD and required corticosteroid therapy during hospitalisation from July 2010 to March 2016. We conducted a nested case-control study; four controls from the entire non-DILD patient cohort were matched to each DILD case on age, sex, main diagnosis, admission year and hospital. We defined 42 classified categories of drugs with 216 generic names as drugs with potential risk of DILD, and we identified the use of these drugs during hospitalisation for each patient. We analysed the association between each drug category and DILD development using conditional logistic regression analyses.

RESULTS

We retrospectively identified 2342 patients who developed DILD. After one-to-four case-control matching, 1541 case patients were matched with 5677 control patients. Six drug categories were significantly associated with the increased occurrence of DILD. These included epidermal growth factor receptor inhibitors (OR: 16.84, 95% CI 9.32 to 30.41) and class III antiarrhythmic drugs (OR: 7.01, 95% CI 3.86 to 12.73). Statins were associated with reduced risk of DILD (OR: 0.68, 95% CI 0.50 to 0.92).

CONCLUSIONS

We demonstrated significant associations between various drug categories and DILD. Our findings provide useful information on drug categories with potential risk to help physicians prevent and treat DILD.

Risk of Cancer in Association with Ranitidine and Nizatidine vs Other H2 Blockers: Analysis of the Japan Medical Data Center Claims Database 2005-2018

INTRODUCTION

In September 2019, ranitidine and nizatidine were suggested to contain N-nitrosodimethylamine, a carcinogenic substance. People have since been concerned about the potential impact of ranitidine/nizatidine use on the risk of cancer.

OBJECTIVE

The objective of this study was to investigate the risk of cancer among people receiving ranitidine or nizatidine compared with other histamine 2 receptor antagonists (H2 blockers) [cimetidine, famotidine, roxatidine, and lafutidine].

METHODS

In the Japan Medical Data Center claims database (comprising people aged < 75 years) from 2005 to 2018, we identified new adult users of H2 blockers and classified them into ranitidine/nizatidine users and other H2 blocker users. We estimated the incidence of cancer diagnosis in each group and conducted a multivariable Cox regression analysis.

RESULTS

We identified 113,745 new users of ranitidine/nizatidine (median age 41.2 years [interquartile range 31.7-51.1]; 49.1% men; median follow-up 2.4 years [1.1-4.5]) and 503,982 new users of other H2 blockers (median age 40.9 years [31.1-51.2]; 51.0% men; median follow-up 2.3 years [0.9-4.2]). The incidence rate of cancer diagnosis was 6.39 (95% confidence interval 6.13-6.66) cases per 1000 person-years (top three sites: breast 14.8%; colorectal 14.6%; and stomach 11.5%) in the ranitidine/nizatidine group and 6.17 (6.05-6.30) cases per 1000 person-years (colorectal 14.7%; breast 13.5%; and stomach 11.2%) in the other H2 blockers group. The adjusted hazard ratio (ranitidine/nizatidine users vs other H2 blocker users) was 1.02 (0.98-1.07). The results were similar by follow-up length, by cancer site, and when ranitidine and nizatidine users were separately compared with the other H2 blockers group. By cumulative dose, the adjusted hazard ratio (95% confidence interval) was 1.03 (0.98-1.08) from 1 to 180 defined daily doses (DDDs), 1.00 (0.73-1.39) from 181 to 365 DDDs, 0.95 (0.61-1.48) from 366 to 730 DDDs, and 0.83 (0.45-1.55) at > 730 DDDs.

CONCLUSIONS

We found no evidence that ranitidine/nizatidine is associated with an increased risk of cancer, although further studies with more accurate measurement of exposure, inclusion of older people, and longer follow-up may be needed.