Why carry out this study?
|
To our knowledge, there are no studies assessing the relative frequency of prescription claims for drugs that may interact with Janus kinase (JAK) inhibitors in the US population of adult rheumatoid arthritis (RA) patients. Because of the rapidly changing treatment options for RA, information on the relative use of drugs with drug-drug interaction (DDI) potential may be informative in the shared decision making between the health care provider and patient. |
The objective of this retrospective, cross-sectional study was to describe the frequency of prescription claims for drugs that may interact and require adjustment in therapy with JAK inhibitors, without documentation of concomitant administration, among adult patients with RA in a large, administrative US claims database. |
What was learned from the study?
|
Up to 10% of patients with RA were prescribed a drug with the potential to cause a DDI with a JAK inhibitor. |
This study highlights the need to consider the potential for DDIs for RA patients in the clinical setting. |
Digital Features
Introduction
Methods
Data
Study Population
Frequency of Variables of Interest
Category | CYP3A4 inhibitors (strong) | CYP3A4 inhibitors (moderate) | CYP2C19 inhibitors (strong) | OAT3 inhibitors (strong) |
---|---|---|---|---|
Drugs | Atazanavir, boceprevir, clarithromycin, clotrimazole, cobicistat, conivaptan, curcumin, danoprevir, darunavir, delavirdine, econazole, efavirenz, elvitegravir, ergotamine, idelaisib, indinavir, itraconazole, ketoconazole, loperamide, lopinavir, mebefradil, midostaurin, naloxone, nefazadone, nelfinavir, nilotinib, posaconazole, ribociclib, ritonavir, saquinavir, stiripentol, telaprevir, telithromycin, terfenadine, tipranavir, troleandomycin, voriconazole | Amiodarone, amprenavir, anastrozole, aprepitant, barnidipine, cyclosporine, clobazam, clozapine, crizotinib, danazol, desvenlafaxine, diltiazem, dimethyl sulfoxide, dronedarone, erythromycin, fluconazole, fluvoxamine, fosamprenavir, fosnetupitant, fusidic acid, haloperidol, imatinib, idalpine, isavuconazole, isavuconazonium, isoniazid, isradipine, linagliptin, lovastatin, luliconazole, miconazole, mifepristone, milnacipran, netupitant, nicardapine, nilvadipine, paroxetine, primaquine, risperidone, sertraline, simeprevir, tioconazole, venetoclax, venlafaxine, verapamil, zimeldine, ziprasidone | Fluvoxamine, ticlopidine, fluconazole, chloramphenicol, delavirdine, gemfibrozil, stiripentol, fluoxetine, amitriptyline, imipramine, clomipramine, lansoprazole, isoniazid, zarfirlukast, tioconazole, miconazole | Probenecid, colchicine-probenecid |
Statistical Analyses
Results
Patient Selection and Demographics
Demographic | RA cohort N = 152,853 (n, %; unless noted otherwise) |
---|---|
Sex | |
Female | 116,093 (75.95%) |
Male | 36,760 (24.05%) |
Age at index (years, mean ± SD; median) | 57.14 ± 13.38; 57 |
Age groups | |
18–24 | 1546 (1.01%) |
25–34 | 6209 (4.06%) |
35–44 | 17,173 (11.23%) |
45–54 | 37,138 (24.30%) |
55–64 | 52,804 (34.55%) |
65–74 | 20,887 (13.66%) |
≥ 75 | 17,096 (11.18%) |
Primary insurance type | |
Commercial | 113,125 (74.01%) |
Medicare | 39,728 (25.99%) |
Region | |
Midwest | 38,738 (25.34%) |
Northeast | 27,616 (18.07%) |
South | 62,476 (40.87%) |
West | 21,930 (14.35%) |
Unknown | 2093 (1.37%) |
Use of DMARD | |
csDMARDsa | 102,597 (67.12%) |
bDMARDsb | 51,591 (33.75%) |
tsDMARDsc | 2471 (1.62%) |
Charlson Comorbidity Index | |
Mean score (SD) | 1.73 (1.33) |
Potential for Drug–Drug Interactions
Metabolic pathway | RA Cohort N = 152,853 n (%) |
---|---|
Strong OAT3 inhibitors | 96 (0.06%) |
Probenecid | 54 (0.04%) |
Colchicine-probenecid | 44 (0.03%) |
Strong CYP3A4 inhibitors | 4825 (3.16%) |
Clarithromycin | 2337 (1.53%) |
Clotrimazole Troche | 684 (0.45%) |
Clarithromycin ER | 539 (0.35%) |
Loperamide hydrochloride | 311 (0.20%) |
Suboxone | 203 (0.13%) |
Moderate CYP3A4 inhibitors | 33,951 (22.21%) |
Fluconazole | 11,676 (7.64%) |
Sertraline hydrochloride | 7102 (4.65%) |
Venlafaxine hydrochloride ER | 3801 (2.49%) |
Paroxetine hydrochloride | 2308 (1.51%) |
Lovastatin | 1828 (1.20%) |
Strong CYP2C19 inhibitors | 23,940 (15.66%) |
Fluconazole | 11,676 (7.64%) |
Amitriptyline hydrochloride | 4802 (3.14%) |
Fluoxetine hydrochloride | 4599 (3.01%) |
Lansoprazole | 3131 (2.05%) |
Gemfibrozil | 698 (0.46%) |
Moderate CYP3A4 AND strong CYP2C19 inhibitors | 14,726 (9.63%) |
Strong CYP3A4 AND strong CYP2C19 inhibitors | 1528 (1%) |
Metabolic pathway | Age group (years), n (%) | ||||||
---|---|---|---|---|---|---|---|
18–24 | 25–34 | 35–44 | 45–54 | 55–64 | 65–74 | ≥ 75 | |
Strong OAT3 inhibitors | 0 (0%) | 0 (0%) | 4 (0.02%) | 13 (0.04%) | 40 (0.08%) | 17 (0.08%) | 22 (0.13%) |
Strong CYP3A4 inhibitors | 39 (2.52%) | 203 (3.27%) | 578 (3.37%) | 1205 (3.24%) | 1718 (3.25%) | 652 (3.12%) | 430 (2.52%) |
Moderate CYP3A4 inhibitors | 261 (16.88%) | 1367 (22.02%) | 4051 (23.59%) | 7918 (21.32%) | 11,249 (21.30%) | 4847 (23.21%) | 4258 (24.91%) |
Strong CYP2C19 inhibitors | 246 (15.91%) | 1128 (18.17%) | 3538 (20.60%) | 6410 (17.26%) | 7883 (14.93%) | 2880 (13.79%) | 1855 (10.85%) |
Moderate CYP3A4 AND strong CYP2C19 inhibitors | 179 (1.10%) | 908 (14.62%) | 2569 (14.96%) | 4036 (10.87%) | 4450 (8.43%) | 1555 (7.44%) | 1029 (6.02%) |
Strong CYP3A4 AND strong CYP2C19 inhibitors | 17 (1.10%) | 69 (1.11%) | 208 (1.21%) | 419 (1.13%) | 517 (0.98%) | 198 (0.95%) | 100 (0.58%) |