Use of Drug Claims Data and a Medication Risk Score to Assess the Impact of CYP2D6 Drug Interactions among Opioid Users on Healthcare Costs
Abstract
:1. Introduction
2. Materials and Methods
2.1. Medication Risk Score
2.2. Opioid Identification
2.3. Data Processing and Statistical Analyses
3. Results
3.1. Overall Opioid Usage
3.2. CYP2D6 Opioids with and without Interacting Drugs
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
DDI | Drug-Drug interaction |
CYP | Cytochrome P450 |
ADE | Adverse drug events |
MRS | Medication risk score |
TRHC | Tabula Rasa HealthCare |
FAERS | USA FDA Adverse Event Reporting System |
LQTS | Long QT syndrome |
CMS | Centers for Medicare and Medicaid services |
NDC | National Drug Codes |
ATC | Anatomical Therapeutic Chemical codes |
RxCUI | RXNorm Concept Unique Identifier |
SD | Standard deviation |
PS | Propensity score |
IQR | Interquartile range |
CI | Confidence interval |
SMD | Standardized mean difference |
GERD | Gastroesophageal reflux disease |
NSAIDs | Non-steroidal anti-inflammatory drugs |
BPH | Benign prostate hyperplasia |
MME | Morphine milligram equivalent |
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n Total 50,843 | No-Opioid Group | Opioid Group | p-Value or Difference |
---|---|---|---|
n (%) | 46,755 (92%) | 4088 (8%) | |
Age: y ± SD * | 40.4 ± 18.5 | 44.9 ± 14.5 | <0.001 |
Gender: | |||
Male (%) | 19,473 (41.6) | 1879 (46.0) | |
Female (%) | 27,282 (58.4) | 2209 (54.0) | <0.001 |
Number of prescribed drugs per patient: mean ± SD | 2.6 ± 2.0 | 4.8 ±3.0 | <0.001 |
Drug class/co-morbidity (using drug as a proxy): n (%) | |||
Anticoagulants | 615 (1.32) | 115 (2.81) | <0.001 |
Antiplatelet drugs | 601 (1.29) | 76 (1.86) | 0.003 |
Anxiety | 1652 (3.53) | 327 (8.00) | <0.001 |
Arrythmia | 357 (0.76) | 63 (1.54) | <0.001 |
BPH | 628 (1.34) | 101 (2.47) | <0.001 |
Chronic airway disease | 5735 (12.27) | 421 (10.30) | <0.001 |
Cardiac heart failure | 1836 (3.93) | 152 (3.72) | 0.53 |
Dementia | 21 (0.04) | 1 (0.02) | 1.0 |
Depression | 7853 (16.80) | 737 (18.03) | 0.04 |
Diabetes | 3477 (7.44) | 281 (6.87) | 0.19 |
Epilepsy | 2271 (4.86) | 516 (12.62) | <0.001 |
GERD | 4251 (9.09) | 507 (12.4) | <0.001 |
Glaucoma | 666 (1.42) | 47 (1.15) | 0.16 |
Gout | 587 (1.26) | 50 (1.22) | 0.94 |
HIV | 103 (0.22) | 7 (0.17) | 0.72 |
Hyperlipidemia | 7965 (17.04) | 618 (15.12) | 0.002 |
Hypertension | 7500 (16.04) | 685 (16.76) | 0.23 |
Hyperthyroidism | 59 (0.13) | 2 (0.05) | 0.24 |
Incontinence | 304 (0.65) | 56 (1.37) | <0.001 |
NSAIDs | 2296 (4.91) | 713 (17.44) | <0.001 |
Malignancies | 111 (0.24) | 8 (0.20) | 0.74 |
Migraine | 626 (1.34) | 68 (1.66) | 0.09 |
Parkinson | 0 | 0 | |
Psoriasis | 119 (0.25) | 9 (0.22) | 0.87 |
Psychotic illness | 544 (1.15) | 77 (1.88) | <0.001 |
Transplant | 191 (0.41) | 11 (0.27) | 0.19 |
Tuberculosis | 3 (0.01) | 0 | 1.0 |
Total MRS: mean (95% CI) ŧ | 3.5 (3.4–3.6) | 8.0 (7.9–8.1) | 4.5 (4.4–4.6) |
CYP450 drug interaction burden score: mean (95% CI) ŧ,** | 3.4 (3.3–3.5) | 4.5 (4.4–4.5) | 1.1 (0.9–1.2) |
Group | Opioids | n (%) * |
---|---|---|
Overall opioid users (n = 4088) | Hydrocodone Oxycodone Tramadol Codeine Morphine Buprenorphine Fentanyl Methadone Hydromorphone Tapentadol | 1777 (43.5) 958 (23.4) 670 (16.4) 631 (15.4) 133 (3.3) 132 (3.2) 48 (1.2) 35 (0.9) 24 (0.6) 15 (0.4) |
CYP2D6 activated opioid_No interaction (n = 3299) | Hydrocodone Oxycodone Codeine Tramadol | 1533 (46.5) 786 (23.8) 564 (17.1) 542 (16.4) |
CYP2D6 activated opioid_With interacting drug(s) (n = 577) | Hydrocodone Oxycodone Tramadol Codeine | 244 (42.3) 172 (29.8) 128 (22.2) 67 (11.6) |
n = 4082 | No-Opioid | Opioid | Fold-Difference |
---|---|---|---|
Total medical expenditure: median (95%CI) | $1370 (1293–1447) | $4043 (3907–4178) | |
Total medical expenditure: mean (P2.5th- P97.5th) * | $1120 (1061–1184) | $2457 (2369–2548) | 2.19 (2.05–2.34) |
Zero-inflated model | |||
Total medical expenditure: mean (P2.5th-P97.5th) * | $1635 (1562–1711) | $3912 (3805–4023) | 2.39 (2.26–2.52) |
n Total 3876 | CYP2D6 Activated Opioid_No Interaction | CYP2D6 Activated Opioid_with Interacting Drugs | p-Value or Difference |
---|---|---|---|
n (%) | 3299 (85%) | 577 (15%) | |
Age: y ± SD | 43.7 ± 14.8 | 52.8 ± 10.4 | <0.001 |
Gender | |||
Male: n (%) | 1517 (46.0) | 239 (41.4) | |
Female: n (%) | 1782 (54.0) | 338 (58.6) | 0.046 |
Number of prescribed drugs per patient: mean ± SD | 4.3 ± 2.5 | 8.0 ± 3.4 | <0.001 |
Drug class/co-morbidity (using drug as a proxy): n (%) | |||
Anticoagulants | 68 (2.06) | 39 (6.76) | <0.001 |
Antiplatelet drugs | 39 (1.18) | 32 (5.55) | <0.001 |
Anxiety | 214 (6.49) | 82 (14.21) | <0.001 |
Arrythmia | 35 (1.06) | 23 (3.99) | <0.001 |
BPH | 71 (2.15) | 26 (4.51) | 0.002 |
Chronic airway disease | 314 (9.52) | 94 (16.29) | <0.001 |
Cardiac heart failure | 16 (0.48) | 126 (21.84) | <0.001 |
Dementia | 0 (0) | 1 (0.17) | 0.15 |
Depression | 339 (10.28) | 328 (56.85) | <0.001 |
Diabetes | 171 (5.18) | 92 (15.94) | <0.001 |
Epilepsy | 310 (9.40) | 158 (27.38) | <0.001 |
GERD | 325 (9.85) | 161 (27.90) | <0.001 |
Glaucoma | 26 (0.79) | 13 (2.25) | 0.005 |
Gout | 35 (1.06) | 13 (2.25) | 0.024 |
HIV | 6 (0.18) | 1 (0.17) | 1.0 |
Hyperlipidemia | 379 (11.49) | 212 (36.74) | <0.001 |
Hypertension | 432 (13.09) | 213 (36.92) | <0.001 |
Hyperthyroidism | 1 (0.03) | 0 (0.0) | 1.0 |
Incontinence | 35 (1.06) | 18 (3.12) | 0.001 |
NSAIDs | 583 (17.67) | 111 (19.24) | 0.38 |
Malignancies | 5 (0.15) | 2 (0.35) | 0.28 |
Migraine | 43 (1.30) | 20 (3.47) | 0.0005 |
Parkinson | 0 | 0 | |
Psoriasis | 4 (0.12) | 5 (0.87) | 0.005 |
Psychotic illness | 27 (0.82) | 35 (6.07) | <0.001 |
Transplant | 5 (0.15) | 4 (0.69) | 0.033 |
Tuberculosis | 0 | 0 | |
Total MRS: mean (95% CI) * | 12.4 (12.1–12.8) | 15.7 (15.4–15.9) | 3.2 (6.9–12.3) |
CYP450 drug interaction burden score: mean (95% CI)* | 4.5 (4.3–4.6) | 6.6 (6.4–6.7) | 2.1 (1.9–2.3) |
n = 452 | No-Opioid | CYP2D6 Activated Opioid_No Interaction | CYP2D6 Activated Opioid_with Interacting Drugs | Fold-Difference (CYP2D6 Opioid Users No vs. with Interactions) |
---|---|---|---|---|
Total medical expenditure: median (95%CI) | $2938 | $7832 (6972–8684) | $9158 (8394–10,011) | |
Total medical expenditure: mean (P2.5th- P97.5th) * | $2368 (1977–2833) | $5625 (4961–6421) | $7841 (7247–8459) | 1.40 (1.20–1.62) |
Zero-inflated model | ||||
Total medical expenditure: mean (P2.5th-P97.5th) * | $3060 (2643–3539) | $6994 (6270–7742) | $8030 (7462–8615) | 1.15 (1.01–1.32) |
CYP2D6 Opioid | CYP2D6 Activated Opioid_No Interaction (n = 452) | CYP2D6 Activated Opioid_with CYP2D6 Interacting Drugs (n = 452) | ||
---|---|---|---|---|
Total daily dose (mg) | Total daily MME | Total daily dose (mg) | Total daily MME | |
Codeine | 14 ± 191 (6 to 720) | 2.1 ± 28.7 (0.9–108) | 31 ± 343 (6 to 720) | 4.7 ± 51.5 (0.9–108) |
Hydrocodone | 4 ± 15 (0.5 to 80) | 4 ± 15 (0.5–80) | 5 ± 34 (0.5 to 80) | 5 ± 34 (0.5–80) |
Oxycodone | 7 ± 28 (0.5 to 180) | 10.5 ± 42.0 (0.8–270) | 9 ± 48 (2 to 180) | 13.5 ± 72.0 (3–270) |
Tramadol | 21 ± 99 (2 to 409) | 2.1 ± 9.9 (0.2–41) | 32 ± 96 (5 to 600) | 3.2 ± 9.6 (0.5–60) |
Total MME * | 5.6 ± 32 (0.2–270) | 7.4 ± 48 (0.5–270) ** |
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Michaud, V.; Bikmetov, R.; Smith, M.K.; Dow, P.; Darakjian, L.I.; Deodhar, M.; Cicali, B.; Bain, K.T.; Turgeon, J. Use of Drug Claims Data and a Medication Risk Score to Assess the Impact of CYP2D6 Drug Interactions among Opioid Users on Healthcare Costs. J. Pers. Med. 2021, 11, 1174. https://doi.org/10.3390/jpm11111174
Michaud V, Bikmetov R, Smith MK, Dow P, Darakjian LI, Deodhar M, Cicali B, Bain KT, Turgeon J. Use of Drug Claims Data and a Medication Risk Score to Assess the Impact of CYP2D6 Drug Interactions among Opioid Users on Healthcare Costs. Journal of Personalized Medicine. 2021; 11(11):1174. https://doi.org/10.3390/jpm11111174
Chicago/Turabian StyleMichaud, Veronique, Ravil Bikmetov, Matt K. Smith, Pamela Dow, Lucy I. Darakjian, Malavika Deodhar, Brian Cicali, Kevin T. Bain, and Jacques Turgeon. 2021. "Use of Drug Claims Data and a Medication Risk Score to Assess the Impact of CYP2D6 Drug Interactions among Opioid Users on Healthcare Costs" Journal of Personalized Medicine 11, no. 11: 1174. https://doi.org/10.3390/jpm11111174