| Literature DB >> 26635183 |
Masayoshi Harigai1, Naoki Ishiguro2, Shigeko Inokuma3, Tsuneyo Mimori4, Junnosuke Ryu5, Syuji Takei6, Tsutomu Takeuchi7, Yoshiya Tanaka8, Yoshinari Takasaki9, Hisashi Yamanaka10, Masahiko Watanabe11, Hiroshi Tamada11, Takao Koike12,13.
Abstract
OBJECTIVE: To perform a postmarketing surveillance study evaluating the safety and effectiveness of abatacept in Japanese patients with rheumatoid arthritis (RA).Entities:
Keywords: Abatacept; Japan; PMS; Rheumatoid arthritis; Safety
Mesh:
Substances:
Year: 2016 PMID: 26635183 PMCID: PMC4898160 DOI: 10.3109/14397595.2015.1123211
Source DB: PubMed Journal: Mod Rheumatol ISSN: 1439-7595 Impact factor: 3.023
Patient demographic and clinical baseline characteristics.
| Variables | Safety analysis set ( | Effectiveness analysis set ( |
|---|---|---|
| Sex (females, %) | 82.3 | 82.4 |
| Age [mean ± SD, years (% ≥65 years)] | 61.4 ± 12.6 (44.1) | 61.1 ± 12.8 (43.4) |
| Body weight (mean ± SD, kg) | 53.5 ± 10.5 | 53.6 ± 10.4 |
| Disease duration (median and IQR, years) | 8.2 (3.3–15.3) | 8.3 (3.4–15.5) |
| Steinbrocker stage I/II/III/IV (%) | 10.8/26.0/31.5/31.6 | 11.2/26.5/31.3/31.0 |
| Steinbrocker class 1/2/3/4 (%) | 11.5/63.4/23.5/1.7 | 11.6/63.7/23.1/1.6 |
| Past medical history (%) | 29.1 | 29.4 |
| Allergy history (%) | 19.5 | 20.2 |
| Smoking history (years) | 12.7 | 12.8 |
| Comorbidities (%) | 69.5 | 69.3 |
| History of surgery for RA (%) | 23.6 | 23.1 |
| Prior use of biologics (%) | 69.6 | 70.2 |
| Concomitant MTX use [% (mean ± SD, mg/week)] | 66.3 (7.1 ± 2.7) | 66.7 (7.1 ± 2.6) |
| Concomitant DMARD use (%) | 81.2 | 81.0 |
| Concomitant oral glucocorticoid use [% (mean ± SD, PSL equivalent dose, mg/day)] | 63.1 (5.0 ± 3.0) | 63.0 (5.0 ± 3.0) |
| Concomitant NSAID use (%) | 69.8 | 69.3 |
| Other concomitant medication use (%) | 85.0 | 85.8 |
| Baseline DAS28-ESR (mean ± SD) | – | 5.07 ± 1.30 |
| Baseline DAS28-CRP (mean ± SD) | – | 4.47 ± 1.23 |
IQR = interquartile range; PSL = prednisolone; SD = standard deviation.
Incidence rates of the most commonly reported adverse drug reactions (≥0.5%).
| PMS ( | ||
|---|---|---|
| ADRs | ADRs | Serious ADRs (%) |
| Upper respiratory tract inflammation | 1.21 | 0.03 |
| Herpes zoster | 1.00 | 0.08 |
| Bronchitis | 0.90 | 0.03 |
| Stomatitis | 0.88 | 0 |
| Nasopharyngitis | 0.80 | 0 |
| Abnormal hepatic function tests | 0.75 | 0.05 |
| Pyrexia | 0.62 | 0 |
| Rash | 0.59 | 0 |
*1886.20 person-year.
†All ADR events including serious ADRs.
Summary and incidences rates of adverse drug reactions of interest.
| Age (years) | Duration of Onset (days) | |||||||
|---|---|---|---|---|---|---|---|---|
| Adverse drug reactions | Incidence rates (%) | Sex (males/females, | Mean | Min–Max | Mean | Min–Max | Cause of incident | |
| Deaths | 8 | 0.21 | 3/5 | 73.5 | 61–86 | 97.4 | 30–176 | Interstitial pneumonia ( Bronchopulmonary aspergillosis Mycosis/acute disseminated encephalomyelitis Pneumocystis pneumonia Pulmonary tuberculosis/tuberculous peritonitis |
| Pneumonia | 28 | 0.72 | 7/21 | 66.2 | 25–79 | 95.8 | 6–178 | Pneumonia ( Bacterial pneumonia ( Bronchopneumonia ( Pneumococcal pneumonia ( |
| Tuberculosis | 1 | 0.03 | 0/1 | 86.0 | – | 176.0 | – | Concurrent pulmonary tuberculosis and tuberculous peritonitis |
| Pneumocystispneumonia | 4 | 0.10 | 1/3 | 62.3 | 60–67 | 64.5 | 28–124 | |
| Interstitial pneumonia | 12 | 0.31 | 4/8 | 73.3 | 62–82 | 101.5 | 22–183 | |
| Malignancies | 6 | 0.15 | 1/5 | 75.2 | 62–83 | 98.3 | 59–127 | Lymphoma ( Gastric cancer Malignant lung neoplasm Colorectal cancer Borderline ovarian cancer |
Figure 1. Multivariate logistic regression analysis revealed risk factors for all (a) ADRs, (b) serious ADRs, (c) infections, and (d) serious infections. Candidate variables for multivariate analysis were selected among many others based on their degree of clinical significance and the results of the univariate analysis. Variable selection for the final model of the multivariate logistic regression analysis was performed by stepwise methods.
Figure 2. Change in disease activity over time in patients treated with abatacept. The last-observation-carried-forward (LOCF) imputation method was used. (a) DAS28 based on erythrocyte sedimentation rate (DAS28-ESR). (b) DAS28-ESR changes. (c) DAS28 based on C-reactive protein (DAS28-CRP). (d) DAS28-CRP changes.
Figure 3. Multivariate logistic regression analysis revealed factors associated with improved DAS (DAS28-CRP51.2) in patients with (a) baseline DAS28-CRP45.1, and (b) baseline DAS28-CRP3.2 and 5.1. Candidate variables for multivariate analysis were selected among many others based on their degree of clinical significance and the results of the univariate analysis. Variable selection for the final model of the multivariate logistic regression analysis was performed by stepwise methods.