Two-year abatacept retention rate in clinical practice in the French ACTION cohort.

OBJECTIVES: Abatacept retention rates were evaluated in the French cohort in the prospective ACTION study (2010-2013), which included patients with moderate-to-severe rheumatoid arthritis managed in everyday clinical practice and started on intravenous abatacept therapy. METHODS: Two-year abatacept retention rates were evaluated in 455 patients classified according to treatment line, body mass index (BMI), and status for rheumatoid factor (RF) and anti-citrullinated peptide antibody (ACPA). RESULTS: After 2 years, the overall abatacept retention rate was 44%. The retention rate was non-significantly higher in the patients with vs. without a history of unresponsiveness to at least one biologic (48.1% vs. 41.8%, respectively). No significant retention rate differences were found across BMI categories (444 patients; <25, 45.5%; ≥25 to <30, 48.9%; and ≥30, 36.6%). Neither were any significant differences demonstrated according to RF and ACPA status (RF+ and ACPA+, 45.7%; RF+ or ACPA+, 43.8%; and FR- and ACPA-, 39.1%). CONCLUSION: The 44% 2-year retention rate in the French ACTION cohort supports the usefulness of abatacept therapy. In this study, retention was not associated with treatment line, BMI, or antibody status.

Correction to: Predictors of abatacept retention over 2 years in patients with rheumatoid arthritis: results from the real-world ACTION study.

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Predictors of abatacept retention over 2 years in patients with rheumatoid arthritis: results from the real-world ACTION study.

OBJECTIVES: Evaluate abatacept retention over 2 years in the AbataCepT In rOutiNe clinical practice (ACTION) study. METHOD: ACTION was an international, observational study of patients with moderate-to-severe rheumatoid arthritis (RA) who initiated intravenous abatacept. Crude abatacept retention rates over 2 years were estimated using Kaplan-Meier analyses in biologic-naive and -failure patients. Clinically relevant risk factors and significant prognostic factors for retention were evaluated using a Cox proportional hazards multivariable model. RESULTS: Overall, 2350/2364 enrolled patients were evaluable; 673 (28.6%) were biologic naive and 1677 (71.4%) had prior biologic failure (1 biologic, 728/1677 [43.4%]; ≥ 2 biologics, 949/1677 [56.6%]). Abatacept retention rate (95% confidence interval [CI]) at 2 years was 47.9% (45.7, 50.0): 54.5% (50.4, 58.3) for biologic-naive vs 45.2% (42.7, 47.7) for biologic-failure patients (log-rank P < 0.001). For patients with 1 and ≥ 2 prior biologic failures, respectively, retention rates (95% CI) were 50.2% (46.3, 53.9) vs 41.3% (38.0, 44.6; log-rank P < 0.001). Main reasons for discontinuation (biologic-naive vs biologic-failure, respectively) were lack of efficacy (61.4 vs 67.7%) and safety (21.3 vs 21.2%). Rheumatoid factor (RF) and anti-cyclic citrullinated peptide (anti-CCP) double positivity versus negativity were predictive of higher retention in both biologic-naive (hazard ratio [HR] [95% CI] 0.71 [0.53, 0.96]; P = 0.019) and biologic-failure patients (HR [95% CI] 0.76 [0.62, 0.94]; P = 0.035). CONCLUSIONS: Abatacept initiation as earlier vs later line of therapy in RA may achieve higher 2-year retention rates. RF and anti-CCP seropositivity could predict increased abatacept retention, irrespective of treatment line. TRIAL REGISTRATION: NCT02109666.

Body mass index and clinical response to intravenous or subcutaneous abatacept in patients with rheumatoid arthritis.

This post hoc analysis of ACQUIRE (NCT00559585) explored the effect of baseline body mass index (BMI) on the pharmacokinetics of and clinical response to subcutaneous (SC) or intravenous (IV) abatacept in patients with rheumatoid arthritis (RA). ACQUIRE was a phase 3b, 6-month, double-blind, double-dummy study in which patients with RA were randomized (1:1) to SC (fixed - dose; 125 mg/week) or IV (weight-tiered; ~ 10 mg/kg/month) abatacept plus methotrexate. In this analysis, minimum abatacept plasma concentration (Cmin) was measured at 3 and 6 months, and clinical remission over 6 months was assessed by Disease Activity Score 28 (C-reactive protein; DAS28 [CRP], < 2.6), Simplified Disease Activity Index (SDAI, ≤ 3.3), and Clinical Disease Activity Index (CDAI, ≤ 2.8). Data were stratified by baseline BMI (underweight/normal, < 25 kg/m2; overweight, 25 to < 30 kg/m2; obese, ≥ 30 kg/m2) and administration route. Of the 1456/1457 patients for whom baseline BMIs were available, 526 (36%; SC 265, IV 261) patients were underweight/normal, 497 (34%; SC 249, IV 248) were overweight, and 433 (30%; SC 221, IV 212) were obese. Median Cmin abatacept concentration was ≥ 10 µg/mL (efficacy threshold) at 3 and 6 months in > 90% of patients across BMI groups with both administration routes. DAS28 (CRP), SDAI, and CDAI remission rates at 6 months were similar across BMI groups and 95% confidence intervals overlapped at all time points in both separate and pooled SC/IV analyses. Therapeutic concentrations of abatacept and clinical remission rates using stringent criteria were similar across patient BMIs and administration routes.

Impact of early cART on HIV blood and semen compartments at the time of primary infection.

BACKGROUND: HIV-infected cells in semen facilitate viral transmission. We studied the establishment of HIV reservoirs in semen and blood during PHI, along with systemic immune activation and the impact of early cART. METHODS: Patients in the ANRS-147-OPTIPRIM trial received two years of early cART. Nineteen patients of the trial were analyzed, out of which 8 had acute PHI (WB ≤1 Ab). We quantified total cell-associated (ca) HIV-DNA in blood and semen and HIV-RNA in blood and semen plasma samples, collected during PHI and at 24 months of treatment. RESULTS: At enrollment, HIV-RNA load was higher in blood than in semen (median 5.66 vs 4.22 log10 cp/mL, p<0.0001). Semen HIV-RNA load correlated strongly with blood HIV-RNA load (r = 0.81, p = 0.02, the CD4 cell count (r = -0.98, p<0.0001), and the CD4/CD8 ratio (r = -0.85, p<0.01) in acute infection but not in later stages of PHI. Median blood and seminal cellular HIV-DNA levels were 3.59 and 0.31 log10cp/106 cells, respectively. HIV-DNA load peaked in semen later than in blood and then correlated with blood IP10 level (r = 0.62, p = 0.04). HIV-RNA was undetectable in blood and semen after two years of effective cART. Semen HIV-DNA load declined similarly, except in one patient who had persistently high IP-10 and IL-6 levels and used recreational drugs. CONCLUSIONS: HIV reservoir cells are found in semen during PHI, with gradual compartmentalization. Its size was linked to the plasma IP-10 level. Early treatment purges both the virus and infected cells, reducing the high risk of transmission during PHI. CLINICAL TRIALS REGISTRATION: NCT01033760.

A comparison between different prediction models for invasive breast cancer occurrence in the French E3N cohort.

Breast cancer remains a global health concern with a lack of high discriminating prediction models. The k-nearest-neighbor algorithm (kNN) estimates individual risks using an intuitive tool. This study compares the performances of this approach with the Cox and the Gail models for the 5-year breast cancer risk prediction. The study included 64,995 women from the French E3N prospective cohort. The sample was divided into a learning (N = 51,821) series to learn the models using fivefold cross-validation and a validation (N = 13,174) series to evaluate them. The area under the receiver operating characteristic curve (AUC) and the expected over observed number of cases (E/O) ratio were estimated. In the two series, 393 and 78 premenopausal and 537 and 98 postmenopausal breast cancers were diagnosed. The discrimination values of the best combinations of predictors obtained from cross-validation ranged from 0.59 to 0.60. In the validation series, the AUC values in premenopausal and postmenopausal women were 0.583 [0.520; 0.646] and 0.621 [0.563; 0.679] using the kNN and 0.565 [0.500; 0.631] and 0.617 [0.561; 0.673] using the Cox model. The E/O ratios were 1.26 and 1.28 in premenopausal women and 1.44 and 1.40 in postmenopausal women. The applied Gail model provided AUC values of 0.614 [0.554; 0.675] and 0.549 [0.495; 0.604] and E/O ratios of 0.78 and 1.12. This study shows that the prediction performances differed according to menopausal status when using parametric statistical tools. The k-nearest-neighbor approach performed well, and discrimination was improved in postmenopausal women compared with the Gail model.