Lobuteva Liudmila Aleksandrovna
AIM. To compare the cost per responder (CPR) between different groups of biologic agents and targeted synthetic disease-modifying antirheumatic drugs in patients with rheumatoid arthritis (RA). Materials and Methods. A total of 320 patients with RA were included in the study. Patients were divided into 4 groups (n=80 in each group): group 1 received B cell-depleting agent (rituximab), group 2 – TNF-alpha (α) inhibitors, group 3 –interleukin-6 inhibitor (tocilizumab), and group 4 – Janus kinase inhibitor (tofacitinib). The effectiveness of therapy was assessed using the generally accepted index of rheumatoid arthritis activity DAS28 and the dynamics of this index after 12 months of therapy. A good response on DAS28 (current DAS28 scores of 3.2 or less with reductions in DAS28 of more than 1.2) was accepted as a response to therapy. For the leading CPR-DAS28 drugs, an ad- ditional CPR study was performed using the SDAI, CDAI, and RAPID-3 indices. Results. A good response on DAS28 was observed more frequently in group 3 (56.3%) and group 4 (6.3%) compared to group 1 (11.5%, p<0.05 in both cases) and group 2 patients (22.5%, p<0.05 in both cases). CPR-DAS28 in group 3 was RUB 1094772.6, in group 4 – RUB 1089201.3; and that was 3.3 times lower than in group 1 (RUB 3587662.2, p<0.05 in both cases) and 2.3 times lower than in group 4 (RUB 2545747.3, p<0.05 in both cases). In group 3 (tocilizumab) CPR-SDAI was RUB 786867.9, CPR-CDAI – RUB 774285.7, and CPR-RAPID-3 – RUB 786867.9. In group 4 (tofacitinib) CPR-SDAI was RUB 1048831.2, CPR-CDAI – RUB 1088379.9, and CPR-RAPID – RUB 915730.8. Conclusion. CPR were lower with interleukin-6 inhibitor and Janus kinase in- hibitor therapy than with B cell-depleting agent and TNF-α inhibitors therapy. Determination of CPR by SDAI, CDAI, and RAPID-3 indices revealed an ad- vantage of interleukin-6 inhibitor therapy over Janus kinase inhibitor therapy.
To determine the feasibility of using cluster analysis to manage treatment costs of systemic autoimmune rheumatic diseases (SARDs). MATERIALS AND METHODS. The object of the study was the case histories of patients hospitalized in 2020. A total of 954 case histories of patients with SARDs were analyzed, among them systemic scleroderma – 411 patients (43.1%), systemic lupus erythematosus – 263 (27.5%), rheumatoid arthritis seropositive and seronegative – 103 (10.8%), systemic vasculitis associated with anti-neutrophil cytoplasmic antibodies – 98 (10.3%), idiopathic inflam- matory myopathies (polymyositis, dermatomyositis) – 57 (6%), Sjögren’s disease – 22 (2.3%). Hierarchical cluster analysis by weighted pairwise mean using Euclidean distance and Chebyshev distance, and non-hierarchical clus- tering by k-means were performed for the sample of case histories in the STA- TISTICA 13.3. Multiple regression model with a dependent factor of treatment costs was built in MS Excel. RESULTS. Hierarchical clustering resulted in 2 dendrograms, which yielded the same number of clusters – 4. The cluster analysis identified 4 clusters with significant differences (p<0.05) in treatment costs with formative indicators: gender, age of patients, duration of disease, number of bed-days, number of hospitalizations, disease activity level, number of comorbidities and compli- cations, previous use of biologic agents, total number of medications pre- scribed, use of Acellbia, Benlista, other biologic agents, and immunoglobulins during hospitalization. General multiple regression model for all patients with SARDs and separate multiple regression models for each cluster were con- structed using statistically significant factors. CONCLUSIONS. Factors affecting the treatment costs for patients with SARDs include the number of days of hospitalization, the degree of disease activity, the number of medications prescribed, and the use of biologic agents and immunoglobulins during hospitalization.
AIM. To compare the cost per responder (CPR) between different groups of biologic agents and targeted synthetic disease-modifying antirheumatic drugs in patients with rheumatoid arthritis (RA). Materials and Methods. A total of 320 patients with RA were included in the study. Patients were divided into 4 groups (n=80 in each group): group 1 received B cell-depleting agent (rituximab), group 2 – TNF-alpha (α) inhibitors, group 3 –interleukin-6 inhibitor (tocilizumab), and group 4 – Janus kinase inhibitor (tofacitinib). The effectiveness of therapy was assessed using the generally accepted index of rheumatoid arthritis activity DAS28 and the dynamics of this index after 12 months of therapy. A good response on DAS28 (current DAS28 scores of 3.2 or less with reductions in DAS28 of more than 1.2) was accepted as a response to therapy. For the leading CPR-DAS28 drugs, an ad- ditional CPR study was performed using the SDAI, CDAI, and RAPID-3 indices. Results. A good response on DAS28 was observed more frequently in group 3 (56.3%) and group 4 (6.3%) compared to group 1 (11.5%, p<0.05 in both cases) and group 2 patients (22.5%, p<0.05 in both cases). CPR-DAS28 in group 3 was RUB 1094772.6, in group 4 – RUB 1089201.3; and that was 3.3 times lower than in group 1 (RUB 3587662.2, p<0.05 in both cases) and 2.3 times lower than in group 4 (RUB 2545747.3, p<0.05 in both cases). In group 3 (tocilizumab) CPR-SDAI was RUB 786867.9, CPR-CDAI – RUB 774285.7, and CPR-RAPID-3 – RUB 786867.9. In group 4 (tofacitinib) CPR-SDAI was RUB 1048831.2, CPR-CDAI – RUB 1088379.9, and CPR-RAPID – RUB 915730.8. Conclusion. CPR were lower with interleukin-6 inhibitor and Janus kinase in- hibitor therapy than with B cell-depleting agent and TNF-α inhibitors therapy. Determination of CPR by SDAI, CDAI, and RAPID-3 indices revealed an ad- vantage of interleukin-6 inhibitor therapy over Janus kinase inhibitor therapy.
To determine the feasibility of using cluster analysis to manage treatment costs of systemic autoimmune rheumatic diseases (SARDs). MATERIALS AND METHODS. The object of the study was the case histories of patients hospitalized in 2020. A total of 954 case histories of patients with SARDs were analyzed, among them systemic scleroderma – 411 patients (43.1%), systemic lupus erythematosus – 263 (27.5%), rheumatoid arthritis seropositive and seronegative – 103 (10.8%), systemic vasculitis associated with anti-neutrophil cytoplasmic antibodies – 98 (10.3%), idiopathic inflam- matory myopathies (polymyositis, dermatomyositis) – 57 (6%), Sjögren’s disease – 22 (2.3%). Hierarchical cluster analysis by weighted pairwise mean using Euclidean distance and Chebyshev distance, and non-hierarchical clus- tering by k-means were performed for the sample of case histories in the STA- TISTICA 13.3. Multiple regression model with a dependent factor of treatment costs was built in MS Excel. RESULTS. Hierarchical clustering resulted in 2 dendrograms, which yielded the same number of clusters – 4. The cluster analysis identified 4 clusters with significant differences (p<0.05) in treatment costs with formative indicators: gender, age of patients, duration of disease, number of bed-days, number of hospitalizations, disease activity level, number of comorbidities and compli- cations, previous use of biologic agents, total number of medications pre- scribed, use of Acellbia, Benlista, other biologic agents, and immunoglobulins during hospitalization. General multiple regression model for all patients with SARDs and separate multiple regression models for each cluster were con- structed using statistically significant factors. CONCLUSIONS. Factors affecting the treatment costs for patients with SARDs include the number of days of hospitalization, the degree of disease activity, the number of medications prescribed, and the use of biologic agents and immunoglobulins during hospitalization.