14 research outputs found
Development of internal control methodology by using statistical methods of variability assessment of material flow business processes
Variability or instability is one of the key features of any process, including business processes of material flow internal control. Variability is a characteristic of all natural systems and technical processes. The objects which properties can be characterized via certain parameters arise at the output of any process. The article discloses the feasibility of using the statistical methods in the internal control system of business entities; in this case the focus is on the method of identifying the causes of variability using control charts of various types (Shewhart control charts) as a prime tool. The view points regarding variability of famous academic economists who researched the business process management issues are also considered. Authorsβ classification of business process variation on types of material flow internal control with the allocation of controlled and uncontrolled variation is taken as the basis of the proposed application. The method of using control charts in estimating the efficiency of material flow internal control business processes is described in detail.peer-reviewe
THE RUSSIAN REGISTRY OF RITUXIMAB. ANALYSIS OF THE EFFICIENCY OF THERAPY AND THE FUNCTIONAL STATEOF PATIENTS WITH RHEUMATOID ARTHRITIS
Objective: To evaluate the functional status of patients with rheumatoid arthritis (RA) receiving two courses of rituximab (RTΠ) therapy and its efficiency from the Russian registrys data. Subjects and methods. The analysis covered 269 patients receiving 1 or 2 courses of RT therapy, their clinical follow-up schedules and quality of life (QL) questionnaires were filled in before drug administration and at 8, 16, and 24 weeks of a follow-up: 220 and 49 patients received 1 and 2 courses of RT therapy, respectively. The DAS28 index was used to evaluate disease activity; the patients functional status was assessed according to the Health Assessment Questionnaire (HAQ). Results. The patients' mean age was 46.5311.79 years; the disease duration was 9.806.87 years; disease activity scale (DAS28) scores were 6.501.06; the majority of patients had significant functional disorders estimated at 1.90 [1.37-2.38] scores according to the HAQ; 78% patients had extra-articular manifestations; rheumatoid factor was detected in 82.9%; the patients received more than 2 basic antiinflammatory drugs on average; 33.5% took TNF-Ρ inhibitors. After the first course of therapy at 24 weeks of the follow-up, there was a gradual decline in DAS28 from 6.491.05 to 4.091.32 scores (p < 0.000001, ANOVA). A significant reduction in serum C-reactive protein was achieved during the first course of therapy just at 2 weeks of the follow-up. A decrease in DAS28 to Ρ1.2 was seen in 79.9 of the patients after the first course at 24 weeks of the follow-up and in 85.7% after the second course. 13% of patients achieved drug-induced remission (DAS2
Π ΠΎΠ»Ρ Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠ½ΡΡ Π±ΠΈΠΎΠΌΠ°ΡΠΊΠ΅ΡΠΎΠ² Π² ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³Π΅ ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΡΠ΅Π²ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ Π³Π΅Π½Π½ΠΎ-ΠΈΠ½ΠΆΠ΅Π½Π΅ΡΠ½ΡΠΌΠΈ Π±ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠ°ΠΌΠΈ
Significant progress in treating immunoinflammatory rheumatic diseases (RD) is related to the design of a novel family of drugs, geneticallyΒ engineered (GE) drugs. Molecular and cellular biomarkers (antibodies, indicators of acute inflammation, cytokines, chemokines, growth factors, endothelial activation markers, immunoglobulins, cryoglobulins, T- and B-cell subpopulations, products of bone and cartilage metabolism, genetic and metabolic markers) that allow one to conduct immunological monitoring and prediction of the effectiveness of RD therapyΒ using tumor necrosis factor Ξ± inhibitors (infliximab, adalimumab, golimumab, etanercept), anti-B-cell drugs (rituximab, belimumab), interleukin-6 receptor antagonist (tocilizumab), and T-cell costimulation blocker (abatacept) have been detected in blood, synovial fluid, urine,Β and bioptates of the affected tissues. In addition to the conventional uniplex immunodiagnostics techniques, multiplex analysis of marker, whichΒ is based on genetic, transcriptomic and proteomic technologies using DNA and protein microarrays, polymerase chain reaction, and flow cytometry, is becoming increasingly widespread. The search for and validation of immunological predictors of the effective response to GE drug therapy make it possible to optimize and reduce the cost of therapy using these drugs in future.ΠΠ½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΡΠΉ ΠΏΡΠΎΠ³ΡΠ΅ΡΡ Π² Π»Π΅ΡΠ΅Π½ΠΈΠΈ ΠΈΠΌΠΌΡΠ½ΠΎΠ²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅Π²ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ (Π Π) ΡΠ²ΡΠ·Π°Π½ Ρ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΎΠΉ Π½ΠΎΠ²ΠΎΠ³ΠΎ ΠΊΠ»Π°ΡΡΠ° Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΡΡ
ΡΡΠ΅Π΄ΡΡΠ² β Π³Π΅Π½Π½ΠΎ-ΠΈΠ½ΠΆΠ΅Π½Π΅ΡΠ½ΡΡ
Π±ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠΎΠ² (ΠΠΠΠ). Π Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ Π² ΠΊΡΠΎΠ²ΠΈ, ΡΠΈΠ½ΠΎΠ²ΠΈΠ°Π»ΡΠ½ΠΎΠΉ ΠΆΠΈΠ΄ΠΊΠΎΡΡΠΈ, ΠΌΠΎΡΠ΅ ΠΈ Π±ΠΈΠΎΠΏΡΠ°ΡΠ°Ρ
ΠΏΠΎΡΠ°ΠΆΠ΅Π½Π½ΡΡ
ΡΠΊΠ°Π½Π΅ΠΉ Π²ΡΡΠ²Π»Π΅Π½Ρ ΠΌΠΎΠ»Π΅ΠΊΡΠ»ΡΡΠ½ΡΠ΅ ΠΈ ΠΊΠ»Π΅ΡΠΎΡΠ½ΡΠ΅ Π±ΠΈΠΎΠΌΠ°ΡΠΊΠ΅ΡΡ (Π°Π½ΡΠΈΡΠ΅Π»Π°, ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ ΠΎΡΡΡΠΎΠΉ ΡΠ°Π·Ρ Π²ΠΎΡΠΏΠ°Π»Π΅Π½ΠΈΡ, ΡΠΈΡΠΎΠΊΠΈΠ½Ρ, Ρ
Π΅ΠΌΠΎΠΊΠΈΠ½Ρ, ΡΠ°ΠΊΡΠΎΡΡ ΡΠΎΡΡΠ°, ΠΌΠ°ΡΠΊΠ΅ΡΡ Π°ΠΊΡΠΈΠ²Π°ΡΠΈΠΈ ΡΠ½Π΄ΠΎΡΠ΅Π»ΠΈΡ, ΠΈΠΌΠΌΡΠ½ΠΎΠ³Π»ΠΎΠ±ΡΠ»ΠΈΠ½Ρ, ΠΊΡΠΈΠΎΠ³Π»ΠΎΠ±ΡΠ»ΠΈΠ½Ρ, ΡΡΠ±ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ Π’- ΠΈ Π-Π»ΠΈΠΌΡΠΎΡΠΈΡΠΎΠ², ΠΏΡΠΎΠ΄ΡΠΊΡΡ ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΠ·ΠΌΠ° ΠΊΠΎΡΡΠ½ΠΎΠΉ ΠΈ Ρ
ΡΡΡΠ΅Π²ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ, Π³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅, ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠ°ΡΠΊΠ΅ΡΡ), ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠΈΠ΅ ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΡΡ ΠΈΠΌΠΌΡΠ½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³ ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ Π Π ΠΈΠ½Π³ΠΈΠ±ΠΈΡΠΎΡΠ°ΠΌΠΈ ΡΠ°ΠΊΡΠΎΡΠ° Π½Π΅ΠΊΡΠΎΠ·Π° ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ Ξ± (ΠΈΠ½ΡΠ»ΠΈΠΊΡΠΈΠΌΠ°Π±, Π°Π΄Π°Π»ΠΈΠΌΡΠΌΠ°Π±, Π³ΠΎΠ»ΠΈΠΌΡΠΌΠ°Π±, ΡΡΠ°Π½Π΅ΡΡΠ΅ΠΏΡ), Π°Π½ΡΠΈ-Π-ΠΊΠ»Π΅ΡΠΎΡΠ½ΡΠΌΠΈ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠ°ΠΌΠΈ (ΡΠΈΡΡΠΊΡΠΈΠΌΠ°Π±, Π±Π΅Π»ΠΈΠΌΡΠΌΠ°Π±), Π°Π½ΡΠ°Π³ΠΎΠ½ΠΈΡΡΠΎΠΌ ΡΠ΅ΡΠ΅ΠΏΡΠΎΡΠ° ΠΈΠ½ΡΠ΅ΡΠ»Π΅ΠΉΠΊΠΈΠ½Π° 6 (ΡΠΎΡΠΈΠ»ΠΈΠ·ΡΠΌΠ°Π±), Π±Π»ΠΎΠΊΠ°ΡΠΎΡΠΎΠΌ ΠΊΠΎΡΡΠΈΠΌΡΠ»ΡΡΠΈΠΈ Π’-ΠΊΠ»Π΅ΡΠΎΠΊ (Π°Π±Π°ΡΠ°ΡΠ΅ΠΏΡ). ΠΠ°ΡΡΠ΄Ρ Ρ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΡΠΌΠΈ ΡΠ½ΠΈΠΏΠ»Π΅ΠΊΡΠ½ΡΠΌΠΈ ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠΈ ΠΈΠΌΠΌΡΠ½ΠΎΠ΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ Π²ΡΠ΅ ΡΠΈΡΠ΅ ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΡΡΡ ΠΌΡΠ»ΡΡΠΈΠΏΠ»Π΅ΠΊΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π±ΠΈΠΎΠΌΠ°ΡΠΊΠ΅ΡΠΎΠ², ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΠΉ Π½Π° Π³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΡ
, ΡΡΠ°Π½ΡΠΊΡΠΈΠΏΡΠΎΠΌΠ½ΡΡ
ΠΈ ΠΏΡΠΎΡΠ΅ΠΎΠΌΠ½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΡ
Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΠΠ- ΠΈ Π±Π΅Π»ΠΊΠΎΠ²ΡΡ
ΠΌΠΈΠΊΡΠΎΡΠΈΠΏΠΎΠ², ΠΏΠΎΠ»ΠΈΠΌΠ΅ΡΠ°Π·Π½ΠΎΠΉΒ ΡΠ΅ΠΏΠ½ΠΎΠΉ ΡΠ΅Π°ΠΊΡΠΈΠΈ, ΠΏΡΠΎΡΠΎΡΠ½ΠΎΠΉ ΡΠΈΡΠΎΠΌΠ΅ΡΡΠΈΠΈ. ΠΠΎΠΈΡΠΊ ΠΈ Π²Π°Π»ΠΈΠ΄Π°ΡΠΈΡ ΠΈΠΌΠΌΡΠ½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠ΅Π΄ΠΈΠΊΡΠΎΡΠΎΠ² ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΠΎΡΠ²Π΅ΡΠ° Π½Π° ΡΠ΅ΡΠ°ΠΏΠΈΡΒ ΠΠΠΠ ΡΠΎΠ·Π΄Π°Π΅Ρ ΠΏΡΠ΅Π΄ΠΏΠΎΡΡΠ»ΠΊΠΈ Π΄Π»Ρ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΠΈ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ Π»Π΅ΡΠ΅Π½ΠΈΡ ΡΡΠΈΠΌΠΈ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠ°ΠΌΠΈ
ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΠΎΠ³ΠΎ ΠΈΠ½Π΄Π΅ΠΊΡΠ° Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎΠΉ ΡΠΊΠ»Π΅ΡΠΎΠ΄Π΅ΡΠΌΠΈΠΈ
Up to now, it is difficult to determine systemic scleroderma (SSD) activity because of the lack of validated tools to estimate changes in the pathological process. Attempts have been made to develop unified activity assessing methods for many years. The indices proposed by the European SSD Group are most popular today. This paper gives the results of using this index in a cohort of Russian patients.ΠΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎΠΉ ΡΠΊΠ»Π΅ΡΠΎΠ΄Π΅ΡΠΌΠΈΠΈ (Π‘Π‘Π) Π΄ΠΎ Π½Π°ΡΡΠΎΡΡΠ΅Π³ΠΎ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ Π·Π°ΡΡΡΠ΄Π½Π΅Π½ΠΎ ΠΈΠ·-Π·Π° ΠΎΡΡΡΡΡΡΠ²ΠΈΡ Π²Π°Π»ΠΈΠ΄ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠΎΠ² Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ°. Π ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ ΠΌΠ½ΠΎΠ³ΠΈΡ
Π»Π΅Ρ ΠΏΡΠ΅Π΄ΠΏΡΠΈΠ½ΠΈΠΌΠ°ΡΡΡΡ ΠΏΠΎΠΏΡΡΠΊΠΈ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΡΠ½ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΎΡΠ΅Π½ΠΊΠΈ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ. ΠΠ°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΠΏΠΎΠΏΡΠ»ΡΡΠ½ΡΠΌΠΈ Π½Π° ΡΠ΅Π³ΠΎΠ΄Π½ΡΡΠ½ΠΈΠΉ Π΄Π΅Π½Ρ ΡΠ²Π»ΡΡΡΡΡ ΠΈΠ½Π΄Π΅ΠΊΡΡ, ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΡΠ΅ Π΅Π²ΡΠΎΠΏΠ΅ΠΉΡΠΊΠΎΠΉ Π³ΡΡΠΏΠΏΠΎΠΉ ΠΏΠΎ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ Π‘Π‘Π. Π ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ΡΡΠΎΠ³ΠΎ ΠΈΠ½Π΄Π΅ΠΊΡΠ° Ρ ΠΊΠΎΠ³ΠΎΡΡΡ ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ²
Role of laboratory biomarkers in monitoring and prediction of the effectiveness of treatment of rheumatic diseases using genetically engineered drugs
<p>Significant progress in treating immunoinflammatory rheumatic diseases (RD) is related to the design of a novel family of drugs, geneticallyΒ engineered (GE) drugs. Molecular and cellular biomarkers (antibodies, indicators of acute inflammation, cytokines, chemokines, growth factors, endothelial activation markers, immunoglobulins, cryoglobulins, T- and B-cell subpopulations, products of bone and cartilage metabolism, genetic and metabolic markers) that allow one to conduct immunological monitoring and prediction of the effectiveness of RD therapyΒ using tumor necrosis factor Ξ± inhibitors (infliximab, adalimumab, golimumab, etanercept), anti-B-cell drugs (rituximab, belimumab), interleukin-6 receptor antagonist (tocilizumab), and T-cell costimulation blocker (abatacept) have been detected in blood, synovial fluid, urine,Β and bioptates of the affected tissues. In addition to the conventional uniplex immunodiagnostics techniques, multiplex analysis of marker, whichΒ is based on genetic, transcriptomic and proteomic technologies using DNA and protein microarrays, polymerase chain reaction, and flow cytometry, is becoming increasingly widespread. The search for and validation of immunological predictors of the effective response to GE drug therapy make it possible to optimize and reduce the cost of therapy using these drugs in future.</p
Use of the international systemic scleroderma activity index
Up to now, it is difficult to determine systemic scleroderma (SSD) activity because of the lack of validated tools to estimate changes in the pathological process. Attempts have been made to develop unified activity assessing methods for many years. The indices proposed by the European SSD Group are most popular today. This paper gives the results of using this index in a cohort of Russian patients