Faculty Bibliography

Purpose: Game consoles such as Xbox, PS3 and Wii, in addition to handheld unit PSP, iTouch and iPhone are used by many children. Data regarding wrist and finger pain that may be caused by excessive use of these devices do not exist, especially in young children. We examined the possible association device type, age of children and hours played may have with wrist and finger pain. Method: 7-12 year olds attending Rossman Elemantary School in St Louis, MO, were administered a questionnaire asking about game consoles and hand-held devices used, hours played, and wrist or finger pain as reported on a 10cm VAS. Summary statistics of playing habits, devices played and pain levels were estimated. Multivariable generalized linear models associating consoles played, age and hours played to pain were constructed using standard backward selection techniques, determining the most significant independent predictors for pain. Results: 171 children completed the survey (mean age 9.7 years, 93 were female (54.4%). 84 (49.1%) reported 0-1 hours of play a day, 58 (33.9%) 1-2 hours, 12 (7%) 2-3 hours and 11 (6.4%) over 3 hours. 20 (11.7%) children reported finger pain and 17 (9.9%) reported wrist pain limiting their playing time. The mean (SD) pain level was 0.83 (1.82). Among the consoles Wii was the most commonly used (n=77, 45%), followed by Xbox/PS3 (n=9, 5.3%). 28 (16.4%) children played with none and 57 (33.3%) played both. For handhelds, Gameboy/PSP were played by 103 (60.2%) and iTouch/iPhone by 10 (5.8%). 39 (22.8%) played both and 19 (11.1%) played with neither. In beta regression, increasing age was independently associated with decreased odds of reporting pain (OR=0.65 (95% CI 0.57 - 0.75)); increasing hours played was associated with increased odds of reporting pain (OR=1.52 (95% CI 1.16-2.00)). Playing the Wii only was also independently associated with increased odds of reporting pain (OR=2.39 (95% CI 1.81-3.73)). In logistic regression, age was the only significant predictor of wrist pain (OR=0.68 (95% CI 0.48-0.96).No significant predictor of finger pain was observed. Conclusion: In children aged 7-12, 80% of which played with a console or handheld, younger age was associated with more wrist pain. Wii use was associated with more self-reported pain independent of age and hours played. Seven year olds reported the most pain as compared the other age groups. These findings may have implications for which age children should start playing with gaming consoles and handheld devices and possibly some limits in the hours they play

OBJECTIVES: Many randomized clinical trials (RCTs) are labelled efficacy and safety while due consideration for power is provided only for efficacy outcomes. This in turn necessitates a discussion of the inadequacy of sample size (type II error) for identifying harm. This is particularly important in RCTs of TNF inhibitors as harm related to these agents is still a matter of debate. METHODS: PubMed was searched for all RCTs published examining TNF inhibitors in RA, PsA and AS. Only original study reports were surveyed for whether: (i) they were labelled as efficacy, safety or both; (ii) the methods sections included safety as a primary or secondary end point; (iii) power calculations were adequately explained; (iv) statistical tests of significance were given for harm; and finally (v) any discussion of type II error for harm was present. RESULTS: Of the 34 articles surveyed, 24 (71%) were labelled as efficacy and safety. Among these, 23 (96%) did not include safety as a formal primary or secondary end point. In only 2/24 (8%) power calculations were given for safety. Finally, in only 3/22 (14%) any discussion about the inadequate sample size (type II error) for detecting harm could be found. CONCLUSIONS: Most reports of RCTs of TNF inhibitors in rheumatological diseases are inappropriately labelled as addressing efficacy and safety. Their lack of power in detecting harm is not adequately discussed, either.

OBJECTIVES: To analyse the capacity of routine assessment of patient index data 3 (RAPID3), an index of only the three patient-reported outcome (PRO) measures in the RA Core Data Set-physical function, pain and global status-to distinguish abatacept from control treatments in two clinical trials, and to compare RAPID3 results with the disease activity score 28 (DAS28) and RAPID-based indices that add a tender or swollen joint count and/or physician/assessor global estimate of status. METHODS: Clinical trial data from AIM (Abatacept in Inadequate response to Methotrexate) and ATTAIN [Abatacept Trial in Treatment of Anti-tumor necrosis factor (anti-TNF) INadequate responders] were reanalysed. Mean values were computed at baseline, endpoint and for change between baseline and endpoint for RAPID3, DAS28 and additional RAPID indices to study whether they had greater capacity to distinguish abatacept from control therapy. RAPID4TJC adds to RAPID3 a tender joint count; RAPID4SJC, a swollen joint count; RAPID4MD, a physician/assessor global estimate; and RAPID5 adds both a tender joint count and physician/assessor global estimate. RAPID2 includes only physician/assessor and patient global estimates. RESULTS: All indices indicated significant differences of 19-28% between abatacept and control groups. Results were similar for RAPID3 of only patient measures, compared to DAS28 and other RAPID-based indices. CONCLUSION: A RAPID3 'patient-only' index, without a joint count or any measure from a health professional or laboratory, distinguishes active from control treatments in two abatacept clinical trials, at levels similar to DAS28 and to other RAPID-based indices that add physician-reported measures

OBJECTIVE: To analyze the time required to score different measures used to assess patients with rheumatoid arthritis (RA), as a guide to feasibility in standard care. The measures studied were a 28-Joint Count, Disease Activity Score (DAS), Health Assessment Questionnaire (HAQ), Multidimensional HAQ (MDHAQ), and various Routine Assessment of Patient Index Data (RAPID) scores derived from the MDHAQ. METHODS: Three rheumatologists at 3 sites performed and timed 28-joint counts in 20 different patients at each site. Each rheumatologist scored and timed identical data in 5 groups of 10 from the same 50 patients seen in standard clinical care, including 50 DAS28 indices using the DAS Website, 50 identical HAQ, and 50 identical MDHAQ from the same patients. The MDHAQ includes 10 activities self-assessed for physical function, 21 circle visual analog scales (VAS) (rather than 10 cm lines), and scoring templates on the questionnaire for physical function, patient self-report joint count and RAPID composite scores. RAPID3 includes the 3 Core Data Set measures, RAPID4 adds the self-report joint count to RAPID3, and RAPID5 adds a physician global estimate to RAPID4. RESULTS: The median number of seconds to complete a 28-joint count was 90, compared to 41.9 s for a HAQ, 9.6 s for an MDHAQ RAPID3, and 19.4 s for RAPID5. CONCLUSION: MDHAQ RAPID3 scores can be calculated in considerably less time than other RA measures, using scoring templates on the MDHAQ, to provide informative, feasible, quantitative measures for standard rheumatology clinical care