Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT04836988 |
| Other study ID # |
Observational |
| Secondary ID |
|
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
March 6, 2021 |
| Est. completion date |
March 30, 2021 |
Study information
| Verified date |
October 2023 |
| Source |
Lund University |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational [Patient Registry]
|
Clinical Trial Summary
This study will compare outcomes of two different delivery methods (Face-to-face and
digitally) of first-line treatment for hip and knee osteoarthritis.
Description:
According to international guidelines, exercise and education should constitute the
first-line intervention for people with knee and hip osteoarthritis (OA) and have been shown
to be effective in reducing OA symptoms regardless of disease severity. To implement those
guidelines, the Better Management of Patients with OsteoArthritis (BOA), a face-to-face
concept including education and an option to exercise, has been developed and are offered at
primary care clinics in Sweden since 2008. However, traditional face to face interventions
present barriers, such as limited access and lack of flexibility, which may limit the
patients' adherence with the interventions. In an effort to overcome such barriers, a digital
self-management program (Joint Academy) that is based on the BOA concept started in 2014.
Although, both delivering methods have been reported to reduce OA symptoms in patients with
hip and/or knee OA, little is known whether the results of digital interventions are
comparable with traditional face-to-face rehabilitation programs. In this retrospective
register-based study we will compare the outcomes of the two different modalities of
first-line treatment delivery (face-to-face vs digitally) after 3 months program
participation using data from the BOA and Joint Academy registers. Main outcome will be
self-reported change in pain between baseline and three months follow-up and secondary
outcomes will be change in self-reported walking difficulties, willingness for joint surgery
and health-related quality of life between baseline and three months follow-up.
Statistical analysis In this study we will include all participants in the digital program
fulfilling the eligibility criteria outlined below (n >2000). These participants will be
matched 1:1 to participants in the BOA register using the propensity scoring approach. The
minimum clinically important difference is typically considered to be one unit on a 0-10 NRS
scale. To obtain a 95% confidence interval for the between-group difference with a width of
at most 0.5 units (i.e. very precise) in a sample with a typical standard deviation of 1.5,
with 99% probability, we will need ~630 patients in total.
We will use observational data to emulate an equivalence trial comparing the effect on joint
pain of a digitally delivered first-line intervention and of an in-person delivered first
line intervention for people with OA of the hip or knee. In order to establish equivalence
between the interventions the pain change after the intervention should differ of less than
1-point on a 0-10 NRS pain scale. This cut off was selected based on previous work
identifying 1-point change as the MCID in people with OA. The main outcome will be analyzed
using a propensity score matching approach. We will estimate the propensity score using a
logistic regression model, in which we will regress the treatment status on the observed
baseline characteristics of the participants. The characteristics to include in the
propensity score will be selected using the disjunctive cause criteria, including factors in
the analysis identified as causes of treatment allocation(exposure) and/or the pain change
(outcome). We will use nearest neighbor matching to select controls (BOA participants) whose
propensity score is closest to that of the treated subject. Furthermore, we will use an
optimal matching strategy to minimize the total within-pair difference of the propensity
score. Within-pair differences in main outcome will be analysed using a paired t-test.
Finally, we will adjust the analysis for baseline pain in order to increase the precision of
the estimates and minimize the regression to the mean effect
