Are the results of shoulder joint replacement improving?

Is there evidence that the outcomes of primary anatomic and reverse shoulder arthroplasty are getting better?

These authors noted that the number of shoulder arthroplasty implants and related devices approved by the FDA are improving exponentially with time.

These new devices increase the cost of shoulder arthroplasty surgery because of their associated development, FDA approval and marketing costs as well as the learning curves and uncertainty of outcomes in comparison to devices that have been in use for longer periods of time.

The authors sought to use published evidence from studies published from 1990 to 2015 to answer the question, "are the patient-reported outcomes and re-operation rates better in reports of more recently performed anatomic (TSA) and reverse (RSA) total shoulder arthroplasties?" The difficulty in answering such a question lies in the fact that the study methods and patient cohorts differ among different reports, confounding attempts to compare the results.

Inclusion criteria for this investigation were met by 42 TSA studies with a mean (± SD) of 116±159 (range, 20–705) patients per study with an average follow-up of 5±3 years, 42±21% males with average age 66±5 years. Inclusion criteria were met by 37 RSA studies with 56±32 (20–174) patients per study with an average follow-up of 4±5 years, 34±15% males with average age 72±5 years.

In order to compare studies that used different outcome scales (ASES, SST, Constant, Dash, SANE, etc), the authors normalized each scale to a 0 (worst) to 100 (best) outcome score.  They considered the outcome in terms of the final post-operative score as well as the percent of maximal possible improvement (%MPI).  As shown in the figure below, the particular outcome scale used in the different publications had a major effect on the normalized outcome score for shoulder arthroplasty. For TSA, the mean normalized post-operative scores were ≥80% for reports using the WOOS, UCLA, Penn, and SANE scales and <65% using the DASH or Constant scales. For RSA, the mean normalized postoperative scores were ≥70% for the Oxford, ASES and VAS Pain scales and ≤60% for the SANE and UCLA scales. For both TSA and RSA the Simple Shoulder Test was at the median.

The diagnosis for which the arthroplasty was performed presented another confounder in the comparison among studies.  For reports of TSA, osteoarthritis (OA) was most common diagnosis (73% for an average study), but the percentage of patients with this diagnosis varied greatly from study to study (0–100%). For reports of RSA, the most common diagnosis was cuff tear arthropathy (CTA) (48% for an average study) but, again, the percentage of patients with this diagnosis varied greatly from study to study (0-100%). For both types of arthroplasty, the diagnosis had a significant effect on the outcome as shown in the figure below. For TSA the results were worse in those studies of rheumatoid arthritis (RA) and cuff tear arthropathy (CTA). Clinical outcomes for RSA were worse in studies of post-traumatic arthritis (PTA).

Over the two decades of this study, there were marginally significantly better clinical outcomes in reports of more recently performed TSAs (p = 0.048). The plots below show the mean outcome score adjusted for outcome scale and diagnosis by median year of surgery.

For RSA the trend showed no significant improvement.

Neither the revision rate for TSA (Coefficient -0.48, 95% CI from -1.35 to 0.39, p= 0.3) or the revision rate for RSA (Coefficient -0.84, 95% CI (from -2.87 to 1.19, p= 0.4) were significantly lower in studies reporting more recently performed procedures.

Comment: It appears that better evidence will be necessary to demonstrate that newer implants and techniques are yielding improved clinical outcomes for patients with glenohumeral arthritis.

The authors suggest that future studies reporting the results of shoulder arthroplasty should include an appendix containing a set of basic data elements for each patient so that meaningful comparisons can be facilitated. Such a data set should include for each patient the age, sex, diagnosis, the scale used to document the presurgical and postoperative patient self-assessed shoulder comfort and function, and date and reason for any reoperation. While this minimal data set will not capture the full set of potential confounders— such as the degree of shoulder stiffness, the condition of the rotator cuff, radiographic pathoanatomy and the effect of surgical team volume and experience—this degree of standardization will enable a more robust comparison of the outcomes for individual patients treated over time with different therapeutic approaches, so that we can learn whether newer implants and techniques contribute added value to the patient with glenohumeral arthritis.
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