This post examines two questions of importance to the surgeons and patients interested in shoulder arthroplasty:
(1) Over the past decade, is there evidence that patient-reported outcomes (PROs) after shoulder arthroplasty have gotten better by a clinically significant amount — that is, by at least the minimal clinically important difference (MCID)?
(2) If they have, is that improvement associated with the surgeon, the technology, the shoulder, or the patient?
Based on the available evidence, the answers are: (1) yes, modestly; and (2) the gain is not attributable to new technology or to any change in the shoulders we treat. The largest lever on the outcome is the patient, while the decade’s trend itself most plausibly reflects accumulated surgical experience and care.
A word on the measure. Surrogates — such as radiographic component position, glenoid version, three-dimensional planning accuracy, and data on implant survivorship drawn from registries — are not the outcomes of primary interest. The important outcome is what the patients report. A technology that improves a surrogate but does not move a PRO beyond its MCID has not improved the outcome for the patient.
Now the detail.
1. Are patient-reported outcomes improving over time?
Anatomic TSA (aTSA). In a single-institution series of 1,899 arthroplasties (2008–2018), the 5-year ASES improvement rose by 1.65 points per year of index surgery on univariable analysis and by 2.20 points per year after adjustment for patient factors [1]. The per-year increment is small — well under one MCID — and reaches clinical significance only when accumulated across the decade. The authors could not attribute the gain to any single factor [1].
Reverse TSA (RSA). Some of the most relevant data come from the U.K. National Joint Registry (24,411 RSAs, 2013–2021): mean 6-month Oxford Shoulder Score (OSS) improvement rose from 15.84 to 20.29 — about half a point per year, roughly one MCID across the whole period [2].
In the Danish Shoulder Arthroplasty Registry (2,867 arthroplasties for osteoarthritis, 2006–2015), the adjusted WOOS score rose by about 10 points [3] — short of the WOOS MCID of 12.3 [16].
So.....both aTSA and RSA show measured, year-over-year PRO improvement. The increments are small per year and reach clinically meaningful magnitude only when accumulated across the decade — about one MCID for RSA across the period, and a larger accumulated difference for aTSA, whose adjusted per-year gain compounds over ten years. These are population- and cohort-level shifts: a patient operated late in the decade does modestly better, on average, than one operated early.
Survivorship bias. A patient-reported outcome plotted against time after surgery is available only for survivors: to contribute a 6-month OSS or a 5-year ASES, a patient must be alive, unrevised, and reachable. Those who die, are revised, or move their care to another surgeon before the minimum follow-up never enter the average — which is therefore selected for better outcomes.
Which way this biases the trend is not obvious. Perioperative mortality and early reoperation fell across this same decade [2], so fewer patients were removed by death in the later years; if anything the later cohorts are less selected, and across-year survivorship is unlikely to be what produced the rising trend. The selection that matters is not across calendar years but across follow-up length — the late-timepoint averages rest on progressively smaller, more selected subsets of the original cohorts.
Implant durability is vulnerable to the same problem in a more specific way. When revision is estimated with a standard Kaplan–Meier survival curve, a patient who dies is treated as still at risk of a revision that can no longer occur. This overestimates the cumulative revision rate, and it overestimates most where mortality is highest — the older patients who receive reverse replacements [15]. Comparisons of durability across groups with different mortality are confounded for the same reason: part of any apparent difference reflects who lived long enough to ever reach a revision, not how the implant performed. Revision rates in older, higher-mortality groups should accordingly be read as upper bounds rather than firm figures [15].
The usual adjustments for age, comorbidity, and surgeon volume operate only among the patients who actually reported a score; they cannot recover those missing because they died or never returned. So even where adjustment strengthens the trend [1], survivorship bias remains in the data. It matters most where follow-up completion is low and uneven, as it was in the National Joint Registry [2].
So two cautions in reading these data. The within-period findings — smoking [9], unemployment and education [10], resilience and mental health [11], and the absence of any effect of glenoid shape [5] or technology [4] — compare patients operated on in the same period, so the across-year attrition that inflates the temporal trend cannot account for them. The year-over-year trend is the vulnerable part: surgeon experience, technique, rehabilitation, and perioperative care all improved over the same years, so a dataset of this kind cannot apportion the gain among them; the measured improvement is best taken as the most that can be claimed, not a precise figure.
2. The surgeon, the technology, the shoulder, or the patient — what is the change associated with?
The surgeon. Surgeon volume and fellowship training have a well-documented effect on revision, reoperation, complications, and length of stay — and a weak-to-absent effect on the size of the PRO improvement patients realize. In the National Joint Registry, surgeons averaging at least 10.4 shoulder replacements a year had lower revision risk (the hazard of revision roughly doubled below that threshold) along with fewer reoperations, fewer serious adverse events, and shorter stays, but no patient-reported outcome was assessed [12]. Fellowship training shows the same pattern: shoulder-and-elbow and sports-medicine fellowship-trained surgeons have significantly lower complication rates at 90 days, 1 year, and 5 years, again with no PRO assessed [14]. The most direct test comes from the Australian registry: a surgeon’s two-year revision rate showed no clinically relevant correlation with PROMs, and all surgeons produced similar postoperative Oxford scores [13]. Revision rates and PROs measure two different facets of the result — surgeon factors move the first; patient factors move the second.
The technology. Advanced technology does not appear to be related to patient-reported outcomes. A systematic assessment of three-dimensional planning, patient-specific instrumentation, navigation, stemless humeral components, and augmented glenoid components found that no individual technology was associated with a statistically or clinically significant improvement in PROs [4]. A single-surgeon consecutive series of 389 anatomic arthroplasties reaches the same conclusion from the other side: implant choice and surgical technology do not predict outcome [5]. The durable result there came from fundamentals — subscapularis management, a conservative neck cut, a securely seated all-polyethylene glenoid, soft-tissue balancing — not new technology.
Cross-linked polyethylene is the one material change with an apparent benefit: in the Australian registry it had a lower anatomic revision rate than conventional polyethylene [6]. But the benefit is on durability — reduced wear-particle osteolysis and loosening — not on comfort and function; no study has shown that it improves PROs. And the advantage appears smaller in contemporary practice, where glenoid component design and fixation, not polyethylene type, emerge as the dominant predictor of revision [7].
The shoulder. Glenoid morphology — the usual proxy for a “worse” arthritic shoulder — does not predict outcome: in a 389-case series, B2 and B3 glenoids met or exceeded the outcomes of other glenoid types, and symptomatic glenoid loosening occurred in 1 of 389 shoulders [5]. Nor has the case mix drifted toward milder disease. In the Australian registry, the reverse diagnosis mix barely changed across the decade — osteoarthritis fell only slightly as a share of reverse procedures (48.2% to 44.7%) while cuff arthropathy rose by almost the same margin (36.2% to 39.7%) — if anything a drift toward classic cuff-deficient disease, the opposite of an “easier shoulders” explanation [8]. A shift in shoulder characteristics does not appear to be driving the PRO gain.
The patient. The data point to the patient — and to the judgment applied in selecting and preparing the patient. Three patient-side domains stand out. Modifiable risk: in an analysis of 14,465 arthroplasties, smoking was independently associated with increased surgical complications [9]; cessation, along with glycemic, nutritional, and opioid optimization, appears to improve the result. Socioeconomic context: in a nationwide cohort of 2,292 arthroplasties, after adjustment for age, sex, diagnosis, implant, and comorbidity, unemployment was associated with a WOOS deficit of roughly 14 to 19 points at one year and lower educational attainment with a further 5 to 8 points [10] — differences that exceed the MCID. Resilience and mental health: in 399 anatomic arthroplasties, greater resilience and better mental health were associated with better outcomes [11].
So among the candidate factors, the patient is the strongest predictor of the outcome a given arthroplasty achieves — selection, optimization, socioeconomic context, and resilience each move the PRO, several beyond the MCID. Whether the patient mix shifted across the decade in a way that would explain the time trend is a separate question, and these data do not show that it did.
Conclusion
The evidence answers both opening questions.
First, patient-reported outcomes after shoulder arthroplasty have improved over the past decade — modestly, and by an amount that reaches the MCID only when accumulated across the period, not within any single year.
Second, two different questions hide inside "what is the change associated with," and they have different answers.
(A) The decade-long trend is real but cannot be apportioned by the available data; it is most plausibly the product of accumulated surgeon experience, refinements in technique, rehabilitation, and perioperative care. The case mix did not drift toward easier shoulders [8], and no individual technology was associated with the improved outcomes over the decade [4].
(B) The other question — what determines the result for an individual patient — has a clearer answer. The available evidence has not shown a patient-reported benefit from any technology assessed, nor from any change in the shoulders we treat. Surgeon volume and training affect revision and complication rates, but not, as far as the data show, the patient-reported result. That leaves the patient: selection, optimization of modifiable risk, socioeconomic context, and resilience.
The greatest demonstrated effect on the outcome therefore lies in choosing and preparing the patient; the experience the surgeon brings to the procedure most likely matters too, though these data cannot show by how much. Whether any new technology will eventually be shown to improve the patient-reported outcome beyond the MCID remains the open question for the next decade; none yet has.
Will the future be better?
Broad-billed Hummingbird
Tucson
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References
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