Do the Revision Rates of Arthroplasty Surgeons Correlate With Postoperative Patient-reported Outcome Measure Scores? A Study From the Australian Orthopaedic Association National Joint Replacement Registry.
Patient-reported outcome measures (PROMs) are a pragmatic and efficient means to evaluate the functional quality of arthroplasty beyond revision rates, which are used by most joint replacement registries to judge success. The relationship between these two measures of quality-revision rates and PROMs-is unknown, and not every procedure with a poor functional result is revised. It is logical-although still untested-that higher cumulative revision rates correlate inversely with PROMs for individual surgeons; more revisions are associated with lower PROM scores.
We used data from a large national joint replacement registry to ask: (1) Does a surgeon's early THA cumulative percent revision (CPR) rate and (2) early TKA CPR rate correlate with the postoperative PROMs of patients undergoing primary THA and TKA, respectively, who have not undergone revision?
Elective primary THA and TKA procedures in patients with a primary diagnosis of osteoarthritis that were performed between August 2018 and December 2020 and registered in the Australian Orthopaedic Association National Joint Replacement Registry PROMs program were eligible. THAs and TKAs were eligible for inclusion in the primary analysis if 6-month postoperative PROMs were available, the operating surgeon was clearly identified, and the surgeon had performed at least 50 primary THAs or TKAs. Based on the inclusion criteria, 17,668 THAs were performed at eligible sites. We excluded 8878 procedures that were not matched to the PROMs program, leaving 8790 procedures. A further 790 were excluded because they were performed by unknown or ineligible surgeons or were revised, leaving 8000 procedures performed by 235 eligible surgeons, including 4256 (53%; 3744 cases of missing data) patients who had postoperative Oxford Hip Scores and 4242 (53%; 3758 cases of missing data) patients who had a postoperative EQ-VAS score recorded. Complete covariate data were available for 3939 procedures for the Oxford Hip Score and for 3941 procedures for the EQ-VAS. A total of 26,624 TKAs were performed at eligible sites. We excluded 12,685 procedures that were not matched to the PROMs program, leaving 13,939 procedures. A further 920 were excluded because they were performed by unknown or ineligible surgeons, or because they were revisions, leaving 13,019 procedures performed by 276 eligible surgeons, including 6730 (52%; 6289 cases of missing data) patients who had had postoperative Oxford Knee Scores and 6728 (52%; 6291 cases of missing data) patients who had a postoperative EQ-VAS score recorded. Complete covariate data were available for 6228 procedures for the Oxford Knee Score and for 6241 procedures for the EQ-VAS. The Spearman correlation between the operating surgeon's 2-year CPR and 6-month postoperative EQ-VAS Health and Oxford Hip or Oxford Knee Score was evaluated for THA and TKA procedures where a revision had not been performed. Associations between postoperative Oxford and EQ-VAS scores and a surgeon's 2-year CPR were estimated based on multivariate Tobit regressions and a cumulative link model with a probit link, adjusting for patient age, gender, ASA score, BMI category, preoperative PROMs, as well as surgical approach for THA. Missing data were accounted for using multiple imputation, with models assuming they were missing at random and a worst-case scenario.
Of the eligible THA procedures, postoperative Oxford Hip Score and surgeon 2-year CPR were correlated so weakly as to be clinically irrelevant (Spearman correlation ρ = -0.09; p < 0.001), and the correlation with postoperative EQ-VAS was close to zero (ρ = -0.02; p = 0.25). Of the eligible TKA procedures, postoperative Oxford Knee Score and EQ-VAS and surgeon 2-year CPR were correlated so weakly as to be clinically irrelevant (ρ = -0.04; p = 0.004 and ρ = 0.03; p = 0.006, respectively). All models accounting for missing data found the same result.
A surgeon's 2-year CPR did not exhibit a clinically relevant correlation with PROMs after THA or TKA, and all surgeons had similar postoperative Oxford scores. PROMs, revision rates, or both may be inaccurate or imperfect indicators of successful arthroplasty. Missing data may limit the findings of this study, although the results were consistent under a variety of different missing data scenarios. Innumerable factors contribute to arthroplasty results, including patient-related variables, differences in implant design, and the technical quality of the procedure. PROMs and revision rates may be analyzing two different facets of function after arthroplasty. Although surgeon variables are associated with revision rates, patient factors may exert a stronger influence on functional outcomes. Future research should identify variables that correlate with functional outcome. Additionally, given the gross level of function that Oxford scores record, outcome measures that can identify clinically meaningful functional differences are required. The use of Oxford scores in national arthroplasty registries may rightfully be questioned.
Level III, therapeutic study.
Hoskins W
，Bingham R
，Corfield S
，Harries D
，Harris IA
，Vince KG
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Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.
Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided.
(1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS?
Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses.
Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS.
Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments.
Level III, diagnostic study.
Lee CC
，Chen CW
，Yen HK
，Lin YP
，Lai CY
，Wang JL
，Groot OQ
，Janssen SJ
，Schwab JH
，Hsu FM
，Lin WH
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ResearchGate
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