Evaluating Glenohumeral Osteoarthritis: The Relative Impact of Patient Age, Activity Level, Symptoms, and Kellgren-Lawrence Grade on Treatment

Adam Schumaier; Joseph Abboud; Brian Grawe; J Gabriel Horneff; Charles Getz; Anthony Romeo; Jay Keener; Richard Friedman; Ed Yian; Stephanie Muh; Gregory Nicholson; Ruth Delaney; Randall Otto; William William; JT Tokish; Gerald Williams; Jack Kazanjian; Joshua Dines; Matthew Ramsey; Andrew Green; Scott Paxton; Surena Namdari; Brody Flanagin; Samer Hasan; Scott Kaar; Anthony Miniaci; Frances Cuomo

. 2019 Mar;7(2):151–160.

Evaluating Glenohumeral Osteoarthritis: The Relative Impact of Patient Age, Activity Level, Symptoms, and Kellgren-Lawrence Grade on Treatment

Adam Schumaier ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Joseph Abboud ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Brian Grawe ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, J Gabriel Horneff ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Charles Getz ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Anthony Romeo ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Jay Keener ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Richard Friedman ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Ed Yian ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Stephanie Muh ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Gregory Nicholson ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Ruth Delaney ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Randall Otto ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, William William ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, JT Tokish ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Gerald Williams ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Jack Kazanjian ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Joshua Dines ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Matthew Ramsey ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Andrew Green ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Scott Paxton ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Surena Namdari ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Brody Flanagin ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Samer Hasan ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Scott Kaar ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Anthony Miniaci ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹, Frances Cuomo ^1,^2,^3,^4,^5,^6,^7,^8,^9,^10,^11,^12,^13,^14,^15,^16,^17,^18,¹⁹

PMCID: PMC6510923 PMID: 31211193

Abstract

Background:

It is not always clear how to treat glenohumeral osteoarthritis, particularly in young patients. The goals of this study were to 1) quantify how patient age, activity level, symptoms, and radiographic findings impact the decision-making of shoulder specialists and 2) evaluate the observer reliability of the Kellgren-Lawrence (KL) grading system for primary osteoarthritis of the shoulder.

Methods:

Twenty-six shoulder surgeons were each sent 54 simulated patient cases. Each patient had a different combination of age, symptoms, activity level, and radiographs. Responders graded the radiographs and chose a treatment (non-operative, arthroscopy, hemiarthroplasty, or total shoulder arthroplasty). Spearman correlations and chi square tests were used to assess the relationship between factors and treatments. Sub-analysis was performed on surgical cases. An intra-class correlation (ICC) was used to assess observer agreement.

Results:

The significant correlations (P<0.01) were: symptoms [0.46], KL grade [0.44], and age [0.11]. In the sub-analysis of operative cases, the significant correlations were: KL grade [0.64], age [0.39], and activity level [-0.10]. The chi square analysis was significant (P<0.01) for all factors, but the practical significance of activity level was minimal. The ICCs were [inter](intra): KL [0.79] (0.84), patient management [0.54].

Conclusion:

When evaluating glenohumeral osteoarthritis, patient symptoms and KL grade are the factors most strongly associated with treatment. In operative cases, the factors most strongly associated with the choice of operation were the patient’s KL grade and age. Additionally, the KL classification demonstrated excellent observer reliability. However, there was only moderate agreement among shoulder specialists regarding treatment, indicating that this remains a controversial topic.

Key Words: Clinical decision-making, Glenohumeral osteoarthritis, Hemiarthroplasty, Kellgren-lawrence, Patient factors, Total shoulder arthroplasty

Introduction

Arthritis is projected to affect around 18% of the U.S. population by 2020 (1). The prevalence of arthritis in the glenohumeral joint has not been defined, but shoulder arthroplasty is now the third most frequently performed joint replacement procedure (2). Despite the proven benefits of arthroplasty, it is not always clear which patients are appropriate candidates for shoulder arthroplasty and which patients should be treated non-operatively or arthroscopically. Further, the most suitable type of shoulder arthroplasty (total shoulder arthroplasty or hemiarthroplasty) remains debatable in certain patient populations as well (3). Evaluation and management is particularly challenging in patients who are young, highly active, or have minimal radiographic signs of glenohumeral arthritis. In young patients, some studies suggest arthroplasty leads to unsatisfactory results (4). In highly active individuals, there are concerns for prosthetic longevity (5–7). Radiographically low-grade arthritis may be more amenable to arthroscopic debridement than high-grade arthritis, but radiographic and symptom severity often do not correlate (8-12).

It is not clear which factors are most important to shoulder surgeons when deciding between non-operative management, arthroscopic treatment, or joint replacement. The goal of this study was to quantify how various patient and shoulder specific factors impact the decision-making of shoulder specialists. Secondarily, we sought to evaluate the inter and intra observer reliability of the Kellgren-Lawrence (KL) grading system and to determine if this correlates with surgeons’ treatment recommendations. The researchers wanted to determine which factors were most important to shoulder surgeons when making clinical decisions, improve our ability to radiographically classify glenohumeral arthritis, and aid future research by establishing specific factors that are most relevant to surgical decision-making. The study hypotheses were that symptoms and radiographic findings would be the factors most strongly associated with treatment and that there would be good agreement on the radiographic classification of glenohumeral osteoarthritis but disagreement on the treatment.

Materials and Methods

A case-based survey study was sent to 26 practicing, fellowship trained shoulder surgeons in August and September of 2017. The survey was composed of 54 simulated cases of patients “presenting” with glenohumeral arthritis that were accompanied by shoulder x-rays. Each patient presented with a different combination of age, symptoms, and activity level. Each factor was equally represented and each specific combination occurred exactly once. The patients were either age 30, 45, or 65 years old. These ages were selected because they were felt to be sufficiently spaced out to detect the effect of age on treatment. The activity level was either low, moderate, or high. The symptoms were either mild, moderate, or severe. The vignette for symptoms and activity level are as follows:

Activity Level: [Low] inactive, very low demand with their shoulder; [Moderate] works a desk job, enjoys playing recreational basketball and lifting weights; [High] active, manual laborer

Symptoms: [Mild] only during strenuous activities; [Moderate] predominant symptoms that limit most things; [Severe] constant

To test each combination of age, activity level, and symptoms, 27 cases were required. Each of the 27 cases was then paired with either a low-grade (1 or 2) or a high-grade (3 or 4) radiograph per the Kellgren-Lawrence system, arriving at the case number of 54 total (13). There was a true anterior-posterior (AP) “Grashey” and an axillary radiograph of the glenohumeral joint provided for each case. The grade of each radiograph was agreed upon by two authors (B.N.G. and J.A.A.) prior to assigning the radiographs to patient cases.

There were 2 questions for each case. The first question asked the surgeon to grade the radiographs from 1 to 4 per the KL scale. Briefly, the classification system is graded in the following manner: Grade 1: doubtful narrowing of joint space and possible osteophytic lipping, Grade 2: definite osteophytes, definite narrowing of joint space, Grade 3: multiple osteophytes, definite narrowing of joint space, some sclerosis, and possible deformity of bone contour, Grade 4: large osteophytes, marked narrowing of joint space, severe sclerosis, and definite deformity of bone contour. No Grade 0 was included as all patients had some level of shoulder osteoarthritis. The second question asked the surgeon to choose a treatment for the patient. The 4 treatment choices were 1) non-operative [medications, injections, physical therapy, or watchful waiting], 2) arthroscopic treatment, 3) hemiarthroplasty, and 4) total shoulder arthroplasty. Throughout the survey, the surgeons were asked to assume that the rotator cuff was intact and that each patient had mild success with one attempt at non-operative care including a corticosteroid injection into the glenohumeral joint and physical therapy. The cases were randomized, so each surgeon reviewed the cases in a different order. The survey was sent a second time one month later, but for the second survey, the surgeons were only asked to grade the radiographs. This was done to calculate the intra-observer reliability for the KL grading system. The full survey is attached as a supplement.

It was assumed all 26 surgeons would complete the 54 cases, which would lead to a total number of 1,404 individual responses (26 x 54). This number of responses provides greater than 90% power to detect a moderate correlation (r=0.4) with an alpha of 0.05. A Spearman rs correlation coefficient and chi square test for independence were performed to quantify how the surgeons’ treatment decisions were related to patient age, activity level, symptoms, and radiographic grade. The treatments were converted to an ordinal scale based on progression of care (i.e., non-operative = 1, arthroscopy = 2, hemiarthroplasty = 3, and total shoulder arthroplasty = 4) in order to calculate the Spearman correlation. The treatments were then individually correlated with age, activity level, symptoms, and radiographic grade. To assess for confounding factors, the radiographic grade was correlated with age, activity level, and symptoms. An additional sub-analysis was performed on the cases for which surgeons chose an operative intervention to correlate patient factors with the type of operation chosen. A correlation of 0 suggests no association and a correlation of 1 suggests perfect association. In this study, the spearman correlations were interpreted according to the effect sizes suggested by Cohen: [weak < 0.3]; [moderate 0.3 to 0.5]; [strong > 0.5] (14).

All 26 surveyed surgeons completed each of the 54 cases, so the inter- and intra-rater reliability was assessed using a two-way mixed agreement, single measures intra-class correlation coefficient (ICC). The ICC is similar to a weighted kappa statistic, except that it can accommodate more than two raters (15, 16). The ICC was interpreted according to Cicchetti: [poor<0.4]; [fair 0.40 to 0.59]; [good 0.60 to 0.74], [excellent >0.75] (17). All statistical tests were performed using R version 3.4.0 (R Foundation for Statistical Computing, Vienna, Austria) with RStudio version 1.0.153 (RStudio Inc, Boston, Massachusetts) (18, 19). The following R packages were used: irr (Gamer, Lemon, and Singh [version 0.84]), RVAideMemoire (Hervé [version 0.9-68]), pwr (Champely [version 1.2-1]) (20-22).

Results

The first survey, which assessed both KL grading and choice of treatment, was completed by 26 surgeons. The second survey, which assessed only KL grading for a second time in order to calculate intra-observer reliability, was completed by 22 surgeons (84.6%). The Spearman correlations for each of the patient factors and the treatment choices ranged from none to moderate [Table 1] (rs, [95% CI], p-value). Symptoms (0.46, [0.41 to 0.50], P<0.001) and KL grade (0.44, [0.40 to 0.49], P<0.001) had a moderate correlation, indicating that more severe symptoms and higher KL grades were more likely to result in surgical treatment decisions [Figures 1; 2]. The Spearman correlation for age had a weak correlation (0.11, [0.05 to 0.16], P<0.01), while the correlation for activity level was very low and statistically insignificant (0.01, [-0.05 to 0.06], P=0.98). In the sub-analysis of cases where operative treatment was chosen (n=813) [Table 2], the correlations were moderate for KL grade (0.64, [0.59 to 0.68], P<0.001) and age (0.39, [0.33 to 0.45], P<0.001), indicating that higher KL grades and older age were more likely to result in escalation of surgical treatment [Figures 3; 4]. The correlation between surgical treatment and activity level was weakly negative (-0.11, [-0.18 to -0.04], P=0.001) and was not statistically significant for symptoms (0.02, [-0.05 to 0.09], P=0.66). The chi squared independence tests for each of the patient factors as related to all treatment options was statistically significant (activity, P=0.034; age, P<0.001; KL, P<0.001; symptoms, P<0.001), but the practical significance was minimal for activity level [Table 2].

Table 1.

Spearman correlations for each patient factor as it relates to treatment chosen for all cases (top) and sub-analysis of operative cases (bottom)

Correlation Between Patient Factors and Treatment (Non-operative and Operative Cases, n=1404)
	Spearmanr (95% CI)	*P-value*	Interpretation
Symptoms	0.46 (0.41 to 0.50)	P < 0.001	Moderate
KL	0.44 (0.40 to 0.49)	P < 0.001	Moderate
Age	0.11 (0.05 to 0.16)	P < 0.001	Weak
Activity	0.01 (-0.05 to 0.06)	P = 0.81	None
Correlation Between Patient Factors and Treatment (Sub-analysis of Operative Cases, n=813)
	Spearmanr (95% CI)	P-value	Interpretation
KL	0.64 (0.59 to 0.68)	P < 0.001	Strong
Age	0.39 (0.33 to 0.45)	P < 0.001	Moderate
Activity	-0.11 (-0.18 to -0.04)	P = 0.001	Weak
Symptoms	0.02 (-0.05 to 0.09)	P = 0.66	None

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Percentage of cases (n=1,404) that surgeons recommended operative treatment based on the patient’s symptoms

Percentage of cases (n=1,404) that surgeons recommended operative treatment based on the patient’s KL grade

Table 2.

Frequency of treatments chosen grouped by patient factors. The p-value for each chi square test is in parenthesis

Treatment Decisions Based on Patient Specific Factors (chi-squared analysis)
Kellgren-Lawrence ( *P<0.001* )	Grade 1	Grade 2	Grade 3	Grade 4
Non-op	63%	50%	38%	26%
Arthroscopy	34%	38%	20%	4%
HA	0%	3%	12%	12%
TSA	3%	9%	29%	58%
Symptom Severity ( *P<0.001* )	Mild	Mod	Severe
Non-op	79%	28%	19%
Arthroscopy	9%	25%	30%
Hemi	2%	11%	10%
TSA	9%	36%	40%
Age ( *P<0.001* )	30 y.o.	45 y.o.	65 y.o.
Non-op	43%	43%	45%
Arth	32%	22%	13%
Hemi	16%	7%	1%
TSA	12%	32%	44%
Activity Level ( *P=0.034* )	Low	Mod	High
Non-op	46%	45%	40%
Arth	18%	23%	26%
Hemi	6%	8%	10%
TSA	34%	28%	28%

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Sub-analysis of operative cases (n=813): percentage of cases that surgeons recommended arthroscopy, hemiarthroplasty, or total shoulder arthroplasty based on the patient’s KL grade (low grade= KL 1-2, high grade = KL 3-4).

In total, 1,404 radiographs were graded from the first survey (KL 1 [280], KL 2 [288], KL 3 [410], KL 4 [426]). In total, 1,188 radiographs were graded from the second survey (KL 1 [232], KL 2 [244], KL 3 [346], KL 4 [366]). For the assessment of confounding factors, there was no significant correlation with radiographic grade and age (P=0.45), activity level (P=0.21), or symptoms (P=0.35). The ICC to assess the inter-observer reliability for KL grading was 0.79 [0.72 to 0.85, P<0.001] and intra-observer reliability was 0.84 [0.82 to 0.85, P<0.001]. The ICC to assess inter-observer agreement of treatment choices was 0.54 [0.44 to 0.64, P<0.001] [Table 3].

Table 3.

Intra-class correlation coefficients for the inter- and intra-observer reliability of the KL grading system and the inter-observer agreement for treatments

Inter and Intra Observer Reliability of Survey Responders (n=26[responders], n=1404[cases])
	ICC (95% CI)	*P-value*	Interpretation
Radiographic Grading (Inter)	0.79 (0.72 to 0.85)	P < 0.001	Good to Excellent
Radiographic Grading (Intra) ^*	0.84 (0.82 to 0.85)	P < 0.001	Excellent
Treatment Choices (Inter)	0.54 (0.44 to 0.65)	P < 0.001	Fair to Good

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n=22[responders], n=1188[cases]

Discussion

Osteoarthritis of the glenohumeral joint can cause significant pain and disability (23). Deciding how to treat patients can be difficult, especially those who are young and highly active (24). Age, activity level, symptoms, and radiographic signs of arthritis are commonly used to evaluate this condition (25). The goal of our study was to quantify how each of these factors influences the surgeon’s choice of non-operative management, arthroscopic treatment, and arthroplasty.

Age

Treatment of glenohumeral arthritis in the young and middle-aged patient is a controversial topic (25–27). The young patient often presents with arthritis secondary to other conditions besides primary osteoarthritis, has higher expectations, and is more likely to eventually experience implant failure (28). Most authors recommend non-operative management (24, 26, 29). Interestingly, our study found that the rates of non-operative management were nearly identical in all age groups. Age was only slightly correlated with management (rs=0.12), but age had a much more significant role in the choice of operation (rs=0.39), as surgeons favored arthroscopy in younger patients. Arthroscopy is useful as a joint preserving treatment that can identify and address conditions like biceps pathology or labral disease (27). There are studies suggesting arthroscopy can reduce pain and prevent arthroplasty, particularly in patients with earlier stage radiographic arthritis (8, 9, 30). This makes such treatment an attractive option for young patients. However, the results of arthroscopic treatment may be inferior for patients with less than 2 mm of joint space remaining (31, 32).

Among cases where joint replacement was selected for the youngest age group in our study, hemiarthroplasty was slightly favored over total shoulder arthroplasty. Hemiarthroplasty could be favored in the young patient because it theoretically offers a degree of glenoid preservation; however, studies suggest it is inferior to total shoulder replacement in terms of pain relief and restoring range of motion with a higher rate of revision (33, 34). Appropriate patient selection for hemiarthroplasty and total shoulder arthroplasty is paramount, as later conversion from hemiarthroplasty to total shoulder arthroplasty may be less successful than a primary total shoulder arthroplasty (35, 36). As well, most published studies investigating hemiarthroplasty and total shoulder arthroplasty in young patients include patients who are mostly near 50 years of age, and it is unclear if the conclusions in these studies can be extrapolated to much younger patients (37–42). From a cost-analysis perspective, an economic decision model by Bhat et al. that also evaluated quality-adjusted-life-years favored total shoulder arthroplasty over hemiarthroplasty in patients who are 30 to 50 years old with glenohumeral arthritis (43). Still, it is unclear if joint preservation with hemiarthroplasty is more successful than total shoulder replacement in the long-term, which likely explains why these procedures were selected at roughly equal rates for the young patients in our study. This is in contrast to the older patients in which total shoulder arthroplasty was clearly favored when a surgical solution was chosen.

Activity Level

Activity level is thought to be an important factor for determining the treatment of glenohumeral arthritis due to the risks associated with implant longevity and component loosening (24, 27, 28, 44). Interestingly, this was the least significant factor in our study with an rs of 0.007. There was a slight negative correlation (rs=-0.1) when analyzing only the cases where operative management was recommended, which indicates that as patients became more active, surgeons were slightly more likely to recommend arthroscopy or hemi arthroplasty compared to total shoulder arthroplasty. Given that the humeral component tends to have satisfactory longevity at long-term follow-up, the decision for hemiarthroplasty over total shoulder arthroplasty could be due to concerns for longevity of the glenoid component in a total shoulder arthroplasty (44, 45).

Symptoms

Symptoms are an important factor in treating any patient, and it is not surprising that this was the factor most strongly correlated with management (rs=0.46). However, symptom severity was not important for deciding what type of operation to choose in the surgical cases (rs=0.02). This demonstrates that the subjective description of symptoms is most important for indicating a patient for surgical treatment, but more objective variables such as radiographic grade of arthritis and age are most important for determining the type of surgery performed.

Radiographic Grade

There are multiple classification systems that have been used for classifying glenohumeral arthropathy with plain radiographs. There is the Samilson and Prieto with Allain and Gerber modifications, Weinstein, Guyette, and KL classifications (30, 46-51). A 2013 study by Elsharkawi included two observers and found excellent inter- and intra-observer reliability with all of these classifications (51). The authors provide a thorough description of each classification (51). In general, each classification assesses osteophytes, joint space narrowing, and sclerosis. We chose the KL classification because it is the most widely used system for classifying arthritis (52, 53). Although it was not originally applied to the glenohumeral joint, the radiographic findings of arthritis are reasonably consistent across most joints, including the shoulder (with the exception of posterior wear) (13, 54).

We found excellent inter- and intra-observer agreement for the KL classification system. Further, it was moderately correlated with patient management (rs=0.44) and had the strongest correlation with choice of operation in the surgically treated cases (rs=0.64). This suggests that it was the only factor that was important for both deciding to operate and which type of operation to perform. Multiple studies have shown that low radiographic grade is an important factor in the success of arthroscopic management of glenohumeral arthritis (8, 9, 30, 55). In support of these studies, we found that surgeons preferred arthroscopy for grade 1 and 2 arthritis. There was little consensus for treating grade 3 arthritis, which had a broad distribution of non-operative management (39%), arthroscopy (20%), hemiarthroplasty (12%), and total shoulder arthroplasty (29%). This could be due to the limitations of grading arthritis on radiographs. Some studies have reported patients with higher grade chondral lesions that do well with arthroscopy, but these lesions may not be associated with detectable radiographic arthritis (8, 56, 57). Additionally, the location, size, and polarity of arthritic lesions can determine if the patient is a good candidate for arthroscopic debridement, but these features are not captured well by the currently used x-ray based classifications.

Limitations

This study has several limitations. While multiple fellowship-trained shoulder surgeons were surveyed, these respondents may not generalize to all practice environments. The question still remains as to what is considered a “young” patient. One must consider a threshold for which a total shoulder arthroplasty is overwhelmingly chosen as the surgical treatment option. Any patient under this threshold would therefore be considered “young.” Our study suggests the age of 40-45 years as a breaking point for which surgeons chose total shoulder arthroplasty as the surgical treatment of choice. However, we only chose arbitrary ages to evaluate. Future studies are needed to determine the threshold for what is considered a “young” patient with arthritis to help guide treatment recommendations. Also, it is clear that variables other than age, activity level, symptom severity, and radiographic findings can contribute substantially to treatment decisions; this may partially explain the variable agreement amongst the surgeons surveyed. Despite this, these variables were selected by consensus of a group of expert shoulder surgeons as the most likely to influence decision-making. Finally, while the intra-observer reliability of the KL classification system was calculated, the intra-observer reliability of treatment decisions was not determined.

When evaluating glenohumeral arthritis, patient symptoms (rs=0.46) and KL grade (rs=0.44) are the factors most strongly correlated with the management decisions of shoulder specialists. In cases that were treated surgically, the factors most strongly correlated with the choice of operation were the KL grade (rs=0.64) and age (rs=0.39). Additionally, we found that the KL classification has excellent inter and intra-observer reliability for classifying glenohumeral arthritis. While this study highlights some of the factors that are important in dictating treatment decisions for glenohumeral osteoarthritis, there was only moderate agreement among shoulder specialists, indicating either limitations in our study methodology or variability in treatment philosophies among surgeons. This underscores the lack of high quality evidence to guide the treatment of younger patients with glenohumeral osteoarthritis.

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9.Van Thiel GS, Sheehan S, Frank RM, Slabaugh M, Cole BJ, Nicholson GP, et al. Retrospective analysis of arthroscopic management of glenohumeral degenerative disease. Arthroscopy. 2010;26(11):1451–5. doi: 10.1016/j.arthro.2010.02.026. [DOI] [PubMed] [Google Scholar]
10.Holzer N, Salvo D, Marijnissen AC, Vincken KL, Ahmad AC, Serra E, et al. Radiographic evaluation of posttraumatic osteoarthritis of the ankle: the Kellgren-Lawrence scale is reliable and correlates with clinical symptoms. Osteoarthritis Cartilage. 2015;23(3):363–9. doi: 10.1016/j.joca.2014.11.010. [DOI] [PubMed] [Google Scholar]
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12.Momenzadeh OR, Gerami MH, Sefidbakht S, Dehghani S. Assessment of correlation between MRI and arthroscopic pathologic findings in the shoulder joint. Arch Bone Jt Surg. 2015;3(4):286–90. [PMC free article] [PubMed] [Google Scholar]
13.Kellgren JH, Lawrence JS. Radiological assessment of osteo-arthrosis. Ann Rheum Dis. 1957;16(4):494–502. doi: 10.1136/ard.16.4.494. [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Cohen J. A power primer. Psychol Bull. 1992;112(1):155–9. doi: 10.1037//0033-2909.112.1.155. [DOI] [PubMed] [Google Scholar]
15.Fleiss JL, Cohen J. The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educ Psychol Meas. 1973;33(3):613–9. [Google Scholar]
16.Norman GR, Streiner DL. Biostatistics: the bare essentials. 3rd ed. Shelton: People’s Medical Publication; 2008. p. 393. [Google Scholar]
17.Cicchetti DV. Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol Assess. 1994;6(4):284–90. [Google Scholar]
18.Team RC R. language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2017. [Google Scholar]
19.Studio R. R studio: integrated development environment for R. Boston: RStudio Inc; 2012. [Google Scholar]
20.Gamer M, Lemon J, Singh IF. Various coefficients of interrater reliabiltiy and agreement. New York: R Package Version; 2012. [Google Scholar]
21.Testing and plotting procedures for biostatistics. RVAideMemoire. 2017. Available at: URL: https://CRAN.R-project.org/package=RVAideMemoire.
22.Basic functions for power analysis. PWR. 2017. Available at: URL: https://CRAN.R-project.org/package=pwr.
23.Rockwood CA. The shoulder. 4th ed. Philadelphia, PA: Saunders/Elsevier; 2009. p. 2. [Google Scholar]
24.Barlow JD, Abboud J. Surgical options for the young patient with glenohumeral arthritis. Int J Shoulder Surg. 2016;10(1):28–36. doi: 10.4103/0973-6042.174516. [DOI] [PMC free article] [PubMed] [Google Scholar]
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40.Roberson TA, Bentley JC, Griscom JT, Kissenberth MJ, Tolan SJ, Hawkins RJ, et al. Outcomes of total shoulder arthroplasty in patients younger than 65 years: a systematic review. J Shoulder Elbow Surg. 2017;26(7):1298–306. doi: 10.1016/j.jse.2016.12.069. [DOI] [PubMed] [Google Scholar]
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47.Allain J, Goutallier D, Glorion C. Long-term results of the Latarjet procedure for the treatment of anterior instability of the shoulder. J Bone Joint Surg Am. 1998;80(6):841–52. doi: 10.2106/00004623-199806000-00008. [DOI] [PubMed] [Google Scholar]
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49.Guyette TM, Bae H, Warren RF, Craig E, Wickiewicz TL. Results of arthroscopic subacromial decompression in patients with subacromial impingement and glenohumeral degenerative joint disease. J Shoulder Elbow Surg. 2002;11(4):299–304. doi: 10.1067/mse.2002.124427. [DOI] [PubMed] [Google Scholar]
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[B5] 5.Li X, Eichinger JK, Higgins LD. Management of failed metal-backed glenoid component in patients with bilateral total shoulder arthroplasty. Int J Shoulder Surg. 2013;7(4):143–8. doi: 10.4103/0973-6042.123527. [DOI] [PMC free article] [PubMed] [Google Scholar]

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[B7] 7.Walch G, Boulahia A, Boileau P, Kempf JF. Primary glenohumeral osteoarthritis: clinical and radiographic classification. The Aequalis Group. Acta Orthop Belg. 1998;64(Suppl 2):46–52. [PubMed] [Google Scholar]

[B8] 8.Ogilvie-Harris DJ, Wiley AM. Arthroscopic surgery of the shoulder A general appraisal. J Bone Joint Surg Br. 1986;68(2):201–7. doi: 10.1302/0301-620X.68B2.3958003. [DOI] [PubMed] [Google Scholar]

[B9] 9.Van Thiel GS, Sheehan S, Frank RM, Slabaugh M, Cole BJ, Nicholson GP, et al. Retrospective analysis of arthroscopic management of glenohumeral degenerative disease. Arthroscopy. 2010;26(11):1451–5. doi: 10.1016/j.arthro.2010.02.026. [DOI] [PubMed] [Google Scholar]

[B10] 10.Holzer N, Salvo D, Marijnissen AC, Vincken KL, Ahmad AC, Serra E, et al. Radiographic evaluation of posttraumatic osteoarthritis of the ankle: the Kellgren-Lawrence scale is reliable and correlates with clinical symptoms. Osteoarthritis Cartilage. 2015;23(3):363–9. doi: 10.1016/j.joca.2014.11.010. [DOI] [PubMed] [Google Scholar]

[B11] 11.Riddle DL, Jiranek WA. Knee osteoarthritis radiographic progression and associations with pain and function prior to knee arthroplasty: a multicenter comparative cohort study. Osteoarthritis Cartilage. 2015;23(3):391–6. doi: 10.1016/j.joca.2014.12.013. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B12] 12.Momenzadeh OR, Gerami MH, Sefidbakht S, Dehghani S. Assessment of correlation between MRI and arthroscopic pathologic findings in the shoulder joint. Arch Bone Jt Surg. 2015;3(4):286–90. [PMC free article] [PubMed] [Google Scholar]

[B13] 13.Kellgren JH, Lawrence JS. Radiological assessment of osteo-arthrosis. Ann Rheum Dis. 1957;16(4):494–502. doi: 10.1136/ard.16.4.494. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B14] 14.Cohen J. A power primer. Psychol Bull. 1992;112(1):155–9. doi: 10.1037//0033-2909.112.1.155. [DOI] [PubMed] [Google Scholar]

[B15] 15.Fleiss JL, Cohen J. The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educ Psychol Meas. 1973;33(3):613–9. [Google Scholar]

[B16] 16.Norman GR, Streiner DL. Biostatistics: the bare essentials. 3rd ed. Shelton: People’s Medical Publication; 2008. p. 393. [Google Scholar]

[B17] 17.Cicchetti DV. Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol Assess. 1994;6(4):284–90. [Google Scholar]

[B18] 18.Team RC R. language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2017. [Google Scholar]

[B19] 19.Studio R. R studio: integrated development environment for R. Boston: RStudio Inc; 2012. [Google Scholar]

[B20] 20.Gamer M, Lemon J, Singh IF. Various coefficients of interrater reliabiltiy and agreement. New York: R Package Version; 2012. [Google Scholar]

[B21] 21.Testing and plotting procedures for biostatistics. RVAideMemoire. 2017. Available at: URL: https://CRAN.R-project.org/package=RVAideMemoire.

[B22] 22.Basic functions for power analysis. PWR. 2017. Available at: URL: https://CRAN.R-project.org/package=pwr.

[B23] 23.Rockwood CA. The shoulder. 4th ed. Philadelphia, PA: Saunders/Elsevier; 2009. p. 2. [Google Scholar]

[B24] 24.Barlow JD, Abboud J. Surgical options for the young patient with glenohumeral arthritis. Int J Shoulder Surg. 2016;10(1):28–36. doi: 10.4103/0973-6042.174516. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B25] 25.Bhatia S, Van Thiel GS, Gupta D, Ghodadra N, Cole BJ, Bach BR, et al. Comparison of glenohumeral contact pressures and contact areas after glenoid reconstruction with latarjet or distal tibial osteochondral allografts. Am J Sports Med. 2013;41(8):1900–8. doi: 10.1177/0363546513490646. [DOI] [PubMed] [Google Scholar]

[B26] 26.Liem D, Kasten P. Management of glenohumeral osteoarthritis in the young patient: ask the experts. J Shoulder Elbow Surg. 2012;21(4):561–6. doi: 10.1016/j.jse.2011.11.011. [DOI] [PubMed] [Google Scholar]

[B27] 27.Sayegh ET, Mascarenhas R, Chalmers PN, Cole BJ, Romeo AA, Verma NN. Surgical treatment options for glenohumeral arthritis in young patients: a systematic review and meta-analysis. Arthroscopy. 2015;31(6):1156–66. doi: 10.1016/j.arthro.2014.11.012. [DOI] [PubMed] [Google Scholar]

[B28] 28.Johnson MH, Paxton ES, Green A. Shoulder arthroplasty options in young (<50 years old) patients: review of current concepts. J Shoulder Elbow Surg. 2015;24(2):317–25. doi: 10.1016/j.jse.2014.09.029. [DOI] [PubMed] [Google Scholar]

[B29] 29.Sinha I, Lee M, Cobiella C. Management of osteoarthritis of the glenohumeral joint. Br J Hosp Med Lond Engl. 2008;69(5):264–8. doi: 10.12968/hmed.2008.69.5.29358. [DOI] [PubMed] [Google Scholar]

[B30] 30.Weinstein DM, Bucchieri JS, Pollock RG, Flatow EL, Bigliani LU. Arthroscopic debridement of the shoulder for osteoarthritis. Arthroscopy. 2000;16(5):471–6. doi: 10.1053/jars.2000.5042. [DOI] [PubMed] [Google Scholar]

[B31] 31.Lubowitz JH. Editorial commentary: shoulder arthroscopy, shoulder hemiarthroplasty, and total shoulder arthroplasty for glenohumeral osteoarthritis. Arthroscopy. 2015;31(6):1167–8. doi: 10.1016/j.arthro.2015.04.076. [DOI] [PubMed] [Google Scholar]

[B32] 32.Mitchell JJ, Warner BT, Horan MP, Raynor MB, Menge TJ, Greenspoon JA, et al. Comprehensive arthroscopic management of glenohumeral osteoarthritis: preoperative factors predictive of treatment failure. Am J Sports Med. 2017;45(4):794–802. doi: 10.1177/0363546516668823. [DOI] [PubMed] [Google Scholar]

[B33] 33.Bryant D, Litchfield R, Sandow M, Gartsman GM, Guyatt G, Kirkley A. A comparison of pain, strength, range of motion, and functional outcomes after hemiarthroplasty and total shoulder arthroplasty in patients with osteoarthritis of the shoulder A systematic review and meta-analysis. J Bone Joint Surg Am. 2005;87(9):1947–56. doi: 10.2106/JBJS.D.02854. [DOI] [PubMed] [Google Scholar]

[B34] 34.Radnay CS, Setter KJ, Chambers L, Levine WN, Bigliani LU, Ahmad CS. Total shoulder replacement compared with humeral head replacement for the treatment of primary glenohumeral osteoarthritis: a systematic review. J Shoulder Elbow Surg. 2007;16(4):396–402. doi: 10.1016/j.jse.2006.10.017. [DOI] [PubMed] [Google Scholar]

[B35] 35.Carroll RM, Izquierdo R, Vazquez M, Blaine TA, Levine WN, Bigliani LU. Conversion of painful hemiarthroplasty to total shoulder arthroplasty: long-term results. J Shoulder Elbow Surg. 2004;13(6):599–603. doi: 10.1016/j.jse.2004.03.016. [DOI] [PubMed] [Google Scholar]

[B36] 36.Sperling JW, Cofield RH. Revision total shoulder arthroplasty for the treatment of glenoid arthrosis. J Bone Joint Surg Am. 1998;80(6):860–7. doi: 10.2106/00004623-199806000-00010. [DOI] [PubMed] [Google Scholar]

[B37] 37.Garcia GH, Liu JN, Sinatro A, Wu HH, Dines JS, Warren RF, et al. High satisfaction and return to sports after total shoulder arthroplasty in patients aged 55 years and younger. Am J Sports Med. 2017;45(7):1664–9. doi: 10.1177/0363546517695220. [DOI] [PubMed] [Google Scholar]

[B38] 38.Getz CL, Kearns KA, Padegimas EM, Johnston PS, Lazarus MD, Williams GR. Survivorship of hemiarthroplasty with concentric glenoid reaming for glenohumeral arthritis in young, active patients with a biconcave glenoid. J Am Acad Orthop Surg. 2017;25(10):715–23. doi: 10.5435/JAAOS-D-16-00019. [DOI] [PubMed] [Google Scholar]

[B39] 39.Kusnezov N, Dunn JC, Parada SA, Kilcoyne K, Waterman BR. Clinical outcomes of anatomical total shoulder arthroplasty in a young, active population. Am J Orthop. 2016;45(5):E273–82. [PubMed] [Google Scholar]

[B40] 40.Roberson TA, Bentley JC, Griscom JT, Kissenberth MJ, Tolan SJ, Hawkins RJ, et al. Outcomes of total shoulder arthroplasty in patients younger than 65 years: a systematic review. J Shoulder Elbow Surg. 2017;26(7):1298–306. doi: 10.1016/j.jse.2016.12.069. [DOI] [PubMed] [Google Scholar]

[B41] 41.Sowa B, Bochenek M, Bülhoff M, Zeifang F, Loew M, Bruckner T, et al. The medium- and long-term outcome of total shoulder arthroplasty for primary glenohumeral osteoarthritis in middle-aged patients. Bone Jt J. 2017;99-B(7):939–43. doi: 10.1302/0301-620X.99B7.BJJ-2016-1365.R1. [DOI] [PubMed] [Google Scholar]

[B42] 42.Sowa B, Thierjung H, Bülhoff M, Loew M, Zeifang F, Bruckner T, et al. Functional results of hemi- and total shoulder arthroplasty according to diagnosis and patient age at surgery. Acta Orthop. 2017;88(3):310–4. doi: 10.1080/17453674.2017.1280656. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B43] 43.Bhat SB, Lazarus M, Getz C, Williams GR, Namdari S. Economic decision model suggests total shoulder arthroplasty is superior to hemiarthroplasty in young patients with end-stage shoulder arthritis. Clin Orthop. 2016;474(11):2482–92. doi: 10.1007/s11999-016-4991-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B44] 44.Denard PJ, Wirth MA, Orfaly RM. Management of glenohumeral arthritis in the young adult. J Bone Joint Surg Am. 2011;93(9):885–92. doi: 10.2106/JBJS.J.00960. [DOI] [PubMed] [Google Scholar]

[B45] 45.Cil A, Veillette CJ, Sanchez-Sotelo J, Sperling JW, Schleck CD, Cofield RH. Survivorship of the humeral component in shoulder arthroplasty. J Shoulder Elbow Surg. 2010;19(1):143–50. doi: 10.1016/j.jse.2009.04.011. [DOI] [PubMed] [Google Scholar]

[B46] 46.Samilson RL, Prieto V. Dislocation arthropathy of the shoulder. J Bone Joint Surg Am. 1983;65(4):456–60. [PubMed] [Google Scholar]

[B47] 47.Allain J, Goutallier D, Glorion C. Long-term results of the Latarjet procedure for the treatment of anterior instability of the shoulder. J Bone Joint Surg Am. 1998;80(6):841–52. doi: 10.2106/00004623-199806000-00008. [DOI] [PubMed] [Google Scholar]

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PERMALINK

Evaluating Glenohumeral Osteoarthritis: The Relative Impact of Patient Age, Activity Level, Symptoms, and Kellgren-Lawrence Grade on Treatment

Adam Schumaier, MD

Joseph Abboud, MD

Brian Grawe, MD

J Gabriel Horneff, MD

Charles Getz, MD

Anthony Romeo, MD

Jay Keener, MD

Richard Friedman, MD

Ed Yian, MD

Stephanie Muh, MD

Gregory Nicholson, MD

Ruth Delaney, MD

Randall Otto, MD

William William, MD

JT Tokish, MD

Gerald Williams, MD

Jack Kazanjian, DO

Joshua Dines, MD

Matthew Ramsey, MD

Andrew Green, MD

Scott Paxton, MD

Surena Namdari, MD

Brody Flanagin, MD

Samer Hasan, MD

Scott Kaar, MD

Anthony Miniaci, MD

Frances Cuomo, MD

Abstract

Background:

Methods:

Results:

Conclusion:

Introduction

Materials and Methods

Results

Table 1.

Figure 1.

Figure 2.

Table 2.

Figure 3.

Figure 4.

Table 3.

Discussion

References

ACTIONS

PERMALINK

RESOURCES

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