Abstract
Objectives
Osteoporosis is a prevalent comorbidity in patients undergoing total or reverse shoulder arthroplasty and is associated with higher rates of periprosthetic fracture, implant loosening, and revision surgery. While bisphosphonates are commonly used to treat osteoporosis, prior research has primarily examined preoperative use. This study aimed to evaluate the association between postoperative bisphosphonate initiation and implant-related complications, particularly revision surgery, in osteoporotic patients undergoing shoulder arthroplasty.
Design
We used the TriNetX U.S. Collaborative Network to identify adults (≥ 18 years) with osteoporosis who underwent total shoulder arthroplasty (TSA) or reverse shoulder arthroplasty (RSA) between 2016 and 2021. Patients were categorized by postoperative bisphosphonate use, defined as initiation within one month after surgery. Propensity score matching (1:1) based on demographics and comorbidities yielded 1,489 patients per group. The primary outcome was a composite of revision surgery, periprosthetic fracture, implant loosening, and periprosthetic joint infection at 6 months. Secondary outcomes were the individual components at 6 months and 2 years. Landmark analyses evaluated the composite outcome at 30-day and 1 year postoperatively.
Results
At 6 months, the bisphosphonate group had a lower composite complication rate compared with controls (11.0% vs. 13.4%; HR, 0.79; 95% CI, 0.63–0.98; P = 0.038), primarily driven by a lower revision rate (3.0% vs. 4.2%; HR, 0.67; 95% CI, 0.46–0.99; P = 0.041). No significant differences were observed for periprosthetic fracture, implant loosening, or infection. At 2 years, revision rates remained lower in the bisphosphonate group (7.1% vs. 8.9%; HR, 0.71; 95% CI, 0.55–0.92; P = 0.009), while other complication rates were comparable. In the landmark analysis, postoperative bisphosphonate use was associated with a lower hazard of composite implant-related complications at 1 year.
Conclusions
In this large real-world cohort, postoperative bisphosphonate initiation was associated with lower rates of composite implant-related complications and revision surgery following shoulder arthroplasty. Although causal inference cannot be established due to the observational design, these findings suggest postoperative bisphosphonate use as a potentially modifiable factor that warrants further investigation in prospective studies.
Level of evidence
Level III, retrospective comparative study, treatment study.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12891-026-09981-w.
Keywords: Bisphosphonates, Shoulder arthroplasty, Osteoporosis, Revision surgery, Implant complications
Introduction
Total shoulder arthroplasty (TSA) and reverse shoulder arthroplasty (RSA) are increasingly performed procedures, particularly in older patients [1–3]. A substantial proportion of these patients have underlying osteoporosis, which poses a known risk for adverse outcomes such as periprosthetic fracture, implant loosening, and increased need for revision [4, 5].
Bisphosphonates are well-established agents for reducing fracture risk in patients with osteoporosis. In the setting of joint arthroplasty, prior studies have primarily focused on bisphosphonate use before surgery [6, 7]. Some of these reports suggest that preoperative use may provide protective effects, while others have noted potential concerns regarding complication risk and unclear benefits in shoulder arthroplasty populations [6, 8, 9].
Despite these investigations, the impact of initiating bisphosphonate therapy after shoulder arthroplasty remains underexplored. In particular, it is uncertain whether patients who did not receive osteoporosis treatment before surgery may still benefit from initiating bisphosphonates in the postoperative period.
This study aimed to address this clinical gap by evaluating the use of bisphosphonate therapy started after TSA or RSA in patients with documented osteoporosis. By comparing outcomes between those who received postoperative treatment and those who remained untreated, this study seeks to clarify whether such intervention may serve as a practical strategy to improve care in this high-risk population.
Materials and methods
Database and study design
This cohort study used data from the TriNetX database, which collects deidentified, patient-level information from electronic health records [10]. The data in the TriNetX database are sourced from health care organizations (HCOs) that aggregate data from their main and satellite hospitals, as well as outpatient clinics. Available data include demographics; diagnoses (based on the International Classification of Diseases, Tenth Revision [ICD-10]); procedures (classified by Current Procedural Terminology [CPT]); medications (coded using the Veterans Affairs Drug Classification System and RxNorm); and laboratory tests and health care utilization records. We used the U.S. Collaborative Network within TriNetX, which includes data from more than 100 million patients across 67 HCOs.
Patient selection and grouping
Patients aged 18 years or older who underwent TSA or RSA between January 1, 2016, and December 31, 2021, were identified using the relevant CPT codes (CPT:23470, 23472) and ICD-10 (ICD-10: Z96.61, Z96.62, Z96.69, 0RRJ0JZ, 0RRK0JZ, 0RRJ00Z, 0RRK00Z). Due to limitations in available procedural coding within the TriNetX platform, TSA and RSA could not be reliably distinguished, thereby precluding procedure-specific analyses. Only patients with a documented diagnosis of osteoporosis (ICD-10: M80-M82) within six months prior to the index surgery were included. Patients were excluded if they had a history of malignancy or metastatic bone disease. To isolate the effect of bisphosphonate therapy, patients with documented use of other anti-osteoporotic agents were excluded. This included those with overlapping prescriptions for the RANKL inhibitor denosumab (RxNorm: 993499), the selective estrogen receptor modulator raloxifene (72413), the anabolic agents teriparatide (32915) and abaloparatide (1921069), and the sclerostin inhibitor romosozumab (2123126). To refine the study focus, patients were included only if they had a visit to a TriNetX-affiliated facility within two years of their index operation.
Patients were categorized into two cohorts based on postoperative bisphosphonate exposure, identified from medication records within the TriNetX platform. These records capture both outpatient prescription orders and inpatient medication administrations. The date of first exposure was defined as the earliest recorded prescription or administration of an eligible bisphosphonate. The index date was defined as the date of the shoulder arthroplasty procedure. Bisphosphonate initiation was defined as the first documented prescription or administration of an oral or intravenous bisphosphonate occurring within 30 days following the index shoulder arthroplasty. Patients meeting this criterion were classified into the bisphosphonate group. Eligible bisphosphonates included alendronate (RxNorm: 46041), risedronate (73056), ibandronate (115264), pamidronate (11473), and zoledronic acid (777655). For the primary analysis, follow-up time was measured from the index surgery date. For the landmark analysis, follow-up commenced from postoperative day 30, as specified below. Diagnosis and procedural codes used for cohort identification and outcome definitions are listed in Supplementary Table.
Covariates
Covariates were selected a priori based on clinical relevance and prior literature, representing factors potentially associated with both bisphosphonate initiation and postoperative outcomes. The variables included age, sex, and race, as well as major comorbidities such as hypertension (HTN), type 2 diabetes mellitus (T2DM), chronic obstructive pulmonary disease (COPD), heart failure, liver disease, rheumatoid arthritis (RA), smoking, and obesity. The collection period was defined as one year prior to the index date, which was set as the date of the surgical procedure. These variables were incorporated into the propensity score model to ensure balanced baseline characteristics between the treatment groups.
Outcomes
The primary outcome was a composite of implant-related complications occurring within six months following the index TSA or RSA. This composite included revision surgery (CPT codes 23473, 23474), periprosthetic fracture (ICD-10 code M97.3), implant loosening (ICD-10 codes T84.038 and T84.039), and periprosthetic joint infection (ICD-10 codes T84.50 and T84.59). Exploratory subgroup analyses were conducted after stratifying patients by age (< 65, 65–79, and ≥ 80 years), sex, race (White, Black, Hispanic), and selected comorbidities including type 2 diabetes mellitus (T2DM), chronic obstructive pulmonary disease (COPD), and rheumatoid arthritis (RA). Within each subgroup, we compared the risk of implant-related complications between bisphosphonate users and non-users. In addition, descriptive comparisons were performed to characterize variation in complication risk across demographic and clinical subgroups, independent of bisphosphonate exposure. All subgroup analyses were prespecified as exploratory and were interpreted cautiously.
Secondary outcomes were the individual components of the composite—revision surgery, periprosthetic fracture, implant loosening, and periprosthetic joint infection—evaluated separately at six months and two years postoperatively. All events were identified from diagnosis and procedure codes recorded in the TriNetX electronic health record network using the corresponding diagnosis and procedure codes. The date of onset for each complication was defined as the earliest occurrence recorded more than one day after the index TSA or RSA. This approach was used to minimize misclassification of perioperative or pre-existing conditions.
Landmark analysis
The landmark analysis was prespecified as a sensitivity analysis to mitigate potential immortal (guarantee-time) bias arising from the postoperative exposure definition. A 30-day postoperative landmark was applied, including only patients who were alive and free of implant-related complications at postoperative day 30. Patients were classified according to whether bisphosphonate therapy was initiated within the first 30 days after surgery. Follow-up for the composite outcome commenced from the landmark time point and continued through 1 year postoperatively. Patients were censored at the time of death, loss to follow-up, or at the end of the 1-year landmark follow-up period.
Statistical analysis
Categorical variables were compared using the chi-square test or Fisher’s exact test, as appropriate. Continuous variables were expressed as mean ± standard deviation (SD), while categorical variables were reported as counts and percentages. Time-to-event outcomes were analyzed using Cox proportional hazards models within the TriNetX Measure of Association Analysis framework, allowing estimation of the relative risk over time. Additionally, Kaplan–Meier analysis was used to evaluate time-to-event and frequency outcomes between groups. These analyses generated hazard ratios (HR) with corresponding 95% confidence intervals (CI) and p-values.
To minimize confounding, propensity score matching (PSM) was performed using the TriNetX platform. Propensity scores were estimated using logistic regression based on prespecified covariates, including age, sex, race, HTN, T2DM, COPD, heart failure, liver disease, RA, smoking, and obesity (assessed within 1 year prior to the index surgery). Patients were matched 1:1 using a greedy nearest-neighbor algorithm without replacement, with a caliper width of 0.1 pooled standard deviations. Covariate balance was evaluated using standardized mean differences (SMDs) before and after matching; absolute SMD values < 0.1 were considered indicative of adequate balance. Subgroup analysis was conducted based on age, sex, race, and comorbidities using stratified groups, with head-to-head comparisons performed to assess potential effect modification. Subgroup comparisons were carried out to evaluate variation in complication risk, using age < 65 years, male sex, White race, and absence of each comorbidity as reference categories.
All statistical analyses were performed using the TriNetX platform. Statistical significance for the prespecified primary analysis was defined as a two-sided p value < 0.05. To address multiplicity in exploratory analyses (including subgroup comparisons and secondary endpoints), we applied a Bonferroni correction within each family of related comparisons by dividing α = 0.05 by the number of comparisons in that family.
Results
The selection of patients
A flowchart of the cohort construction is provided in Fig. 1. This study analyzed data from the TriNetX U.S. Collaborative Network from January 1, 2016 to December 31, 2021, which includes 67 health care organizations (HCOs) and 100,570,809 individuals. Patients aged ≥ 18 years who underwent TSA or RSA and had a diagnosis of osteoporosis were selected, resulting in 18,943 eligible individuals. After applying exclusion criteria, including invalid osteoporosis diagnoses, absence of TSA or RSA, preoperative use of bisphosphonate, and concurrent use of other anti-osteoporotic medications, 1,507 patients who initiated bisphosphonate therapy in the postoperative period and 9,226 patients without postoperative bisphosphonate exposure were identified.
Fig. 1.
Study cohort selection and propensity score matching flowchart. TSA, total shoulder arthroplasty; RSA, reverse shoulder arthroplasty; PSM, propensity score matching; n, number of patients
A 1:1 PSM based on age, sex, race, and comorbidities was performed, resulting in 1,489 patients in the bisphosphonate group being matched to 1,489 patients in the non-bisphosphonate group. The final matched cohort consisted of 2,978 patients for analysis.
Demographic features
In the unmatched cohort, patients in the bisphosphonate group (n = 1,507) were slightly older than those in the control group (77.4 ± 8.2 vs. 76.4 ± 8.7 years; P < 0.001) and had a higher proportion of females (86.1% vs. 76.9%; P < 0.001) and White patients (87.9% vs. 84.2%; P < 0.001). The bisphosphonate group had a lower proportion of Black patients (4.2% vs. 6.8%; P < 0.001) and individuals with unknown ethnicity (12.3% vs. 16.7%; P < 0.001). The proportion of Hispanic or Latino, Asian, and non-Hispanic/non-Latino patients was similar between groups.
Regarding comorbidities, T2DM was less prevalent in the bisphosphonate group compared with the control group (25.2% vs. 28.3%; P = 0.014). The prevalence of other comorbidities, including HTN (75.5% vs. 76.6%), COPD (18.9% vs. 17.0%), heart failure (14.8% vs. 15.8%), liver disease (14.6% vs. 13.7%), rheumatoid arthritis (18.1% vs. 15.6%), smoking (15.6% vs. 15.4%), and obesity (38.9% vs. 38.5%) was broadly similar, although SMD exceeded 0.05 for several variables, indicating measurable baseline imbalance before matching.
After matching, there were no statistically significant differences between the two groups in terms of age, sex distribution, or racial composition. The proportion of female patients was 88.1% in the bisphosphonate group and 89.2% in the non-user group. There were no significant differences in the prevalence of key comorbidities, including HTN, T2DM, COPD, heart failure, liver disease, rheumatoid arthritis, smoking, and obesity. All covariates demonstrated standardized mean differences less than 0.1, confirming adequate balance after matching (Table 1). However, although propensity score matching achieved good balance across measured covariates, residual confounding due to unmeasured clinical factors cannot be excluded.
Table 1.
Baseline demographic and clinical characteristics of bisphosphonate users and non-users before and after propensity score matching
| Category | Unmatched Cohort | ||||
|---|---|---|---|---|---|
| Variable | Bisphosphonate (n = 1,507) | Control group (n = 9,226) | Std. Diff | P-value | |
| Demographics | |||||
| Age (years), mean ± SD | 77.4 ± 8.2 | 76.4 ± 8.7 | 0.12 | < 0.001 | |
| Female, (n%) | 1,283 (86.1%) | 7,070 (76.9%) | 0.24 | < 0.001 | |
| Male, (n%) | 168 (11.3%) | 1,781 (19.4%) | 0.23 | < 0.001 | |
| White, (n%) | 1,371 (87.9%) | 8,374 (84.2%) | 0.11 | < 0.001 | |
| Hispanic or Latino, (n%) | 61 (4.1%) | 441 (4.8%) | 0.03 | 0.23 | |
| Black, (n%) | 62 (4.2%) | 621 (6.8%) | 0.11 | < 0.001 | |
| Asian, (n%) | 13 (0.9%) | 117 (1.3%) | 0.04 | 0.19 | |
| Unknown ethnicity, (n%) | 184 (12.3%) | 1,537 (16.7%) | 0.12 | < 0.001 | |
| Not Hispanic or Latino, (n%) | 1,245 (83.6%) | 7,216 (78.5%) | 0.13 | < 0.001 | |
| Comorbidities | |||||
| Hypertension, (n%) | 1,125 (75.5%) | 7,044 (76.6%) | 0.03 | 0.35 | |
| Type 2 Diabetes, (n%) | 375 (25.2%) | 2,598 (28.3%) | 0.07 | 0.01 | |
| COPD, (n%) | 282 (18.9%) | 1,560 (17.0%) | 0.05 | 0.06 | |
| Heart Failure, (n%) | 220 (14.8%) | 1,457 (15.8%) | 0.03 | 0.29 | |
| Liver Disease, (n%) | 218 (14.6%) | 1,260 (13.7%) | 0.03 | 0.34 | |
| Rheumatoid Arthritis, (n%) | 273 (18.1%) | 1,443 (15.6%) | 0.08 | 0.05 | |
| Smoking, (n%) | 244 (15.6%) | 1,535 (15.4%) | 0.01 | 0.82 | |
| Obesity, (n%) | 580 (38.9%) | 3,536 (38.5%) | 0.01 | 0.73 | |
| Category | Matched Cohort | ||||
|---|---|---|---|---|---|
| Bisphosphonate (n = 1,489) | Control group (n = 1,489) | Std. Diff | P-value | ||
| Demographics | |||||
| Age (years), mean ± SD | 77.4 ± 8.2 | 77.8 ± 8.3 | 0.052 | 0.156 | |
| Female, (n%) | 1,282 (86.1%) | 1,291 (86.7%) | 0.018 | 0.63 | |
| Male, (n%) | 168 (11.3%) | 159 (10.7%) | 0.019 | 0.598 | |
| White, (n%) | 1,371 (87.9%) | 1,380 (88.5%) | 0.018 | 0.617 | |
| Hispanic or Latino, (n%) | 61 (4.1%) | 63 (4.2%) | 0.007 | 0.854 | |
| Black, (n%) | 62 (4.2%) | 56 (3.8%) | 0.021 | 0.573 | |
| Asian, (n%) | 13 (0.9%) | 10 (0.7%) | 0.023 | 0.533 | |
| Unknown ethnicity, (n%) | 184 (12.4%) | 183 (12.3%) | 0.002 | 0.643 | |
| Not Hispanic or Latino, (n%) | 1,244 (83.5%) | 1,243 (83.5%) | 0.002 | 0.882 | |
| Comorbidities | |||||
| Hypertension, (n%) | 1,125 (75.6%) | 1,125 (75.6%) | < 0.001 | 0.992 | |
| Type 2 Diabetes, (n%) | 375 (25.2%) | 364 (24.4%) | 0.017 | 0.641 | |
| COPD, (n%) | 282 (18.9%) | 273 (18.3%) | 0.016 | 0.672 | |
| Heart Failure, (n%) | 220 (14.8%) | 209 (14.0%) | 0.021 | 0.566 | |
| Liver Disease, (n%) | 217 (14.6%) | 196 (13.2%) | 0.041 | 0.266 | |
| Rheumatoid Arthritis, (n%) | 272 (18.3%) | 278 (18.7%) | 0.008 | 0.915 | |
| Smoking, (n%) | 244 (15.6%) | 209 (13.4%) | 0.064 | 0.075 | |
| Obesity, (n%) | 580 (39.0%) | 538 (36.1%) | 0.058 | 0.112 | |
Values are presented as mean ± standard deviation (SD) for continuous variables and number (percentage) for categorical variables. Standardized mean differences (Std. Diff) and P values are provided for comparisons between groups. Covariate balance was considered adequate when the standardized mean difference was < 0.1
Outcome
Primary outcome
At six months postoperatively, the incidence of composite implant-related complications was lower in the bisphosphonate group compared with the control group (11.0% vs. 13.4%; HR, 0.79; 95% CI, 0.63–0.98; P = 0.038) (Table 2). The Kaplan–Meier survival curve was presented in Fig. 2.
Table 2.
Incidence of implant-related complications at 6 months following TSA or RSA in the matched cohort
| Outcome | Bisphosphonate (n = 1,489) | Control group (n = 1,489) | Hazard Ratio (95% CI) | P-value |
|---|---|---|---|---|
| Implant related complication, (n%) | 164 (11.0%) | 201 (13.4%) | 0.79 (0.63–0.98) | 0.038 |
| Revision Surgery, (n%) | 44 (3.0%) | 62 (4.2%) | 0.67 (0.46–0.99) | 0.041 |
| Periprosthetic Fracture, (n%) | 14 (0.9%) | 16 (1.1%) | 0.87 (0.53–2.24) | 0.787 |
| Implant Loosening, (n%) | 67 (4.5%) | 75 (5.0%) | 0.89 (0.61–1.18) | 0.325 |
| Periprosthetic Joint Infection, (n%) | 14 (0.9%) | 16 (1.1%) | 0.87 (0.43–1.80) | 0.714 |
Data are presented as number (percentage). Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox proportional hazards models
Fig. 2.
Kaplan–Meier survival curve of postoperative bisphosphonate use on the incidence of composite implant-related complications within 6 months after surgery. Shaded areas represent 95% confidence intervals
In exploratory subgroup analyses, postoperative bisphosphonate use was generally associated with a lower hazard of implant-related complications across several patient subgroups. In patients aged 65–79 years, bisphosphonate use was associated with a 25% lower hazard (HR, 0.75; 95% CI, 0.58–0.96; P = 0.024), and in those aged ≥ 80 years, with a 32% lower hazard (HR, 0.68; 95% CI, 0.52–0.89; P = 0.006). A lower hazard was observed among female patients (HR, 0.76; 95% CI, 0.60–0.96; P = 0.022), whereas no statistically significant association was observed among male patients (HR, 0.82; 95% CI, 0.61–1.12; P = 0.19). Among racial subgroups, only White patients experienced a statistically significant reduction in risk with bisphosphonate use (HR, 0.77; 95% CI, 0.62–0.96; P = 0.021). Regarding comorbid conditions, bisphosphonate use was associated with lower complication risk in patients with T2DM (HR, 0.70; 95% CI, 0.52–0.93; P = 0.012) and RA (HR, 0.68; 95% CI, 0.51–0.90; P = 0.007), whereas the reduction in patients with COPD did not reach statistical significance (HR, 0.76; 95% CI, 0.55–1.05; P = 0.09) (Table 3). These subgroup analyses highlight differences in baseline risk across age groups and selected comorbidities.
Table 3.
Hazard ratios for implant-related complications with bisphosphonate use versus non-use across subgroups
| Subgroup | Hazard ratio (Bisphosphonate vs. No use) | 95% CI | P-value |
|---|---|---|---|
| Age < 65 | 0.85 | (0.62–1.17) | 0.32 |
| Age 65–79 | 0.75 | (0.58–0.96) | 0.024 |
| Age ≥ 80 | 0.68 | (0.52–0.89) | 0.006 |
| Female | 0.76 | (0.60–0.96) | 0.022 |
| Male | 0.82 | (0.61–1.12) | 0.19 |
| White | 0.77 | (0.62–0.96) | 0.021 |
| Black | 0.83 | (0.59–1.17) | 0.28 |
| Hispanic | 0.86 | (0.60–1.24) | 0.35 |
| With T2DM | 0.7 | (0.52–0.93) | 0.012 |
| With COPD | 0.76 | (0.55–1.05) | 0.09 |
| With RA | 0.68 | (0.51–0.90) | 0.007 |
Data are presented as number (percentage). Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox proportional hazards models. Type 2 diabetes mellitus (T2DM), chronic obstructive pulmonary disease (COPD), and rheumatoid arthritis (RA)
In contrast, subgroup comparisons independent of bisphosphonate use revealed that older age was significantly associated with an increased risk of implant-related complications. Patients aged 65–79 had a 20% higher hazard compared to those under 65 (HR, 1.20; 95% CI, 1.02–1.41; P = 0.028), and those aged ≥ 80 had a 47% increased hazard (HR, 1.47; 95% CI, 1.21–1.78; P < 0.001). Female sex was not significantly associated with increased risk relative to males (HR, 1.08; 95% CI, 0.90–1.30; P = 0.404). Similarly, there were no significant differences in risk for Black (HR, 1.15; 95% CI, 0.91–1.46; P = 0.248) or Hispanic patients (HR, 1.09; 95% CI, 0.83–1.43; P = 0.533) compared to White patients. Among comorbidities, both T2DM (HR, 1.26; 95% CI, 1.08–1.47; P = 0.003) and RA (HR, 1.22; 95% CI, 1.04–1.44; P = 0.016) were significantly associated with elevated risk, while COPD demonstrated a non-significant trend toward increased risk (HR, 1.17; 95% CI, 0.98–1.39; P = 0.078) (Table 4). All subgroup analyses were exploratory; p values were interpreted cautiously in the context of multiple testing.
Table 4.
Hazard ratios for implant-related complications by demographic and clinical subgroups
| Comparison Group | HR (95% CI) | P-value |
|---|---|---|
| Age 65–79 vs. < 65 | 1.20 (1.02–1.41) | 0.028 |
| Age ≥ 80 vs. < 65 | 1.47 (1.21–1.78) | < 0.001 |
| Female vs. Male | 1.08 (0.90–1.30) | 0.404 |
| Black vs. White | 1.15 (0.91–1.46) | 0.248 |
| Hispanic vs. White | 1.09 (0.83–1.43) | 0.533 |
| With T2DM vs. Without | 1.26 (1.08–1.47) | 0.003 |
| With COPD vs. Without | 1.17 (0.98–1.39) | 0.078 |
| With RA vs. Without | 1.22 (1.04–1.44) | 0.016 |
Cox regression identified older age, type 2 diabetes mellitus (T2DM), and rheumatoid arthritis (RA) as factors associated with higher risk; chronic obstructive pulmonary disease (COPD) showed a non-significant trend
Secondary outcomes
Six months
For individual complications, the incidence of revision surgery was lower in the bisphosphonate group compared with the control group (3.0% vs. 4.2%; HR, 0.67; 95% CI, 0.46–0.99; P = 0.041). No significant differences were observed for periprosthetic fracture (0.9% vs. 1.1%; HR, 0.87; 95% CI, 0.53–2.24; P = 0.787), implant loosening (4.5% vs. 5.0%; HR, 0.89; 95% CI, 0.61–1.18; P = 0.325), or periprosthetic joint infection (0.9% vs. 1.1%; HR, 0.87; 95% CI, 0.43–1.80; P = 0.714) (Table 2).
Two years
At two years, the bisphosphonate group continued to demonstrate a lower revision rate (7.1% vs. 8.9%; HR, 0.71; 95% CI, 0.55–0.92; P = 0.009). Rates of periprosthetic fracture (2.1% vs. 2.5%; HR, 0.83; 95% CI, 0.66–1.57; P = 0.814), implant loosening (9.5% vs. 10.1%; HR, 0.94; 95% CI, 0.76–1.21; P = 0.724), and periprosthetic joint infection (1.8% vs. 2.1%; HR, 0.87; 95% CI, 0.69–1.54; P = 0.596) remained comparable between groups (Table 5). These secondary outcomes were relatively infrequent, and the absence of statistically significant differences should be interpreted as inconclusive rather than evidence of no association.
Table 5.
Comparison of implant-related complications and individual outcomes at 2 years postoperatively between bisphosphonate users and controls after TSA or RSA
| Outcome | Bisphosphonate (n = 1,489) | Control group (n = 1,489) | Hazard Ratio (95% CI) | P-value |
|---|---|---|---|---|
| Implant related complication, (n%) | 304 (20.4%) | 357 (23.9%) | 0.81 (0.68–0.97) | 0.012 |
| Revision Surgery, (n%) | 106 (7.1%) | 132 (8.9%) | 0.71 (0.55–0.92) | 0.009 |
| Periprosthetic Fracture, (n%) | 31 (2.1%) | 37 (2.5%) | 0.83 (0.66–1.57) | 0.814 |
| Implant Loosening, (n%) | 142 (9.5%) | 150 (10.1%) | 0.94 (0.76–1.21) | 0.724 |
| Periprosthetic Joint Infection, (n%) | 27 (1.8%) | 31 (2.1%) | 0.87 (0.69–1.54) | 0.596 |
Data are presented as number (percentage). Hazard ratios (HR) and 95% confidence intervals (CI) were derived from Cox proportional hazards models
Additional analyses
After applying the 30-day landmark criteria, patients who experienced death or implant-related complications within the first 30 postoperative days were excluded from the landmark cohort. In the 30-day landmark analysis, the cumulative incidence of composite implant-related complications was 2.4% in the bisphosphonate group and 3.8% in the control group, with no statistically significant difference (HR, 0.92; 95% CI, 0.68–1.23; P = 0.097). At one year following the landmark, complication rates were 8.1% in the bisphosphonate group compared with 11.2% in the control group. In this sensitivity landmark analysis, postoperative bisphosphonate use was associated with a lower hazard of composite implant-related complications during follow-up beginning after the 30-day landmark time point (HR, 0.67; 95% CI, 0.46–0.99; P = 0.041).
Discussion
This large-scale cohort study evaluated postoperative bisphosphonate initiation in osteoporotic patients undergoing shoulder arthroplasty using a propensity score–matched design within a real-world, multi-institutional database. Implant-related complications were assessed at both 6-month and 2-year intervals. Our findings are consistent with and add to the existing literature by identifying an association between postoperative bisphosphonate initiation and lower rates of implant-related complications observed during follow-up.
Lawand et al. reported that osteoporotic patients undergoing TSA had significantly higher rates of implant-related complications at 2 years, including mechanical loosening, periprosthetic joint infection, dislocation, fracture, and revision surgery, compared to non-osteoporotic patients. In their matched cohort of 7,842 patients, osteoporotic individuals experienced consistently elevated complication rates despite adjustment for baseline variables, underscoring the need for targeted medical management in this vulnerable group [11].
Parel et al. examined 40,532 TSA patients and demonstrated that preoperative anti-osteoporotic therapy was associated with a 31% reduction in revision and 25% reduction in loosening risk. However, they did not distinguish whether therapy was initiated before or after surgery and excluded RSA, limiting generalizability [12].
Lin et al. conducted a meta-analysis across 20 studies and showed that postoperative bisphosphonate use significantly reduced all-cause revision risk (RR 0.57; 95% CI 0.43–0.74), whereas preoperative use increased revision and periprosthetic fracture risk [13]. Our study aligns with this finding and expands the evidence by focusing specifically on shoulder arthroplasty using real-world clinical data. Notably, Lin et al. reported an increased risk of revision and periprosthetic fracture with preoperative bisphosphonate use, contrasting with the more favorable associations observed with postoperative initiation. This discrepancy may be related to timing-dependent differences in bone remodeling and implant integration, although this interpretation remains speculative. Preoperative bisphosphonate therapy might suppress essential bone turnover during early implant integration, whereas postoperative initiation may allow initial healing while counteracting accelerated bone resorption, potentially contributing to improved bone-implant stability. These proposed mechanisms remain hypothetical, as this study did not include direct measures of bone turnover, bone mineral density, implant fixation, or osseointegration.
Postoperative bisphosphonate use was associated with a significantly lower risk of revision surgery, which represents the most procedure-specific and clinically robust endpoint in this analysis. However, the absolute reduction in revision events was modest (3.0% vs. 4.2% at 6 months; 7.1% vs. 8.9% at 2 years), and its clinical relevance should be interpreted within the broader context of patient selection, treatment burden, and overall perioperative management. The clinical drivers of postoperative bisphosphonate initiation are likely multifactorial, including DEXA-confirmed osteoporosis, intraoperative identification of poor bone quality, postoperative fragility events, or consultation with endocrinology or rheumatology. These observations suggest that postoperative bone health optimization may warrant further investigation in patients undergoing shoulder arthroplasty. However, such prescribing patterns may also reflect confounding by indication or healthy-adherer effects, which cannot be fully accounted for in an observational database study.
Importantly, the 30-day landmark analysis yielded findings consistent with the primary results after restricting follow-up to patients who were alive and event-free at the landmark time point, supporting the robustness of the observed association.
Older age, particularly ≥ 80 years, was associated with a higher risk of implant-related complications, with hazard ratios increasing progressively by age strata. T2DM and RA were also associated with elevated risk, which may reflect systemic inflammatory burden and impaired bone metabolism [14–16]. Collectively, these findings suggest that patients with advanced age or inflammatory comorbidities may represent higher-risk populations; however, the subgroup analyses were exploratory and should be interpreted cautiously given the potential for residual confounding.
Future prospective studies or randomized trials are needed to define optimal timing, duration, and dosing strategies for bisphosphonate therapy. In clinical practice, systematic bone quality assessment (e.g., routine DEXA screening) and multidisciplinary care may help guide individualized perioperative bone health management while balancing potential benefits and risks.
Although osteoporosis is often considered primarily in the context of fragility fractures, emerging evidence indicates that poor bone quality also negatively affects implant stability and long-term survivorship in elective arthroplasty procedures [2, 4, 7, 12, 17–19]. Casp et al. reported that osteoporosis increased revision rates in both TSA (OR 1.21) and RSA (OR 1.42) [4]. However, few studies have evaluated whether postoperative pharmacologic treatment may influence this risk trajectory. The present study contributes to this gap in knowledge by examining a real-world, potentially modifiable intervention in patients with low bone density.
Retrospective studies by Testa et al. and Lawand et al. further demonstrated significantly elevated risks of complications in shoulder arthroplasty patients with low bone quality or fragility fractures. Within two years, these patients experienced higher rates of periprosthetic fracture (OR 2.24), fragility fracture (OR 9.11), deep infection (OR 1.68), and revision surgery (OR 1.68) [5, 11]. Notably, neither study evaluated the potential impact of postoperative osteoporosis therapy. By specifically examining bisphosphonate initiation after surgery, our study provides new insight into postoperative osteoporosis management in this high-risk population.
From a biological perspective, bisphosphonates inhibit osteoclast-mediated bone resorption and preserve bone mass; however, their specific effects on periprosthetic bone remodeling in shoulder arthroplasty remain incompletely defined. Through stabilization of periprosthetic bone stock and reduction of implant–bone micromotion, bisphosphonates may potentially lower the risk of aseptic loosening and structural failure [20, 21]. By improving bone quality, they may also reduce the risk of periprosthetic fracture and early mechanical failure [9, 22–25]. These mechanisms are supported by a systematic review by Pegios et al., which included over 99,000 total hip arthroplasties and found significantly lower rates of aseptic loosening (1.85% vs. 3.2%) and all-cause revision (2.17% vs. 4.06%) in bisphosphonate users [26]. Although focused on the hip, these findings are mechanistically relevant and suggest a potential cross-joint benefit of antiresorptive therapy. However, the present analysis relied in part on diagnosis-based administrative codes for complications such as implant loosening and infection, which are not inherently shoulder-specific. As such, these outcomes should be interpreted as supportive rather than definitive measures of shoulder prosthesis failure.
However, several limitations should be noted. First, TSA and RSA could not be reliably distinguished using available procedural CPT codes, which may have introduced procedural heterogeneity and limited procedure-specific interpretation. Second, the use of a large, de-identified electronic health record database limited access to granular clinical information, including preoperative bone loss, surgeon experience, implant type, fixation method (e.g., cemented vs. uncemented), surgical approach, subscapularis repair, intraoperative complications, and radiographic outcomes. Third, data on vitamin D levels and supplementation, which are known to influence bone metabolism and may affect implant-related outcomes, were inconsistently reported or unavailable in the TriNetX platform. Fourth, bisphosphonate treatment rationale, dosage, duration, and adherence could not be assessed within the available medication data. Additionally, information regarding the specific indications and mechanisms leading to revision surgery was not available in the TriNetX database, which limits clinical interpretation and precludes mechanistic inference regarding the observed association with revision risk.
Conclusion
Postoperative bisphosphonate therapy in patients with osteoporosis undergoing total or reverse shoulder arthroplasty was associated with lower rates of composite implant-related complications and revision surgery during early and intermediate follow-up. These findings suggest that postoperative bisphosphonate use may be considered for further investigation as an adjunctive strategy in perioperative bone health management after shoulder arthroplasty. Further prospective studies are warranted to confirm these associations and to define optimal treatment strategies.
Supplementary Information
Acknowledgements
The authors greatly appreciate C.C. Lai, for statistical analysis support.
Authors’ contributions
Conception and design: C.C. Lai, W.Y. Jao, W.S. Chang. Data curation: C.C. Lai. Main manuscript text writing: W.Y. Jao. Figures and Table preparation: W.Y. Jao, C.S. Chien, W.S. Chang. All authors reviewed the manuscript.
Funding
Declaration:
This research received no external funding.
Data availability
The data used in this study were obtained from the TriNetX research network. Due to the federated nature of the TriNetX platform and data privacy regulations, individual-level patient data cannot be shared publicly or provided upon request. Aggregate-level analyses can be conducted within the TriNetX environment by qualified researchers in accordance with TriNetX data access policies.
Declarations
Ethics approval and consent to participate
This study was reviewed and approved by the Institutional Review Board of Chi Mei Medical Center (No. 11408-E01). Informed consent was waived because the TriNetX dataset is de-identified. All methods were performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data used in this study were obtained from the TriNetX research network. Due to the federated nature of the TriNetX platform and data privacy regulations, individual-level patient data cannot be shared publicly or provided upon request. Aggregate-level analyses can be conducted within the TriNetX environment by qualified researchers in accordance with TriNetX data access policies.