Decreased fracture risk in cystic fibrosis patients treated with CFTR modulator therapy

Akin Adio; Miguel Fiandeiro; Jehad Feras Alsamhori; Imad Ashkar; Peter Boufadel; John G. Horneff; Joseph A. Abboud

doi:10.1016/j.jor.2025.12.042

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73 (); 193-197

doi:

10.1016/j.jor.2025.12.042

Decreased fracture risk in cystic fibrosis patients treated with CFTR modulator therapy

Akin Adio^a,, Miguel Fiandeiro^b, Jehad Feras Alsamhori^c, Imad Ashkar^d, Peter Boufadel^e, John G. Horneff^f, Joseph A. Abboud^e

a Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

b Rothman Orthopaedic Institute, Philadelphia, PA, USA

c School of Medicine, The University of Jordan, Amman, Jordan

d Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Jbeil, Lebanon

e Division of Shoulder and Elbow Surgery, Rothman Orthopaedic Institute, Philadelphia, PA, USA

f Department of Orthopaedic Surgery, Hospital of the University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA

⁎Corresponding author: Akin Adio. akin.adio@pennmedicine.upenn.edu

Received: 2025-11-27, Accepted: 2025-12-15, Published: 2025-12-15

The Authors

Disclaimer:
This article was originally published by Reed Elsevier India Pvt. Ltd. and was migrated to Scientific Scholar after the change of Publisher.

Abstract

Cystic fibrosis–related bone disease contributes substantially to fragility fractures and morbidity in patients with cystic fibrosis (CF). Cystic Fibrosis Transmembrane conductance Regulator (CFTR) modulators have been shown to improve pulmonary and nutritional outcomes, but their impact on skeletal health remains incompletely defined.

We conducted a retrospective cohort study using the TriNetX Research Network, which aggregates deidentified electronic medical records from 168 health care organizations. Patients with CF who initiated CFTR modulators between 2012 and 2023 were compared with matched CF patients without modulator exposure. Sub-analyses examined outcomes in patients receiving elexacaftor/tezacaftor/ivacaftor (ETI) versus non-ETI modulators. A 1:1 propensity score matching algorithm balanced demographic and clinical covariates. The primary outcome was 2-year fracture risk. Relative risks (RR) with 95 % confidence intervals (CI) were calculated.

After matching, 5639 patients receiving CFTR modulators were compared with controls. Modulator therapy was associated with significantly reduced risk of overall fracture (RR 0.48, p < .0001), with protective effects observed for hand or wrist, forearm, upper limb, femur, lower leg, and vertebral fractures. Both ETI and non-ETI modulators were associated with significantly lower fracture risk compared with no therapy. There were no significant differences in fracture outcomes between ETI and non-ETI users.

In this large, population-based analysis, CFTR modulator therapy was associated with lower 2-year fracture risk. These findings extend the benefits of modulator therapy beyond pulmonary and nutritional domains, highlighting its potential role in skeletal protection.

Keywords

Cystic fibrosis

Fracture

CFTR modulator

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1 Introduction

Cystic fibrosis (CF) is an autosomal recessive genetic disorder caused by mutations in the Cystic Fibrosis Transmembrane conductance Regulator (CFTR) gene, affecting approximately 160,000 individuals globally.¹^,² The disease is characterized by the buildup of thick mucus, leading to chronic respiratory infections and multisystem complications. A significant complication of cystic fibrosis is bone disease.³^,⁴ Cystic fibrosis–related bone disease arises from multiple converging mechanisms. CFTR dysfunction directly increases osteoclast differentiation and increases bone reabsorption.^5–7 Chronic systemic inflammation further contributes to bone loss including, elevated pro-inflammatory cytokines.^8–10 Additionally pancreatic insufficiency resulting in fat-soluble vitamin deficiencies (notably D and K), hormonal disturbances, and reduced mechanical loading due to exercise intolerance exacerbate skeletal fragility.⁸^,¹¹ These mechanisms result in an over 9-fold fracture risk compared to non-CF patients.¹² Epidemiologic studies estimate prevalence rates of osteoporosis in 23.5 %, vertebral fractures in 14 %, and nonvertebral fractures in 19 % in CF patients.^13–15

The development of CFTR modulators has transformed cystic fibrosis care, moving beyond symptomatic treatment to disease-modifying therapy. Over the past decade, several CFTR modulators, including ivacaftor, lumacaftor/ivacaftor combination therapy, and tezacaftor/ivacaftor combination therapy have demonstrated improvements in CF care, decreasing pulmonary exacerbations by 35 %.¹⁶^,¹⁷ However, these advances have been limited to 5–10 % of the CF population with specific gating mutations or homozygous F508 deletions.¹⁸ In 2019, the triple combination elexacaftor, tezacaftor, and ivacaftor (ETI) was approved, extending CFTR modulator eligibility to an estimated 90 percent of individuals with cystic fibrosis.¹⁹ Published clinical trials have shown that ETI therapy reduces pulmonary exacerbation rates and improves nutritional status, lung function, and survival metrics, establishing it as the current standard of care for eligible patients.¹⁸^,²⁰

Despite elevated fracture risk in CF patients and the growing optimism about CFTR modulator therapy, no study to date has directly evaluated CFTR modulator impact on fracture incidence. While these therapies target core CF pathophysiology, their effect on fracture risk remains unknown.⁴ The primary objective of this study is to explore the influence of CFTR modulator use on 2-year fracture risk through a comparative analysis of propensity-matched cohorts derived from a large national database. We hypothesize that CFTR modulator use significantly decreases the risk of fracture.

2 Methods

This is a retrospective cohort study designed to evaluate the risk of 2-year fracture risk in cystic fibrosis patients. We used TriNetX, an aggregated database of deidentified electronic medical cohorts from 168 health care organizations within the global collaborative network. The query for deidentified patient data was executed on August 28, 2025. Patients with CFTR modulator use between January 1, 2012, and August 01, 2023, were included. Because this study solely used deidentified patient records and the absence of individually identifiable data, Institutional Review Board approval was not required.

Patients with cystic fibrosis were identified using International Classification of Diseases, 10th Revision (ICD-10) codes. The index event was defined as the date of the first recorded CFTR modulator prescription for patients in the treatment group, and the date of an inpatient encounter for patients in the non-modulator group. Patients were required to have no CFTR modulator prescriptions for at least 1 year before and 2 years after the index event to remain in the non-modulator cohort. Secondary analyses further stratified exposure: patients prescribed elexacaftor/tezacaftor/ivacaftor (ETI) were classified into the ETI cohort, while patients prescribed ivacaftor, lumacaftor/ivacaftor, or tezacaftor/ivacaftor without ETI exposure during the same timeframe were classified into the non-ETI modulator cohort. Comparisons were performed for ETI versus no modulator use, non-ETI modulator versus no modulator use, and ETI versus non-ETI modulator use. All codes used for identification are displayed in Table 1.

Table 1 Codes used for cohort identification and outcomes.

Category	Codes
Cystic Fibrosis Diagnosis	ICD-10CM: E84.0, E84.1, E84.11, E84.19, E84.8, E84.9
Medications
Ivacaftor	RxNorm: 1243041
Lumacaftor	RxNorm: 1655922
Tezacaftor	RxNorm: 1999382
Elexacaftor	RxNorm: 2256951
Outcomes
Overall Fracture	ICD-10CM: S12, S22, S32, S42, S52, S62, S72, S82, S92
Hand or Wrist Fracture	ICD-10CM:S62
Forearm Fracture	ICD-10CM: S52
Upper Limb Fracture	ICD-10CM: S42
Femur Fracture	ICD-10CM: S72
Lower Leg Fracture	ICD-10CM: S82
Vertebral Fracture	ICD-10CM: S12, S22, S32

2.1

2.1 1:1 propensity-matched cohort

The TriNetX platform was used to conduct 1:1 propensity score matching employing logistic regression. The platform integrates nearest-neighbor matching with a tolerance level of 0.01 and ensures that the difference between propensity scores is P ≤ .01 for each covariate after matching. Propensity matching was performed to balance demographic characteristics (age, sex, race) as well as relevant clinical factors, including body mass index, obesity, diabetes mellitus (types 1 and 2), liver disease, malnutrition, vitamin D deficiency, calcium deficiency, sweat chloride values, disorders of bone density and structure (osteoporosis, osteopenia, and related conditions), tobacco use/nicotine dependence, alcohol-related disorders, and long-term or current use of steroids and bisphosphonates.

2.1.1

2.1.1 Outcomes

The primary outcomes assessed in this study were fracture risks at 2 years, including overall fracture, hand or wrist fracture, forearm fracture, upper limb fracture, femur fracture, lower leg fracture, and vertebral fracture.

2.1.2

2.1.2 Statistical analysis

For all outcomes of interest, relative risks (RRs), 95 % confidence intervals (CIs) and p-values were computed using the TriNetX system. Categorical variables were assessed using the chi-squared test, while continuous variables were evaluated with Student's t-tests. Statistical significance was defined as p < .05.

3 Results

3.1

3.1 Cohort characteristics

Before 1:1 propensity score matching, 9663 patients with CFTR modulator use were identified compared with 24,493 non-modulator controls. Prior to matching, modulator users were younger, more often male and White, and had higher rates of vitamin D deficiency, tobacco/nicotine use, long-term steroid therapy, obesity, disorders of bone density, liver disease, type 1 and type 2 diabetes, and elevated sweat chloride levels. After 1:1 matching, balance was achieved across all covariates. A complete summary of demographics is presented in Table 2.

Table 2 Characteristics of cohorts before and after propensity score matching.

		Before Matching			After Matching
Characteristics	Cohort	Patients	% Patients	P-Value	Patients	% Patients	P-Value
Demographics
Age at Index (Mean ± SD)	CFTR Modulator	9631 (22.2 ± 14.8)	100 %	<0.001	5639 (22.4 ± 15.4)	100 %	0.07
Age at Index (Mean ± SD)	No Modulator	21,482 (32.0 ± 24.0)	100 %		5639 (22.8 ± 18.3)	100 %
Male	CFTR Modulator	4894	50.80 %	<0.001	2835	50.30 %	0.10
Male	No Modulator	9401	43.80 %		2747	48.70 %
Female	CFTR Modulator	4719	49 %	<0.001	2788	49.40 %	0.08
Female	No Modulator	11,852	55.20 %		2882	51.10 %
White	CFTR Modulator	8274	85.90 %	<0.001	4694	83.20 %	1.00
White	No Modulator	15,382	71.60 %		4694	83.20 %
Black or African American	CFTR Modulator	263	2.70 %	<0.001	193	3.40 %	0.08
Black or African American	No Modulator	2676	12.50 %		161	2.90 %
Diagnosis
Vitamin D deficiency	CFTR Modulator	2560	26.60 %	<0.001	594	10.50 %	0.81
Vitamin D deficiency	No Modulator	859	4 %		602	10.70 %
Tobacco use	CFTR Modulator	87	0.90 %	<0.001	26	0.50 %	0.79
Tobacco use	No Modulator	111	0.50 %		28	0.50 %
Nicotine dependence	CFTR Modulator	215	2.20 %	0.012	87	1.50 %	0.70
Nicotine dependence	No Modulator	584	2.70 %		82	1.50 %
Alcohol related disorders	CFTR Modulator	177	1.80 %	<0.001	56	1 %	0.92
Alcohol related disorders	No Modulator	224	1 %		55	1 %
Long term use of steroids	CFTR Modulator	1244	12.90 %	<0.001	168	3 %	0.28
Long term use of steroids	No Modulator	171	0.80 %		149	2.60 %
Other long term drug therapy	CFTR Modulator	2238	23.20 %	<0.001	431	7.60 %	0.44
Other long term drug therapy	No Modulator	767	3.60 %		453	8 %
BMI 0–19.9 kg/m2	CFTR Modulator	492	5.10 %	<0.001	58	1 %	0.33
BMI 0–19.9 kg/m2	No Modulator	58	0.30 %		48	0.90 %
BMI 20–29 kg/m2	CFTR Modulator	702	7.30 %	<0.001	76	1.30 %	0.74
BMI 20–29 kg/m2	No Modulator	112	0.50 %		72	1.30 %
BMI 30–39 kg/m2	CFTR Modulator	104	1.10 %	<0.001	31	0.50 %	0.71
BMI 30–39 kg/m2	No Modulator	105	0.50 %		34	0.60 %
BMI > 40 kg/m2	CFTR Modulator	45	0.50 %	<0.019	14	0.20 %	0.85
BMI > 40 kg/m2	No Modulator	64	0.30 %		13	0.20 %
Overweight and obesity	CFTR Modulator	330	3.40 %	<0.002	141	2.50 %	0.22
Overweight and obesity	No Modulator	895	4.20 %		162	2.90 %
Disorders of bone density and structure	CFTR Modulator	1084	11.30 %	<0.001	365	6.50 %	0.26
Disorders of bone density and structure	No Modulator	811	3.80 %		395	7 %
Liver Disease	CFTR Modulator	1148	11.90 %	<0.001	310	5.50 %	0.96
Liver Disease	No Modulator	497	2.30 %		311	5.50 %
Disorders of mineral metabolism	CFTR Modulator	481	5.00 %	<0.001	158	2.80 %	0.43
Disorders of mineral metabolism	No Modulator	375	1.70 %		172	3.10 %
Type 1 diabetes mellitus	CFTR Modulator	630	6.50 %	<0.001	186	3.30 %	0.50
Type 1 diabetes mellitus	No Modulator	358	1.70 %		199	3.50 %
Type 2 diabetes mellitus	CFTR Modulator	1371	14.20 %	<0.001	419	7.40 %	0.32
Type 2 diabetes mellitus	No Modulator	1267	5.90 %		447	7.90 %
Laboratory
Calcidiol [Mass/volume] in Serum or Plasma	CFTR Modulator	3984(31.8 ± 13.1)	41.40 %	0.216	1032(31.9 ± 13.1)	18.30 %	0.05
Calcidiol [Mass/volume] in Serum or Plasma	No Modulator	1304(31.2 ± 15.7)	6.10 %		1123(30.7 ± 14.7)	19.90 %
Chloride [Moles/volume] in Serum, Plasma or Blood	CFTR Modulator	5529	33.30 %	<0.001	2441(103.2 ± 3.4)	43.40 %	0.32
Chloride [Moles/volume] in Serum, Plasma or Blood	No Modulator	12,882	35.10 %		2799(102.9 ± 4.7)	49.60 %
Medication s
Bisphosphonates	CFTR Modulator	230	2.40 %	<0.001	92	1.60 %	0.16
Bisphosphonates	No Modulator	258	1.20 %		112	2 %

3.2

3.2 2-Year fracture risk in all-modulator versus No therapy

In the primary analysis (n = 5639), CFTR modulator use was associated with significantly lower risks across multiple fracture categories. Overall fracture risk was reduced by more than half in the modulator group compared with controls (RR 0.48; P < .0001). Subgroup analyses demonstrated similarly protective effects, with lower risks of hand or wrist fracture (RR 0.51; P = .0038), forearm fracture (RR 0.59; P = .0498), upper limb fracture (RR 0.41; P = .0005), femur fracture (RR 0.42; P = .0162), lower leg fracture (RR 0.39; P = .0093), and vertebral fracture (RR 0.36; P < .0001). These results are summarized in Table 3.

Table 3 2 year Fracture Risk in Propensity Matched Modulator vs. No Modulator Therapy.

Modulator vs No Modulator Therapy (n = 5639)
Outcome	Incidence (%)		RR	95 % CI	P-value
Outcome	Modulator	No Modulator	RR	95 % CI	P-value
Overall Fracture	2.13 %	4.40 %	0.48	0.39-0.60	<0.0001
Hand or Wrist Fracture	0.78 %	1.24 %	0.63	0.43-0.92	0.014
Forearm Fracture	0.44 %	0.89 %	0.51	0.31-0.81	0.049
Upper Limb Fracture	0.34 %	0.83 %	0.41	0.24-0.69	0.0005
Femur Fracture	0.17 %	0.40 %	0.42	0.21-0.86	0.016
Lower Leg Fracture	0.48 %	1.22 %	0.39	0.25-0.61	0.009
Vertebral Fracture	0.64 %	1.79 %	0.36	0.24-0.52	<0.0001

3.3

3.3 2-Year fracture risk by modulator class

Sub-analyses were performed to compare outcomes by specific modulator classes. In the ETI versus no therapy cohort (n = 4138), ETI use was associated with significantly reduced risks of overall fracture (RR 0.52; P < .0001), hand or wrist fracture (RR 0.61; P = .0184), forearm fracture (RR 0.59; P = .0498), femur fracture (RR 0.46; P = .0336), lower leg fracture (RR 0.55; P = .0093), and vertebral fracture (RR 0.29; P < .0001). Comparisons of ETI versus non-ETI modulators (n = 2146) revealed no significant differences in fracture outcomes. In the non-ETI versus no therapy analysis (n = 1795), non-ETI modulators were associated with reduced overall fracture risk (RR 0.58; P = .0025), and vertebral fracture (RR 0.28; P < .0001). A complete summary of subgroup comparisons is presented in Table 4.

Table 4 2 year fracture risk by modulator Sub-class.

Outcome	ETI Modulator vs No Therapy (n = 4138)		ETI vs non-ETI Modulator (n = 2146)		Non-ETI Modulator vs No Therapy (n = 1795)
Outcome	RR	P-value	RR	P-value	RR	P-value
Overall Fracture	0.52	<0.0001	0.89	0.558	0.58	0.003
Hand or Wrist Fracture	0.61	0.018	0.55	0.104	0.60	0.525
Forearm Fracture	0.59	0.049	1.00	1.0000	0.76	0.530
Upper Limb Fracture	0.79	0.403	1.09	0.834	1.00^a	1.00^a
Femur Fracture	0.46	0.033	1.00^a	1.00^a	1.00^a	1.00^a
Lower Leg Fracture	0.55	0.009	1.25	0.562	0.56	0.129
Vertebral Fracture	0.29	<0.0001	1.31	0.463	0.28	<0.0001

a TriNetX rounds up numbers less than 10 to protect patient privacy.

4 Discussion

This study represents the first comprehensive, population-based evaluation of mid-term fracture outcomes associated with CFTR modulator therapy in cystic fibrosis. The purpose of this study was to evaluate 2-year fracture outcomes in patients with cystic fibrosis prescribed CFTR modulators using a 1:1 propensity-matched cohort. Compared with patients not receiving modulator therapy, those treated with modulators exhibited significantly reduced risks of overall fracture as well as site-specific fractures involving the wrist, forearm, upper limb, femur, lower leg, and vertebrae. In analyses stratified by treatment class, both ETI and non-ETI modulators conferred overall fracture protection compared with no therapy. No significant differences in fracture risk were observed between ETI and non-ETI modulators.

We found that ETI (elexacaftor/tezacaftor/ivacaftor) markedly reduces 2-year fracture risk. While this has never been studied directly, it aligns with prior research showing ETI therapy increases BMD.^21–23 Mechanistically, ETI functions by both correcting CFTR protein folding and potentiating channel opening, which restores robust chloride transport.²⁴ This dual action re-establishes normal cellular ionic homeostasis in osteoblasts, thereby improving their differentiation and function. Additionally, ETI normalizes RANKL/OPG signaling and reduces osteoclast-mediated bone resorption.²⁵^,²⁶ Furthermore, it also exerts indirect systemic effects, including improved nutritional status, increased BMI and lean mass, and reduced systemic inflammation.²⁷^,²⁸ Our observations underscore ETI's capacity for rapid bone density enhancements and reduced fracture risk in real-world settings.

We found that non-ETI modulator therapy also conferred significant fracture protection, aligning with previous literature.²⁹^,³⁰ Combination corrector–potentiator regimens (lumacaftor/ivacaftor and tezacaftor/ivacaftor) have shown broader systemic benefits, including dampening of inflammatory mediators such as IL-1β, which may indirectly support bone remodeling.³¹^,³² However due to their restricted mutation specificity, these early modulators are indicated for only a 5–10 % of the CF population, limiting their clinical applications.³³ Notably, fracture rates did not differ significantly between the ETI and non-ETI therapy groups, although both demonstrated a reduced risk compared with patients receiving no modulator therapy. This suggests that disease-modifying therapies, regardless of regimen, may alter the underlying bone remodeling abnormalities in cystic fibrosis enough to meaningfully reduce fracture risk.

To our knowledge, this is the first large-scale, population-based analysis to evaluate the impact of CFTR modulators on fracture risk. However, several limitations must be acknowledged. First, as a retrospective study using the TriNetX database, our findings are susceptible to selection bias, confounding variables, and variation in coding accuracy across electronic medical record systems. Second, our dataset lacks clinical granularity in key domains such as BMD values, fall history, and specifics of fracture mechanisms, which could provide deeper insight into fracture risk pathways. Lastly, the non-ETI versus no-modulator comparison contained a smaller sample size, which may have reduced statistical power and limited the ability to detect differences within individual fracture subgroups.

5 Conclusion

In this large, population-based analysis, CFTR modulator therapy was associated with significantly reduced fracture risk in patients with cystic fibrosis. These benefits align with established pulmonary, nutritional, and quality-of-life improvements, underscoring CFTR's role as a comprehensive, disease-modifying therapy.

Author contributions

Akin Adio: Conceptualization, Methodology, Data curation, Formal analysis, Writing – Original draft preparation.

Miguel Fiandeiro: Methodology, Software, Data curation, Writing – Reviewing and Editing.

Jehad Feras Alsamhori: Data curation, Software, Validation.

Imad Ashkar: Investigation, Visualization, Writing – Reviewing and Editing.

Peter Boufadel: Supervision, Investigation, Writing – Reviewing and Editing.

John G. Horneff: Supervision, Methodology, Writing – Reviewing and Editing.

Joseph A. Abboud: Supervision, Project administration, Writing – Reviewing and Editing.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Ethics statement

This study did not involve direct interaction with human subjects or animals. All analyses were conducted using deidentified data from the TriNetX research network and were therefore determined to be non–human subjects research. As such, institutional review board approval and informed consent were not required. All procedures were performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki and the Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals. Privacy and confidentiality of all patient data were strictly maintained.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Patient consent

Not applicable.

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