Keywords
β-adrenoreceptor blockers, osteoarthritis, knee joint replacement and hip joint replacement
There is paucity of safe and effective analgesic drugs for osteoarthritis (OA). β-adrenoreceptor blockers have demonstrated anti-nociceptive effects in several painful conditions. We investigated whether β-blockers are associated with a reduced risk of total joint replacement (TJR) at the knee or the hip in people with incident knee or hip OA.
This was a cohort study. We used data from the Clinical Practice Research Datalink. Participants aged 40 years or older with incident knee or hip OA, prescribed β-blockers following OA diagnosis (new-user design) and their age, sex, OA location and propensity score (PS) for β-blocker prescription matched controls were included in the study. Cox-proportional hazard ratios (HRs) and 95% confidence intervals (CI) were calculated. The analyses were adjusted for factors that influence health-seeking behaviour, progression of OA, and stratified according to β-blocker classification. Data analysis was conducted using STATA-MP v15.
Data for 6,970 PS-matched β-blocker exposed and unexposed participants were included. Any β-blocker prescription was not associated with knee or hip TJR (aHR 1.11; 95 % CI 0.98 – 1.25). However, prescription of lipophilic non-selective β-blockers with membrane stabilising effect associated with reduced risk of knee or hip TJR (aHR 0.69; 95 % CI 0.52 – 0.93). Of these, there was a protective effect for propranolol (aHR 0.71; 95 % CI 0.53 – 0.95), the commonest prescribed drug in this class. The number needed to treat (95%CI) with propranolol for two years, in order to prevent one TJR was 32 (23–52).
The non-selective β-blocker propranolol reduces the risk of knee or hip TJR, consistent with its analgesic effects demonstrated in other conditions. A randomised controlled trial is required to further evaluate the analgesic potential of propranolol in OA.
The problem: Osteoarthritis is the commonest form of arthritis and affects many people older than 50 years in age. It is the commonest cause of pain which can be severe and disabling. Many people with osteoarthritis are prescribed painkillers and require joint-replacement surgery. Findings from several studies raise the possibility that beta-blockers commonly used in the treatment of high blood-pressure, hypertension, and irregular heartbeat can reduce pain due to osteoarthritis.
What we did: We investigated whether people with osteoarthritis prescribed beta-blockers were less likely to require joint replacement surgery. We used anonymous data from the NHS provided by the Clinical Practice Research Datalink (CPRD) Gold. CPRD Gold contains anonymised medical information collected during routine clinical care for over 14 million people registered with a GP in the UK. The risk of requiring knee or hip joint replacement surgery in people with osteoarthritis commenced on beta-blockers was compared to similar people not prescribed this medication. Factors that could influence getting knee or hip joint replacement surgery were controlled for in the analysis. These were age, sex, osteoarthritis location, the likelihood of being prescribed beta-blockers, health-seeking behaviour and progression of osteoarthritis.
What we found: When all beta-blocker medicines were considered, there was no difference in the risk of knee or hip joint replacement surgery between people with osteoarthritis prescribed beta-blockers and others not prescribed this medication. However, when each beta-blocker medicine was considered separately, patients prescribed propranolol were less likely to undergo total joint replacement.
Conclusion: Propranolol reduced the risk of knee and hip joint replacement surgery in people with osteoarthritis. Further clinical trials are needed to confirm these findings before this medicine can be used to treat pain in people with osteoarthritis.
β-adrenoreceptor blockers, osteoarthritis, knee joint replacement and hip joint replacement
Osteoarthritis (OA) is the commonest form of arthritis and affects approximately one in four adults older than 45 years of age1. There is a paucity of effective structure-modifying drug for OA, and analgesics only have a modest effect size (ES) and may cause troublesome and potentially serious side effects2,3. Consequently, many people undergo total joint replacement (TJR), most commonly at the knee or the hip. An estimated 1.9 million knee or hip TJRs are projected to be performed each year in the USA alone by the year 20304.
Our recent research demonstrated that β-adrenoreceptor blocking drugs (β-blockers) atenolol and propranolol have anti-nociceptive effects on knee and/or hip pain, with the largest ES for propranolol5. Prior to this, we reported lower opioid consumption and less severe joint pain in people with large-joint lower limb OA prescribed β-blockers6, and β-blocker prescription associated with lower opioid use at day 30 in another study on patients undergoing knee TJR7. However, this observation was not confirmed in a study using Osteoarthritis Initiative (OAI) data8. Whether β-blockers reduce incidence of TJR in people with OA is not known.
Thus, the objective of this study was to examine whether β-blocker prescription associates with a lower risk of lower limb arthroplasty in a primary-care population with knee or hip OA.
Data from Clinical Practice Research Datalink (CPRD) Gold were used in this study. Incepted in the year 1987, CPRD is a longitudinal anonymised electronic database containing health records of >10 million people in the UK9. CPRD participants are representative of the UK population in terms of age, sex, and ethnicity9.
Approval was obtained from Independent Scientific Advisory Committee (now called Research Data Governance committee) of the CPRD (Reference: 18_227R).
Patients aged ≥40 years, newly diagnosed with knee or hip OA between 1st January 1990 and 31st December 2013, with at-least 2-year prior registration in the CPRD before OA diagnosis or β-blocker prescription, and contributing acceptable research quality data in up-to-standard GP practices were included in this study (Figure 1).
The exposure of interest was new continuous β-blocker prescription. This was defined as ≥2 prescriptions of β-blockers within a 60-day period after the first OA diagnosis (new user design)
The unexposed, were participants without a prescription of β-blocker, or with a single β-blocker prescription after OA diagnosis date, matched to exposed participants for age at OA diagnosis (5-year age band), sex, OA location (knee or hip) and propensity score (PS) for β-blocker prescription. The PS included factors that account for confounding by indication such as comorbidities and drug prescriptions (Table 1).
Demographic factors |
Age, gender, body mass index (WHO classification categories) *, smoking status*, deprivation score (General practice level index of multiple deprivation score) |
Comorbidities |
Hypertension, angina, myocardial infarction, congestive cardiac failure, atrial fibrillation, stroke, chronic kidney disease, diabetes, anxiety, migraine, essential tremor, duration in years of cardiovascular comorbidities, osteoarthritis at any other joint, knee, hip, neck or back pain prior to index date. |
Drug prescriptions |
Calcium channel blockers, angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor antagonists, bendroflumethiazide, aldosterone antagonists, loop diuretics, alfa-adrenoreceptor blocking drugs, aspirin, clopidogrel, statins, fibrates. |
Index date was the date of first β-blocker prescription for the exposed participants. Unexposed participants were assigned the index date of their matched exposed participant.
[1] Consultation for any of the following prior to index date:
Conditions causing chronic pain: autoimmune inflammatory rheumatic diseases (rheumatoid arthritis, psoriatic arthritis, ankylosing spondylitis, lupus, polymyalgia rheumatica); gout; radiculopathy; neuropathy; and fibromyalgia.
Contra-indications for β-blockers: chronic obstructive pulmonary disease or asthma; peripheral vascular disease; heart block, aortic stenosis, and hypertrophic obstructive cardiomyopathy.
[2] Knee or hip TJR prior to the index date or within the subsequent 90 days. Knee or hip TJR within 90 days after the index date were excluded because we did not expect β-blockers to influence the rate of TJR immediately, and these drugs may have been commenced during pre-anaesthetic check-up.
Exposed participants were followed up from index date. The duration between OA diagnosis date and index date in the exposed was added to the OA diagnosis date of the matched unexposed to obtain start of follow-up for the latter. This allows exposed and matched unexposed participants to have the same duration of OA prior to the start of follow-up. As the risk of joint replacement increases with duration of OA10, this minimises any bias due to unequal disease duration in matched exposed and unexposed participants. Participant follow-up ended at the earliest of date of first outcome, death date, transfer out date, date of last data collection, or study end (31/12/2018).
As participants prescribed β-adrenoreceptor blocking drugs are likely to have comorbidities, be older and have a high body mass index (BMI), a PS for β-blocker prescription was calculated using a cumulative logit regression model. Greedy nearest neighbour 1:1 matching11, without replacement specifying a maximum calliper width of 0.001, was undertaken to match the exposed to unexposed participants. Missing values for BMI and smoking status were categorised as missing data for the purpose of PS matching as people with healthy lifestyle and normal BMI are more likely to have missing data in consultation-based databases such as CPRD where lifestyle and demographic factors are collected opportunistically12. Mean, standard deviation (SD), n (%), and standardised mean difference (SMD) were used to examine the covariate balance between matched exposed and unexposed participants. Any variables that were imbalanced after PS matching were included in the model if the SMD was >0.10, as recommended13.
Cox proportional hazard ratios (HRs) and 95% confidence interval (CI) were calculated for each incident outcome using first Read code for the event. Covariates that are likely to influence outcomes, e.g. progression of OA, or reflect health-seeking behaviour were included in the Cox model for additional confounder adjustment. These were:
number of GP consultations for knee or hip injury, non-osteoporotic fractures (defined as fractures in any bone except the femur, distal radius, and vertebrae after the age of 18 years but before the age of 50 years in women and 60 years in men) prior to start of follow-up,
number of analgesic prescriptions between the first consultation for knee/hip OA and start of follow-up,
number of GP consultations, hospital out-patient referrals, hospital admissions in the 12-month period preceding start of follow-up,
bisphosphonate or glucosamine/chondroitin sulphate prescription in the 12-month period prior to start of follow-up,
new diagnosis of interphalangeal or thumb base OA, neck or back pain or spinal degenerative diseases after start of follow-up.
These analyses were stratified according to the class of β-blocker drug used namely, β1 selective, intrinsic sympathomimetic activity, membrane stabilising effect, and lipophilic properties (low versus high). Number needed to treat (NNT) and 95% CI for a two-year treatment duration were computed using the aHR and survival probability in control group as described previously14.
Additionally, we performed multiple imputation to handle missing body mass index (BMI) values and smoking status using chained equations as a sensitivity analysis. Demographic factors, relevant diagnoses and prescriptions (Table 1), covariates that are likely to influence outcomes or reflect health-seeking behaviour listed above, primary outcome variable, and Nelson-Aalen estimator of baseline cumulative hazard were included in the imputation model as recommended15. Ten imputed datasets were created to account for random variability16. PS calculation, matching and Cox regression analyses were undertaken in each imputed dataset. However, we did not find substantial difference between the results with missing values as a dummy category and the imputed values (Table 2–Table 4). Thus, results are only reported with the missing category approach. Data management and analysis were performed in Stata MP v15.
Imputed dataset | Knee or hip replacement HR (95% CI)1 | Knee replacement HR (95% CI)1 | Hip replacement HR (95% CI)1 |
---|---|---|---|
1 | 1.09 (0.96-1.24) | 1.15 (0.98-1.35) | 1.28 (0.99-1.64) |
2 | 1.09 (0.96-1.24) | 1.08 (0.92-1.26) | 1.32 (1.03-1.70) |
3 | 1.10 (0.97-1.25) | 1.12 (0.96-1.31) | 1.30 (1.02-1.67) |
4 | 1.15 (1.01-1.30) | 1.18 (1.01-1.38) | 1.31 (1.02-1.69) |
5 | 1.15 (1.01-1.30) | 1.19 (1.01-1.39) | 1.26 (0.99-1.62) |
6 | 1.10 (0.97-1.24) | 1.11 (0.95-1.31) | 1.29 (1.01-1.65) |
7 | 1.09 (0.97-1.24) | 1.06 (0.91-1.24) | 1.28 (1.00-1.64) |
8 | 1.17 (1.03-1.32) | 1.18 (1.01-1.39) | 1.33 (1.04-1.70) |
9 | 1.15 (1.01-1.30) | 1.15 (0.98-1.34) | 1.41 (1.09-1.83) |
10 | 1.11 (0.98-1.26) | 1.14 (0.97-1.33) | 1.41 (1.10-1.80) |
1PS matched, and, additionally adjusted for number of GP consultations, hospital out-patient referrals, hospital admissions and number of bisphosphonate, glucosamine/chondroitin sulphate prescription in the 12 month period preceding index date; total number of GP consultations for knee or hip injury, non-osteoporotic fractures, hand osteoarthritis, neck or back pain or spinal degenerative diseases, hypertension, duration of OA prior to index date; number of analgesic prescription between the first consultation for knee/hip OA and beta-blocker prescription.
Multiple imputation was performed to handle missing BMI values and smoking status using chained equations. Ten imputed datasets were created to account for random variability. PS calculation, matching and Cox regression analyses were undertaken in each imputed dataset.
Comparison group is unexposed to β-blockers;1HR(95 CI), propensity score matched, and, additionally adjusted for number of GP consultations, hospital out-patient referrals, hospital admissions and number of bisphosphonate, glucosamine/chondroitin sulphate prescription in the 12 month period preceding index date; total number of GP consultations for knee or hip injury, non-osteoporotic fractures, hand osteoarthritis, neck or back pain or spinal degenerative diseases, hypertension, duration of OA prior to index date; number of analgesic prescription between the first consultation for knee/hip OA and beta-blocker prescription; ≠β-blocker properties independent of each other; MSE: membrane stabilising effect. Drugs from the rest of β-blocker class combinations were not present.
Multiple imputation was performed to handle missing BMI values and smoking status using chained equations. Ten imputed datasets were created to account for random variability. PS calculation, matching and Cox regression analyses were undertaken in each imputed dataset.
Imputed dataset | Atenolol HR (95% CI)1 | Bisoprolol HR (95% CI)1 | Propranolol HR (95% CI)1 |
---|---|---|---|
1 | 1.14 (0.98-1.31) | 1.14 (0.90-1.38) | 0.74 (0.55-0.99) |
2 | 1.14 (0.99-1.32) | 1.14 (0.93-1.41) | 0.70 (0.52-0.94) |
3 | 1.18 (1.03-1.36) | 1.10 (0.89-1.36) | 0.72 (0.54-0.96) |
4 | 1.18 (1.003-1.37) | 1.21 (0.98-1.50) | 0.80 (0.60-1.07) |
5 | 1.20 (1.04-1.38) | 1.17 (0.95-1.45) | 0.81 (0.62-1.08) |
6 | 1.17 (1.02-1.35) | 1.13 (0.91-1.39) | 0.69 (0.51-0.92) |
7 | 1.13 (0.99-1.30) | 1.18 (0.96-1.45) | 0.72 (0.54-0.97) |
8 | 1.22 (1.06-1.41) | 1.22 (0.99-1.50) | 0.75 (0.56-1.01) |
9 | 1.20 (1.04-1.38) | 1.20 (0.97-1.48) | 0.82 (0.62-1.10) |
10 | 1.17 (1.01-1.34) | 1.16 (0.95-1.43) | 0.70 (0.52-0.94) |
Comparison group is unexposed to β-blockers. 1PS matched, and, additionally adjusted for number of GP consultations, hospital out-patient referrals, hospital admissions and number of bisphosphonate, glucosamine/chondroitin sulphate prescription in the 12 month period preceding index date; total number of GP consultations for knee or hip injury, non-osteoporotic fractures, hand osteoarthritis, neck or back pain or spinal degenerative diseases, hypertension, duration of OA prior to index date; number of analgesic prescription between the first consultation for knee/hip OA and beta-blocker prescription.
Multiple imputation was performed to handle missing BMI values and smoking status using chained equations. Ten imputed datasets were created to account for random variability. PS calculation, matching and Cox regression analyses were undertaken in each imputed dataset.
Data for 13,620 participants exposed to β-blockers and up to five age, sex and OA location matched unexposed participants (n=48,636) were ascertained during the study period. Of these, data for 6,970 PS-matched β-blocker exposed (n=3,485), and unexposed (n=3,485) participants contributing 42,066 person-years of follow-up were analysed (Figure 1). The majority of participants had knee OA (81.12%), more than half our participants were women (57.89%) and the mean (SD) age at OA diagnosis was 65 (11) years. There was covariate balance between exposed and unexposed after PS-matching on all covariates except for hypertension (SMD=0.115) for which there was a minor imbalance (Table 5). Hypertension was included in the model as a covariate to account for the imbalance. After PS matching, unexposed participants had a similar number of consultations with their GP in the preceding 12-months as the exposed, with median (Inter Quartile Range) 11 (6 to 18) and 11 (7 to 18) GP visits, respectively.
Covariates | Entire cohort | PS matched sample | ||||
---|---|---|---|---|---|---|
Exposed (n= 4,641) | Unexposed (n= 9,118) | SMD | Exposed (n= 3,485) | Unexposed (n= 3,485) | SMD | |
Continuous covariates; mean (SD) | ||||||
Age at OA diagnosis | 64.92 (11.18) | 64.11 (11.18) | 0.071 | 64.80 (11.16) | 65.34 (11.49) | -0.048 |
Index of multiple deprivation in tertiles | 5.86 (2.92) | 5.94 (2.86) | -0.026 | 5.87 (2.89) | 5.81 (2.87) | 0.020 |
Duration of ischaemic heart disease/ congestive cardiac failure* | 1.21 (3.92) | 0.83 (3.43) | 0.101 | 1.12 (3.91) | 1.28 (3.82) | -0.042 |
Duration of hypertension* | 4.07 (6.97) | 3.39 (6.51) | 0.101 | 4.27 (7.34) | 4.71 (6.26) | -0.065 |
Categorical covariates; n (%) | ||||||
Male | 2,022 (43.57) | 3,937 (43.18) | 0.008 | 1,489 (42.73) | 1,446 (41.49) | -0.025 |
Non-smoker | 2,553 (55.01) | 5,203 (57.06) | -0.009 | 1,985 (56.96) | 2,005 (57.53) | -0.012 |
Current smoker | 593 (12.78) | 1,194 (13.09) | -0.041 | 430 (12.34) | 391 (11.22) | 0.035 |
Ex-smoker | 1,239 (26.70) | 2,218 (24.33) | 0.054 | 900 (25.82) | 910 (26.11) | -0.007 |
Smoking missing data | 256 (5.52) | 503 (5.52) | 0.000 | 170 (4.88) | 179 (5.14) | -0.012 |
Underweight | 34 (0.73) | 66 (0.72) | 0.001 | 27 (0.77) | 21 (0.60) | 0.021 |
Normal weight | 1,015 (21.87) | 2,056 (22.55) | -0.016 | 762 (21.87) | 732 (21.00) | 0.021 |
Pre-obese | 1,688 (36.37) | 3,128 (34.31) | 0.043 | 1,235 (35.44) | 1,263 (36.24) | -0.017 |
Obese | 1,375 (29.63) | 2,710 (29.72) | -0.002 | 1,059 (30.39) | 1,098 (31.51) | -0.024 |
BMI missing data | 529 (11.40) | 1,158 (12.70) | -0.040 | 402 (11.54) | 371 (10.65) | 0.028 |
Hypertension | 2,742 (59.08) | 3,236 (35.49) | 0.486 | 1,908 (54.75) | 2,106 (60.43) | -0.115 |
Angina | 473 (5.19) | 672 (14.48) | 0.316 | 373 (10.70) | 344 (9.87) | 0.027 |
Myocardial Infarction | 494 (10.64) | 251 (2.75) | 0.320 | 240 (6.89) | 192 (5.51) | 0.057 |
Congestive cardiac failure | 285 (6.14) | 231 (2.53) | 0.178 | 168 (4.82) | 162 (4.65) | 0.008 |
Atrial fibrillation | 594 (12.80) | 370 (4.06) | 0.319 | 341 (9.78) | 319 (9.15) | 0.022 |
Stroke | 305 (6.57) | 496 (5.44) | 0.048 | 232 (6.66) | 254 (7.29) | -0.025 |
Chronic kidney disease | 336 (7.24) | 730 (8.01) | -0.029 | 266 (7.63) | 298 (8.55) | -0.034 |
Diabetes | 462 (9.95) | 856 (9.39) | 0.019 | 365 (10.42) | 392 (11.25) | -0.027 |
Anxiety | 675 (14.54) | 1,063 (11.66) | 0.085 | 479 (13.74) | 518 (14.86) | -0.030 |
Migraine | 335 (7.22) | 498 (5.46) | 0.072 | 247 (7.09) | 265 (7.60) | -0.020 |
Tremor | 133 (2.87) | 133 (1.46) | 0.097 | 92 (2.64) | 96 (2.75) | -0.007 |
Osteoarthritis at any other joint | 1,736 (37.41) | 2,898 (31.78) | 0.119 | 1,260 (36.15) | 1,276 (36.61) | -0.010 |
Neck or back pain | 1,984 (42.75) | 3,626 (39.77) | 0.061 | 1,475 (42.32) | 1,508 (43.27) | -0.020 |
Calcium channel blockers | 1,248 (26.89) | 1,842 (20.20) | 0.158 | 949 (27.23) | 1,037 (29.76) | -0.056 |
ACE inhibitors/Angiotensin II receptor antagonists | 1,577 (33.98) | 2,207 (24.20) | 0.217 | 1,162 (33.34) | 1,269 (36.41) | -0.064 |
Bendroflumethiazide/Aldosterone antagonists/loop diuretics | 2,294 (49.43) | 2,875 (31.53) | 0.371 | 1,616 (46.37) | 1,748 ()50.16 | -0.076 |
Alfa-adrenoreceptor blockers | 270 (5.82) | 378 (4.15) | 0.077 | 211 (6.05) | 214 (6.14) | -0.004 |
Aspirin/Clopidogrel | 2,085 (44.93) | 2,140 (23.47) | 0.464 | 1,347 (38.65) | 1,418 (40.69) | -0.042 |
Statins/Fibrates | 1,580 (34.04) | 2,311 (25.35) | 0.191 | 1,108 (31.79) | 1,213 (34.81) | -0.064 |
Overall β-blocker prescription was not associated with hip or knee TJR (aHR 1.11; 95 % CI 0.98 – 1.25), knee TJR (aHR 1.14; 95 % CI 0.98 –1.34) and hip TJR (aHR 1.23; 95 % CI 0.96 – 1.57) (Table 6). Similar results were observed on the assessment of β -blocker classes except for β-blocker with MSE which showed a reduction in the risk of knee or hip TJR (aHR 0.69; 95% CI 0.52 – 0.93). The NNT (95% CI) to prevent joint replacement at two years follow-up was 32 (23–52). When data were stratified according to individual drugs, there was a protective effect for propranolol but an increase in the risk of knee or hip TJR for atenolol (Table 7; Figure 2).
Outcomes | Exposed | Events | Person-time (years) | Event rate (95% CI)/ 1,000 person-years | Model 1 HR (95% CI)1 | Model 2 HR (95% CI)2 |
---|---|---|---|---|---|---|
Knee or hip replacement | No | 459 | 17,637 | 26.02 (23.75-28.52) | 1.00 | 1.00 |
Yes | 587 | 21,894 | 26.81 (24.73- 29.07) | 1.08 (0.96-1.22) | 1.11 (0.98-1.25) | |
Knee replacement | No | 278 | 14,730 | 18.87 (16.78-21.23) | 1.00 | 1.00 |
Yes | 378 | 18,291 | 20.69 (18.69-22.86) | 1.12 (0.96-1.31) | 1.14 (0.98-1.34) | |
Hip replacement | No | 119 | 2,782 | 42.77 (35.74-51.19) | 1.00 | 1.00 |
Yes | 151 | 3,491 | 43.25 (36.88-50.73) | 1.14 (0.90-1.45) | 1.23 (0.96-1.57) |
1PS matched. 2As in model 1, and, additionally adjusted for number of GP consultations, hospital out-patient referrals, hospital admissions and number of bisphosphonate, glucosamine/chondroitin sulphate prescription in the 12 month period preceding index date; total number of GP consultations for knee or hip injury, non-osteoporotic fractures, hand osteoarthritis, neck or back pain or spinal degenerative diseases, hypertension, duration of OA prior to index date; number of analgesic prescription between the first consultation for knee/hip OA and beta-blocker prescription.
Exposure status | Events (n) | Person-time (years) | Event rate 95% CI/1,000 person-years | Model 1 HR (95% CI)2 | Model 2 HR (95% CI)3 |
---|---|---|---|---|---|
Unexposed1 | 459 | 17,637 | 26.02 (23.75-28.52) | 1.00 | 1.00 |
β-blocker class≠ | |||||
low lipophilic only | 13 | 444 | 29.27 (17.00-50.41) | 1.17 (0.67-2.03) | 1.21 (0.69-2.13) |
High lipophilic only | 7 | 157 | 44.62 (21.27-93.60) | 1.75 (0.83-3.69) | 1.92 (0.91-4.08) |
Beta1selective and low lipophilic | 490 | 17,165 | 28.55 (26.13-31.19) | 1.15 (1.01-1.30) | 1.16 (1.02-1.32) |
Beta1selective and high lipophilic | 22 | 734 | 29.99 (19.75-45.55) | 1.17 (0.77-1.80) | 1.12 (0.73-1.73) |
MSE and high lipophilic | 55 | 3,327 | 16.53 (12.69-21.53) | 0.67 (0.51-0.89) | 0.69 (0.52-0.93) |
β-blocker drug name | |||||
Atenolol | 371 | 12,929 | 28.70 (25.92-31.77) | 1.19 (1.03-1.36) | 1.17 (1.01-1.34) |
Bisoprolol | 116 | 4,174 | 27.79 (23.17-33.34) | 1.04 (0.85-1.27) | 1.17 (0.95-1.44) |
Propranolol | 53 | 3,193 | 16.60 (12.68-21.73) | 0.68 (0.51-0.91) | 0.71 (0.53-0.95) |
1Comparison group is unexposed to β-blockers; 2Propensity score matched; 3As in model 1, and, additionally adjusted for number of GP consultations, hospital out-patient referrals, hospital admissions and number of bisphosphonate, glucosamine/chondroitin sulphate prescription in the 12 month period preceding index date; total number of GP consultations for knee or hip injury, non-osteoporotic fractures, hand osteoarthritis, neck or back pain or spinal degenerative diseases, hypertension, duration of OA prior to index date; number of analgesic prescription between the first consultation for knee/hip OA and beta-blocker prescription; ≠β-blocker properties independent of each other; MSE: membrane stabilising effect. Drugs from the rest of β-blocker class combinations were not present.
In this study, we found no association between β-blocker prescription and TJR when all β-blockers were considered together. However, when β-blockers possessing different properties were considered, this study found that propranolol, a non-selective β-blocker, reduces the risk of TJR at the knee and the hip. This is consistent with our previous findings that propranolol reduces the risk of primary-care consultations for knee OA and knee pain by 22% and 20% respectively5.
There are several mechanisms by which propranolol may cause analgesia. These include blocking the β2 adrenoreceptors on the peripheral nociceptors, dorsal root ganglia, and superficial dorsal horn17–19, regulation of periaqueductal grey neurons firing, interference with sensitization in the rostral ventromedial medulla and locus coeruleus20,21, and increased analgesic effect of opioids22. Propranolol also induces infiltrative cutaneous analgesia and is more potent than lidocaine23. It acts by blocking the voltage sensitive Na+ and Ca2+ channels, reducing Na+ and Ca2+ influxes, and decreasing intracellular cyclic adenosine monophosphate (AMP) via reduction of the adenyl-cyclase activity23.
Our findings are broadly consistent with the results of previous observational studies reporting less severe pain and lower analgesic requirements in people prescribed β-blockers6,7. In intervention studies, propranolol has shown analgesic benefits on musculoskeletal pain due to fibromyalgia, temporomandibular joint dysfunction and reduced post-operative analgesic requirement in people undergoing surgery24–26.
However, the findings of our current study do not agree with those of a study using data from the Osteoarthritis Initiative which reported no difference in pain severity between people prescribed and not prescribed β-blockers. This may be due to a lack of power to detect differences in that study, with a modest sample size of 1,168 and only 15% of participants being exposed to β-blockers27.
Propranolol may be particularly suitable as an analgesic for people with OA who have comorbid anxiety28. Similarly, it may be useful in treatment of neuropathic-like OA pain that is non-responsive to NSAIDs and driven by β2 adrenoreceptor stimulation19. Additionally, people with low COMT gene activity may benefit more from propranolol as an analgesic29. This is of particular mechanistic relevance as >70% Caucasians have COMT (158Met) polymorphisms that confer low activity of the COMT gene30.
In the present study, atenolol prescription associated with an increased risk of TJR; this was an unexpected finding given the results of our previous study in which atenolol reduced the risk of incident knee pain. This discordance may be due to the fact that β1-adrenoreceptor blockade reduces bone resorption and increases bone mineral density31, and increased bone mineral density associates with an increased risk of TJR32. Additionally, increased bone mineral density is also causally associated with end-stage OA according to a mendelian randomisation study using data from the UK Biobank33. Unlike β1-adrenoreceptor blockade, β2-adrenoreceptor blockade with propranolol does not affect bone resorption or increase bone mineral density31.
The findings of this study should be validated in independent datasets and confirmed in a randomised controlled trial before propranolol is adopted as an analgesic for people with OA.
The strengths of our study are its power derived from a large population sample size, confounder control by achieving covariate balance between PS-matched β-blocker exposed and unexposed groups, and adjustment for other factors such as health-seeking behaviour and comorbidities. We are confident that the majority of people with OA were included in this study as it is unlikely that someone with OA will be seen in a secondary care hospital service, including private settings, without consulting their GP first given GPs are the first port of call for people with chronic conditions in the UK. This increases generalisability of the study findings. People with less than two years of registration in their current GP practice were excluded to minimise the chance of including prevalent cases of OA as incident OA. Additionally, we excluded participants with chronic painful conditions and contra-indications to β-blockers to minimise confounding by indication that may not be addressed by PS matching.
To define the start of the follow-up period, we used a validated definition of primary care diagnosis of knee or hip OA34,35 and did not define our population just on consultation for knee or hip joint pain. Similarly, we used a GP entry of joint replacement surgery to define our outcomes. This has been validated against Hospital Episode Statistics (HES) and UK joint registry data and shown to have excellent validity36,37. Only 60% of CPRD practices are linked to HES and restricting the dataset to such practices would result in loss of sample size.
There are limitations to this study. First, we used primary care consultation for knee or hip OA which is likely to be later than the onset of OA symptoms. However, it is unlikely that this delay will be different according to the exposure status. Second, the exposure was dichotomised as present or absent and we did not analyse cumulative dose response. Third, our controls were not individuals initiating another drug (i.e., active comparator). This is because there is a hierarchy in the use of different drugs for the treatment of cardiovascular diseases in the UK driven by NICE guidelines. For example, the NICE guidelines recommend beta-blockers to treat resistant hypertension that has failed to respond to most other anti-hypertensive agents including ACE inhibitors, diuretics, angiotensin-II receptor blockers and calcium channel blockers. In contrast, they recommend β-blockers as first-line drugs for treatment of angina, atrial fibrillation, and heart failure. Therefore, using an active comparator study design would introduce biased selection of unexposed participants. Primary-care prescriptions in the UK are typically issued for four weeks at a time. In this study, exposed participants were required to receive two prescriptions in a 60-day period in order to enrich the sample with participants likely to continue with β-blocker treatment. This introduces immortal time bias as follow-up started at first prescription (index date). However, as both exposed and unexposed participants were required to have at-least 90 days of follow-up from their index date without undergoing TJR, immortal time bias between the first and second prescription is cancelled out.
In summary, we report that the non-selective β-blocker propranolol reduces the risk of knee or hip TJR. A randomised controlled trial is required to further evaluate the analgesic potential of propranolol in OA.
This study used data from the Clinical Practice Research Datalink (CPRD). Due to the CPRD data sharing policy, data used in this study cannot be shared with the third party. However, access to CPRD data can be requested directly from the CPRD (enquiries@cprd.com).
All authors conceived the study, interpreted results, contributed to and approved the final version of the manuscript. GN performed data analysis supervised by AA and MJG. GN and AA wrote the first-draft of the manuscript.
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Partly
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: chronic pain mechanisms and neuroimmune studies
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
References
1. Tamimi I, García-Meléndez G, Vieitez-Riestra I, Palacios-Penedo S, et al.: The Use of β-Blockers and the Risk of Undergoing a Knee Arthroplasty: A Nested Case-Control Study.J Bone Joint Surg Am. 2023; 105 (19): 1494-1501 PubMed Abstract | Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Hip and knee arthroplasty; autonomic musculoskeletal interactions; osteoporosis; hip and knee arthroscopy; epidemiology; traumatology
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
No
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?
Partly
Are the conclusions drawn adequately supported by the results?
No
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: arthroplasty; knee arthroplasty; hip arthroplasty; osteotomy; periprosthetic join infection; revision arthroplasty
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Version 1 06 Oct 23 |
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