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. 2025 Oct 1;10(10):782–795. doi: 10.1530/EOR-2025-0022

Placebo response to intra-articular injections in knee osteoarthritis: magnitude, evolution over time, and influencing factors. A systematic review and meta-analysis with meta-regression

Davide Previtali 1,2,✉, Angelo Boffa 3, Giorgio Di Laura Frattura 1,4, Giulia Merli 5, Giuseppe Filardo 1,6
PMCID: PMC12495556  PMID: 41031623

Abstract

Purpose

  • To quantify the response to intra-articular saline administration in terms of pain, function, and quality of life, with a focus on the evolution of placebo response over time and the identification of influencing factors on the placebo response to knee osteoarthritis injections.

Methods

  • After registration on PROSPERO, a systematic review was conducted following PRISMA guidelines to identify double-blind, placebo-controlled randomised clinical trials on intra-articular knee injections for knee osteoarthritis. The placebo response was evaluated through meta-analyses of VAS pain, WOMAC, KOOS, and responder rates at 1-, 3-, 6-, and 12-months on placebo arms of included trials. The evolution of placebo response over time was assessed, and meta-regression was conducted. Risk of bias and quality of evidence were assessed following Cochrane guidelines.

Results

  • From the initial 2,746 records, 73 articles on 5,895 patients were included. The meta-analysis demonstrated statistically and clinically significant improvements at the 1-, 3-, and 6-month follow-ups. At the 12-month follow-up, placebo response declined and was no longer clinically significant for some sub-scores. Responder rates exceeded 50% at 1-, 3-, and 6-months. The placebo response was stronger in studies with a higher proportion of female participants and in more recently published trials.

Conclusions

  • Placebo response to intra-articular injections is statistically and clinically significant in knee osteoarthritis for pain, function improvement, and patients' quality of life, with responses peaking at 4–8 months but evidence up to 12 months. Among influencing factors, female sex and recent publications seem to present stronger placebo responses, emphasising the importance of placebo-controlled trials to evaluate knee osteoarthritis treatments.

Keywords: knee, osteoarthritis, intra-articular injections, placebo

Introduction

Placebo is a well-known component of the treatment response in knee osteoarthritis (OA) (1, 2), yielding an improvement that frequently equalises the therapeutic effect of commonly used as well as promising OA treatments (3, 4). Among all approaches, intra-articular administration of saline, commonly used as a control in studies on active treatments, has been shown to strongly induce a placebo response (5). Placebo response to intra-articular knee injections includes both a reduction of pain and an increase of knee function (1), with a rate of responders quantified as being higher than 50% at 3 and 6 months (1). New randomised controlled trials (RCTs) suggest that a significant improvement could also be present for questionnaires assessing patients’ quality of life (6, 7, 8).

A key challenge in the placebo response is the high variability reported in the published RCTs on intra-articular injections in knee OA. This could be due to different patient- and treatment-related factors that can influence the response to placebo (9). The ability to recognise these factors could help in evaluating treatment response in clinical practice and in designing clinical trials. Previous meta-analyses and systematic reviews tried to identify possible influencing factors but were limited by focussing on a low number of included trials (1, 2, 5). Furthermore, while documented up to 6 months, there are still no data on the evolution of the placebo response after this timeframe, which impairs the understanding of the interplay of placebo response with the Hawthorne phenomenon and regression to the mean, as well as the proper interpretation of RCT results at longer follow-up. Quantifying the placebo component across the various dimensions of patient symptoms over time may offer novel insights and serve as a reference for better understanding the placebo response.

The aim of this systematic review and meta-analysis was to quantify the response to intra-articular saline administration in terms of pain, function, and quality of life, with a focus on the evolution of placebo response over time and the identification of influencing factors, providing a comprehensive reference on the evidence on the placebo response of intra-articular knee OA injections.

Materials and methods

Data sources

This meta-analysis with systematic review was conducted following a protocol published on PROSPERO. The following string was used without filters on PubMed (1974–2024), Web of Science (1990–2024), and Cochrane Library (no limits-2024) to retrieve all eligible articles up to January 3rd 2024: (knee) AND (osteoarthritis OR OA) AND (injections OR intra-articular) AND (saline OR placebo).

Study selection

The following inclusion criteria were used to select the eligible studies: double-blind RCTs including a placebo control arm undergoing knee intra-articular saline injections for knee OA; studies assigning both knees of patients treated bilaterally to the same group; studies reporting symptom differences from baseline or both baseline and follow-up data; and studies on humans. All the studies not respecting these criteria were excluded. The inclusion/exclusion process started by reading titles and abstracts. When not enough information could be obtained from the abstract, the full-text article was read to evaluate eligibility. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were used (10). Two authors independently performed the article selection and data extraction process, with disagreement on study eligibility solved by a third author. Patient/public involvement was not feasible for this study.

Data extraction and outcome measures

Information on trial methodology was collected, including level of evidence, study design, inclusion/exclusion criteria, blinding procedures, randomisation methods, follow-up duration, details on saline injection, and experimental treatments tested. In addition, the following data on the study population were extracted: number of patients screened, included, and lost to follow-up; sex, age, body mass index (BMI), and OA grade; patient-reported outcome measures (PROMs); complication rates; functional tests’ results; knee range of motion (ROM); responder rates; and radiological outcomes. When standard deviations or standard errors were not available from the full-text articles (as in 21 out of 73 articles), they were estimated using established methods (11, 12). When results were not available in the text but were presented in graphs, data were extracted electronically following Cochrane guidelines (13, 14). The primary outcome of the meta-analysis was the change from baseline in knee pain following saline injections measured using a Visual Analogue Scale (VAS). Secondary outcomes included changes in the Western Ontario and McMaster Osteoarthritis Index (WOMAC) sub-scores (pain 0–20, stiffness 0–8, function 0–68), the Subjective International Knee Documentation Committee Score (IKDC), Knee Injury and Osteoarthritis Outcome Score (KOOS) sub-scores (Pain, other Symptoms, Function in Daily Living, Function in Sport and Recreation, and knee-related Quality of Life), and responder rates. Four different follow-up time points were analysed: 1 month (4–6 weeks), 3 months (12–16 weeks), 6 months (24–28 weeks), and 12 months. Due to the limited number of studies reporting results at 24 months, analyses for this time point were not feasible. In addition, PROM results were compared to previously reported Minimal Clinically Important Differences (MCID): 13.7/100 for VAS pain score, 1.5/20 for WOMAC pain score, 0.6/8 for WOMAC stiffness score, 4.6/68 for WOMAC function score, 8.6 for IKDC subjective score, 9.3 for KOOS pain, 8.4 for KOOS other symptoms, 9 for KOOS function in daily living, 12.5 for KOOS function in sport and recreation, and 10.3 for KOOS knee-related quality of life (15, 16, 17). For the responder rate analyses, three different time points were considered: 1, 3, and 6 months. Two analyses were performed for the responder rate: i) including all studies reporting it, regardless of the criteria used, and ii) including only studies using the OMERACT-OARSI criteria, the most widely accepted criteria in the field (18). To avoid misleading underpowered analyses, the meta-analyses were performed for all the outcomes reported in at least five studies. The evolution of placebo response over time was then evaluated.

The influence on the response to placebo for the type of injected treatment in the comparison group was analysed with a sub-analysis. Furthermore, the impact of various studies and patient characteristics on the response to saline was assessed, including the response in the experimental group, mean age, BMI, type of experimental product, publication year, and symptom duration. The influence of the per capita Gross Domestic Product (GDP) and Human Development Index (HDI) of the country (https://www.worldometers.info/gdp/gdp-per-capita/ and https://hdr.undp.org/data-center/human-development-index#/indicies/HDI consulted on 24.07.2024) where the studies were conducted was also analysed.

Risk of bias and quality of evidence assessment

The risk of bias was assessed using the revised tool for risk of bias in randomised trials (RoB 2.0) (19), and the overall quality of evidence for each outcome was graded according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidelines (https://gdt.gradepro.org/app/handbook/handbook.html consulted on 05.09.2024).

Statistical analysis

The statistical analysis was performed using the meta (v4.11-0, Schwarzer G, 2007) and metafor (v2.4-0, Viechtbauer W, 2010) packages in RStudio (v1.2.5019).

The placebo response was assessed through a single-arm meta-analysis, synthesising the results from the placebo arms of the included trials with the function meta-mean for continuous variables and the function metaprop for dichotomous variables. For the meta-mean function, the DerSimonian and Laird (DL) method was used to estimate between-study variance (tau2). Prevalence meta-analyses were conducted using logit-transformed proportions and the maximum likelihood (ML) estimator for tau2, as implemented in the metaprop() function of the R meta package. For continuous variables, the placebo response was represented by the mean difference (MD) from baseline to various follow-up points. In the case of dichotomous variables, the response to saline injections was evaluated through a single-arm meta-analysis of prevalence. A random-effects model was chosen to address heterogeneity across the included studies. Subgroup analyses were carried out for influencing factors expressed as nominal variables.

Separate linear random-effects meta-regressions were performed with the function metareg, which internally uses the method of moments (DL) to estimate tau2, to investigate potential influencing factors represented as continuous variables. In addition, a multiple meta-regression was conducted with the function rma with restricted maximum likelihood (REML) estimation of tau2 to incorporate all the extracted variables. The meta-regression focused on the data for changes in VAS at 6 months or, when unavailable, at 12 months. For studies that did not report VAS changes, the WOMAC pain subscale (converted from a 0–20 scale to a 0–100 scale) was used. To check the robustness of the meta-regression models, we performed an influence analysis using standardised residuals, Cook’s distances, and leverage statistics for the variables found to be significant in the meta-regression models.

The linear mixed model meta-analysis was performed using the rma function of the metafor package, with follow-up time as study-level variables (often referred to as ‘moderators’). The linear mixed model meta-analysis was based on the data reported in the included studies in terms of VAS pain or WOMAC pain subscale (converted from a 0–20 scale to a 0–100 scale) when VAS pain data were not available. To investigate the time course of the placebo response, we extracted all available mean changes from baseline in the saline injection arms of the included RCTs at each reported follow-up across studies. For each distinct follow-up time, we conducted a separate random-effects meta-analysis using the restricted maximum likelihood (REML) estimator to pool the standardised mean differences (SMDs). We then modelled the relationship between follow-up time and the magnitude of the placebo response using a polynomial meta-regression, with time (in months) as a continuous predictor. We chose a quadratic term for time as it provided the best fit according to Akaike’s Information Criterion (AIC). To enhance the robustness of the fitted curve, we excluded pooled time points derived from fewer than ten studies, as these estimates were considered less reliable.

A significance level of P = 0.05 was applied to all analyses.

Results

Article selection and patients’ characteristics

The PRISMA flowchart of the article selection process is shown in Fig. 1. After duplicate exclusion and the application of inclusion and exclusion criteria, 73 articles on 5,895 patients were included out of the original 2,746 extracted records. The experimental product tested against placebo was a hyaluronic acid derivative in 32 studies (20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53), a blood derivative (i.e. platelet-rich plasma – PRP – or similar products) in 13 studies (6, 7, 23, 30, 40, 54, 55, 56, 57, 58, 59, 60, 61), a steroid product in ten studies (28, 62, 63, 64, 65, 66, 67, 68, 69, 70), and a cell-based product in five studies (8, 71, 72, 73, 74); other products such as low-molecular-weight fibrinogen (LMWF-5A), disease-modifying anti-rheumatic drugs (DMARDs), sprifermin, lidocaine, homoeopathic drugs, botulinum toxin, and prolotherapy were used in a lower number of studies (75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89). Included studies were published between 1994 and 2023. The mean age of patients in these studies ranged from 46.6 to 71.0 years, whereas the mean BMI ranged from 25.5 to 34.5 kg/m2. The detailed characteristics of each included study are reported in Table 1.

Figure 1.

Figure 1

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PRISMA Flowchart of the study inclusion process.

Table 1.

Characteristics of the included studies evaluated as possible influencing factors in the meta-regression.

Study Country GDP ($) HDI Patient characteristics Experimental drug F-U Risk of bias
M F Age (y) BMI (kg/m2) Symptoms duration (y)
Altman et al. (20) Multi-centric 63 111 63.3 29.5 6.5 HA 6 m Some concerns
Altman et al. (21) USA 63,544 0.927 109 186 60.8 33.0 NR HA 6 m Some concerns
Arden et al. (22) Multi-centric 59 51 60.9 27.5 3.1 HA 6 w Some concerns
Auw-Yang et al. (75) Netherlands 59,229 0.946 43 30 53.0 28.0 NR Anti-IL1R 1 y Some concerns
Baltzer et al. (23) Germany 53,694 0.950 39 68 60.3 NR NR PRP or HA 6 m Some concerns
Bar-Or et al. (76) USA 63,544 0.927 57 107 NR NR NR LMWF-5A 3 m Some concerns
Bennel et al. (54) Australia 52,518 0.964 60 84 61.6 29.6 6.0 PRP 1 y Low
Brandt et al. (24) USA 63,544 0.927 26 43 67.0 29.8 NR HA 25 wk Some concerns
Chao et al. (70) USA 63,544 0.927 31 2 63.2 NR 12.5 Steroids 3 m Some concerns
Chevalier (25) Multi-centric 41 88 62.5 29.8 5.8 HA 6 m Low
Chu (55) China 17,312 0.788 127 175 54.5 27.9 NR PRP 2 y Low
Conaghan et al. (68) Multi-centric 39 61 59.7 31.2 6.4 Steroids 6 m Some concerns
Conaghan et al. (69) Multi-centric 66 96 62.4 30.2 6.6 Steroids 6 m Low
Day et al. (26) Australia 52,518 0.964 51 73 62.0 NR NR HA 3 m Some concerns
Dório (56) Brazil 29,462 0.760 2 19 62.5 27.6 7.1 PRP 6m Low
Eckstein et al. (77) Multi-centric 32 76 64.6 29.3 7.0 Sprifermin 2 y Low
Eker (78) Turkey 28,120 0.855 14 12 69.7 30.7 4.8 Lidocaine 3 m Low
Görmeli et al. (30) Turkey 28,120 0.855 20 20 52.8 29.5 NR PRP or HA 6 m Some concerns
Gupta et al. (27) India 6,454 0.644 22 51 53.6 26.2 NR HA 2 m Some concerns
Hangody et al. (28) Multi-centric 18 51 58.0 29.1 NR HA + steroids Or HA 6 m Some concerns
Henrotin (29) France 46,227 0.910 10 31 63.0 30.8 5.9 HA + mannitol 6 m Some concerns
Hochberg et al. (79) Multi-centric 32 76 64.5 29.2 7.0 Sprifermin 2 y Low
Huang et al. (31) Taiwan 68,730 NR 22 78 64.2 25.4 1.0 HA 25 wk Some concerns
Hunter (67) Australia 52,518 0.964 7 18 64.8 27.9 NR Steroids 6 m Low
Huskisson (32) UK 44,916 0.940 21 29 64.8 NR NR HA 6 m Some concerns
In & Ha (34) S. Korea 43,124 0.929 1 5 61.7 NR 2.5 HA 3 m Some concerns
Jørgensen et al. (35) Denmark 60,399 0.952 73 97 61.4 NR 6.7 HA 1 y Some concerns
Jubb et al. (33) UK 44,916 0.940 72 128 65.0 29.8 8.5 HA 1 y Some concerns
Kandel (36) Israel 41,855 0.915 59 NR NR NR HA 3 m Some concerns
Karlsson et al. (37) Sweden 54,563 0.952 22 35 71.0 NR NR HA 1 y Some concerns
Ke (38) China 17,312 0.788 48 172 61.6 25.4 NR HA 6 m Low
Kim et al. (71) S. Korea 43,124 0.929 26 101 63.8 25.9 9.0 Allo-Chondrocytes 1 y Some concerns
Kon et al. (6) Multi-centric 9 5 54.0 NR NR PRP 1 y Low
Kul-Panza & Berker (39) Turkey 28,120 0.855 5 18 62.8 29.9 6.3 HA 3 m Some concerns
Lee et al. (73) S. Korea 43,124 0.929 25 58.0 25.0 NR TissueGene-c 6 m Some concerns
Lee et al. (72) S. Korea 43,124 0.929 14 21 56.0 30.0 NR AD-MSC 6 m Some concerns
Lin & Renn (40) China 17,312 0.788 10 17 62.2 25.0 NR PRP or HA 1 y Some concerns
Lohmander et al. (41) Sweden 54,563 0.952 53 67 58.0 NR NR HA 20 wk Some concerns
Lozada (80) USA 63,544 0.927 46 67 59.7 29.6 NR Tr14/Ze14 12 wk Low
Lundsgaard et al. (42) Denmark 60,399 0.952 77 90 NR NR NR HA 6 m Low
McAlindon et al. (66) USA 63,544 0.927 32 38 57.2 31.7 NR Steroids 2 y Low
McAlindon (81) Multi-centric 38 51 61.1 30.4 7.6 Onabotulinumtoxin A 24 wk Low
Mendes et al. (82) Brazil 29,462 0.760 2 33 64.6 30.5 5.3 Botox 3 m Low
Migliore (43) Multi-centric 115 230 63.8 28.5 4.8 HA 6 m Low
Navarro-Sarabia et al. (44) Spain 38,335 0.911 128 25 63.9 28.7 8.1 HA 40 m High
Nishida et al. (45) Japan 42,917 0.920 75 145 62.4 25.6 5.2 HA 6 m Some concerns
Nunes-Tamashiro et al. (57) Brazil 29,462 0.760 3 30 68.0 30.2 7.8 PRP 1 y Low
Patel & Dhillon (58) India 6,454 0.644 6 17 53.7 26.2 NR PRP 6 m Some concerns
Pavelka et al. (83) Czech Rep 41,737 0.895 10 25 62.7 NR NR GAGPS 6 m Some concerns
Petrella et al. (46) Canada 48,073 0.935 20 30 71.0 27.1 7.4 HA 3 m Some concerns
Pereira (47) Switzerland 71,352 0.967 5 3 54.8 28.7 NR HA 1 m Some concerns
Petterson (53) USA 63,544 0.927 79 106 58.7 30.4 NR HA 6 m Low
Ravaud et al. (64) France 46,227 0.910 10 18 63.0 29.0 NR Steroids 6 m Some concerns
Raynauld et al. (65) Canada 48,073 0.935 13 21 63.3 NR 8.7 Steroids 2 y Some concerns
Regina Sit et al. (84) Hong Kong 59,238 0.956 11 27 63.7 25.0 8.2 Prolotherapy 1 y Some concerns
Ross (63) Multi-centric 37 60 61.3 30.4 6.3 Steroids 6 m Low
Rossini et al. (86) Italy 41,840 0.906 5 35 66.2 29.1 NR Clodronate 3 m Some concerns
Sadri (8) Iran 13,116 0.780 2 18 56.1 29.1 NR Cells 1 y Some concerns
Salottolo (85) USA 63,544 0.927 12 12 63.1 34.4 NR LMWF-5A 3 m Low
Saraf (59) India 6,454 0.644 12 15 55.9 26.6 NR PRP 1 y Some concerns
Scale et al. (48) Germany 53,694 0.950 20 20 58.6 NR 5.9 HA 3 m Some concerns
Schwappach et al. (87) USA 63,544 0.927 7 13 61.4 28.7 NR LMWF-5A 1 y Low
Sert et al. (88) Turkey 28,120 0.855 2 20 54.4 32.3 2.1 Prolotherapy 6 m Some concerns
Shrestha et al. (62) Nepal 4,009 0.601 23 37 67.1 NR NR Steroids 3 m Some concerns
Smith (60) USA 63,544 0.927 6 9 46.6 27.5 NR PRP 1 y Low
Soltani (74) Iran 13,116 0.780 1 9 55.8 28.9 NR Placental MSC 6 m High
Strand (49) USA 63,544 0.927 51 77 60.3 28.7 2.6 HA 3 m Low
Takamura et al. (50) USA 63,544 0.927 60 99 62.8 NR 0.7 HA 6 m Some concerns
Tschopp et al. (61) Switzerland 71,352 0.967 16 12 58.0 25.1 NR PRP 2 y Low
Van Der Weegen et al. (52) Netherlands 59,229 0.946 50 47 60.1 29.3 5.6 HA 6 m Some concerns
Wobig et al. (51) Germany 53,694 0.950 14 40 59.0 NR 6.0 HA 6 m Some concerns
Yacizi (89) USA 63,544 0.927 42 72 60.7 29.2 NR DMARDs 1 y Some concerns
Yurtbay (7) Turkey 28,120 0.855 83 29 NR NR NR PRP 1 y High
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NR, not reported; Wk, week; m, months; y, year; US, ultrasound; HA, hyaluronic acid; LMWF-5A, low-molecular-weight fraction of 5% human serum albumin; PRP, platelet-rich plasma; AD-MSC, adipose-derived mesenchymal stem cells; GAGPS, glycosaminoglycan polysulphuric acid; MSC, mesenchymal stem cells.

Response to intra-articular saline injections

The meta-analyses on VAS-pain showed a statistically and clinically significant improvement of pain at the 1-month follow-up, the 3-month follow-up, and the 6-month follow-up, whereas at the 12-month follow-up the improvement was statistically significant without exceeding the MCID.

Regarding the WOMAC sub-scales, the improvements were both statistically and clinically significant at all follow-ups, except for WOMAC-stiffness at the 12-month follow-up. In particular, the improvement in terms of mean difference for WOMAC-pain at 1 month was 3.2, at 3 months was 3.1, at 6 months was 3.2, and at 12 months was 2.5; for WOMAC-stiffness the improvement in terms of mean difference at 1 month was 1.3, at 3 months was 1.1, at 6 months was 1.1, and at 12 months was 0.6; the improvement in terms of mean difference for WOMAC-function at 1 month was 9.8, at 3 months was 9.8, at 6 months was 10.0, and at 12 months was 7.0.

The meta-analysis on the KOOS pain sub-scale showed a statistically and clinically significant difference at 1 month, at 3 months, and at 6 months whereas at 12 months the difference was statistically significant without exceeding the MCID. The meta-analysis on the KOOS other symptoms sub-scale showed a statistically and clinically significant difference at 1 month, at 3 months, and at 6 months, whereas at 12 months the difference was not statistically significant. The meta-analysis on the KOOS function in daily living sub-scale showed a statistically and clinically significant difference at 1 month, at 3 months, at 6 months, and at 12 months. The meta-analysis on the KOOS function in sport and recreation sub-scale showed a statistically and clinically significant improvement at 3 months and at 6 months, and a statistically significant difference at 1 month and at 12 months without exceeding the MCID. The meta-analysis on the KOOS knee-related quality of life sub-scale showed a statistically and clinically significant difference at 1 month, at 3 months, and at 6 months, whereas at 12 months the difference was statistically significant without exceeding the MCID (Fig. 2). For the detailed results of the meta-analyses please see Table 2.

Figure 2.

Figure 2

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Diagram synthesising the results of the meta-analysis for VAS-pain, WOMAC subscales, and KOOS subscales in terms of change from baseline at the 1-month, 3-month, 6-month, and 12-month follow-ups. The grey area represents MCID for each score.

Table 2.

Results of the meta-analysis.

1 month 3 months 6 months 12 months
STS, n MD (95%CI) P I 2 STS, n MD (95%CI) P I 2 STS, n MD (95%CI) P I 2 STS, n MD (95%CI) P I 2
VAS-pain 29 18.8 (13.7–23.8) <0.0001 98% 41 18.9 (15.6–22.1) <0.0001 95% 37 15.7 (11.9–19.5) <0.0001 98% 14 12.5 (7.5–17.4) <0.0001 91%
WOMAC
 Pain 29 3.2 (2.8–3.7) <0.0001 85% 37 3.1 (2.7–3.4) <0.0001 88% 31 3.2 (2.6–3.8) <0.0001 94% 10 2.5 (1.3–3.8) <0.0001 95%
 Stiffness 15 1.3 (1.0–1.5) <0.0001 69% 25 1.1 (0.9–1.3) <0.0001 80% 22 1.1 (0.8–1.4) <0.0001 89% 9 0.6 (0.1–1.1) 0.03 87%
 Function 20 9.8 (8.3–11.3) <0.0001 76% 31 9.8 (8.4–11.3) <0.0001 86% 28 10.0 (8.2–11.8) <0.0001 91% 10 7.0 (3.3–10.9) 0.0002 95%
KOOS
 Pain 5 11.8 (9.6–14.1) <0.0001 74% 8 12.0 (6.4–17.7) <0.0001 82% 7 4.5 (9.4–19.6) <0.0001 86% 6 8.7 (5.0–12.5) <0.0001 91%
 Other symptoms 5 11.7 (9.4–13.9) <0.0001 78% 7 15.5 (8.6–22.3) <0.0001 93% 6 15.9 (9.7–22.1) <0.0001 96% 6 3.4 (−2.3 to 9.1) 0.456 98%
 Daily living 5 14.7 (12.0–17.3) <0.0001 95% 8 15.4 (9.5–21.3) <0.0001 89% 7 15.2 (9.8–20.6) <0.0001 88% 5 10.3 (5.3–15.3) <0.0001 84%
 Sport and recreation 5 11.8 (9.1–14.5) <0.0001 98% 8 12.6 (6.0–19.3) 0.0002 82% 7 12.5 (5.0–20.1) 0.001 85% 6 8.9 (2.8–14.9) 0.004 92%
 Quality of life 4 10.9 (7.1–14.8) <0.0001 76% 7 15.3 (10.5–20.1) 0.0001 86% 6 15.5 (8.7–22.4) <0.0001 94% 5 9.6 (4.5–14.7) 0.0002 75%
Responder rate* 5 51% (27–74%) - 85% 12 51% (38–65%) - 89% 17 56% (46–66%) - 89% - - - -
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STS, studies; MD, mean difference; CI, confidence interval; VAS, visual analogue scale; WOMAC, Western Ontario and McMaster Universities Arthritis Index; KOOS, Knee Injury and Osteoarthritis Outcome Score.

*

Frequency (95% CI) is provided.

Due to the low number of studies reporting this item, the analysis on the IKDC subjective score was not possible (reported by two studies at 1 month, three studies at 3 months, four studies at 6 months, and two studies at 12 months of follow-up).

The meta-analysis of prevalence on the responder rate showed a rate of responders at 1 month of follow-up of 51% (95% CI: 27–74%), at 3 months of 51% (95% CI: 38–65%), and at 6 months of 56% (95% CI: 46–66%). In the sub-analysis including only the studies using the OMERACT OARSI criteria, the rate of responders at 1 month of follow-up was 50% (95% CI: 37–63%), at 3 months of follow-up was 56% (95% CI: 44–67%), and at 6 months of follow-up was 61% (95% CI: 52–68%).

Determinants of the placebo response

The analysis of the evolution of the placebo response over time showed that the maximum placebo response was reached 4–8 months after the injection with a subsequent progressive decrease (Fig. 3).

Figure 3.

Figure 3

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The diagram illustrates the curve of the placebo response over time in terms of pain, derived from the linear mixed-effects model meta-analysis. The model was based on data from the included trials at all reported follow-up time points, using VAS-pain scores or WOMAC-pain subscale scores (converted from a 0–20 scale to a 0–100 scale when VAS data were not available).

The sub-analysis based on the type of injected treatment in the experimental group showed a statistically significant improvement in all sub-groups without statistically significant differences among groups (P < 0.05).

The linear meta-regression showed that the male/female ratio of the included patients is a statistically significant factor influencing the placebo response, with a greater placebo response in the studies including more females. The estimate suggests that each one-point increase in the male-to-female ratio is associated with a 1.4-point decrease in the placebo response (estimate: −1.378, P = 0.04); a tendency towards significance as a potential influencing factor for placebo responses was found for the year of publication, with placebo responses increasing for the most modern studies (estimate: 0.3105, P = 0.07). The multiple meta-regression including both these influencing factors confirmed the significance of both male/female ratio (estimate: −1.4320, P = 0.01) and year of publication (estimate: 0.3327, P = 0.02). Neither the linear meta-regressions nor the multiple meta-regressions showed a statistically significant influence on the magnitude of placebo response for the response in the experimental treatment group, the mean age and BMI of patients, symptom duration, the per capita GDP, and the HDI of the country where the studies were conducted. Results of all meta-regression and bubble plots of the meta-regression models for significant variables are shown in Supplementary (see section on Supplementary materials given at the end of the article). Influence diagnostics showed that no single study had a disproportionate impact on the meta-regression results.

Risk of bias and quality of evidence

The risk of bias analysis showed an overall good methodological quality of the included studies. In fact, according to the strict criteria of Cochrane’s RoB 2.0 tool, 25 studies had a low risk of bias, 45 some concerns of bias, and only three studies had a high risk of bias. For the studies with some concerns of bias, this was mainly due to an unclear randomisation sequence concealment method or to the absence of reference to a previously published protocol. For the three studies with a high risk of bias, the main problems were the high drop-out rate in the study of Navarro-Sarabia et al. (44), the baseline differences between groups in the study of Soltani et al. (74), and the limited and unbalanced adherence to the assigned intervention in the study of Yurtbay et al. (7).

Due to the high number and the overall good quality of the included studies as well as the magnitude of the results, the quality of the evidence was moderate to high for VAS and WOMAC sub-scales. The results of KOOS are obtained from a limited number of studies and could be more influenced by studies with some concerns of bias. Moreover, the magnitude of the results was smaller for some of the sub-scales and follow-ups, thus limiting the confidence of those findings. Details of the risk of bias and quality of evidence analysis are reported in the supplementary data.

Discussion

The main finding of this meta-analysis is that the placebo response of intra-articular injections is both statistically and clinically significant in knee OA. Its relevance has been demonstrated in terms of pain and function improvement, as well as in the enhancement of patients' quality of life, with responses peaking at 4–8 months but evidence up to 12 months. Among patient factors, female sex presented a stronger placebo response. Finally, more placebos were found in recent publications, further emphasising the importance of performing placebo-controlled randomised clinical trials to evaluate the efficacy of knee OA treatments.

Placebo in intra-articular knee OA injections has been previously studied, with evidence of short-term improvements in both pain and function (1). This updated and comprehensive meta-analysis documented even longer-lasting improvements, and how they encompass all dimensions of patients’ symptoms, significantly affecting their quality of life. Quality of life items are widely used in cost-effectiveness analyses, which play a key role in defining new treatment guidelines. This is the focus of one of the sub-scores of KOOS, the most comprehensive knee OA scoring system, whose popularity has progressively increased over the past 30 years, both in observational and randomised clinical trials (90). The high number of trials published in recent years made it possible to analyse the placebo response in terms of all KOOS sub-scores across four different follow-up time points. The placebo response was found to be statistically and clinically significant for all sub-scores, despite the higher MCID identified in the literature for KOOS compared to other clinical scoring systems (15). Accordingly, the quantification of placebo responses in terms of KOOS represents an important reference value for studies using KOOS to evaluate their outcomes, considering that KOOS values are significantly affected by placebo.

The present meta-analysis also provided an in-depth assessment of the placebo response in other scores commonly used in knee OA studies: VAS and WOMAC sub-scales. The analysis of 73 double-blind, placebo-controlled, randomised clinical trials strengthens the understanding of this topic and makes it possible to conclude, with a high level of evidence, that the placebo response of intra-articular injections in terms of VAS-pain and all WOMAC sub-scales is not only statistically but also clinically significant and long-lasting. Regarding its persistence over time, recent long-term trials enabled the evaluation of the placebo response’s presence and magnitude 12 months after injection. This analysis also revealed that the placebo response declines at 12 months. Specifically, the curve illustrating the evolution of the placebo response over time showed a peak between 4 and 8 months post-treatment, followed by a subsequent progressive decline.

Several factors may play a role in interpreting this finding. First of all, although some authors advocated a possible active effect of saline in knee injections (9, 91), the absence of a therapeutic effect has been demonstrated by trials directly comparing saline and sham injections (92). In this light, it seems reasonable that, after 6–8 months, the positive psychological effect of placebo diminishes in favour of the persistence or progression of an ‘untreated’ disease. Furthermore, the reduction in the placebo response at the 12-month follow-up aligns with the well-known regression to the mean phenomenon (93) and the possible emergence of new peaks in knee OA symptoms within the context of the typical irregular disease evolution pattern of knee OA (94). Regarding regression to the mean, it should be noted that the placebo response found in this meta-analysis overcomes the recently reported estimated regression to the mean for pain, function, and quality of life, thus suggesting that other factors are implied in placebo response and its evolution over time (95, 96).

Independently from the underlying reasons, the highlighted evolution patterns may have some implications on the interpretation of treatment effects. In this light, the comparison of intra-articular treatments against oral drugs may be highly influenced by the high placebo effect of intra-articular injections in the first 6 months. Important consequences can also affect the comparison of steroids, hyaluronic acid, and PRP, which are commonly used for the treatment of knee-OA-related symptoms (97). According to the literature evidence and recommendations, steroids and hyaluronic acid are particularly effective at the short term (3 months) and mid-term (6 months) follow-ups, respectively (98, 99, 100), whereas PRP seems to overcome those effects after 6 months (3). Knowing the time frame in which intra-articular injection placebo response is stronger helps in the interpretation of these literature data (101), since the effect of injective treatments in the first 6 months may be masked by the placebo response to any injection, with real benefit becoming evident only after the ‘wash-out’ of the placebo response.

The placebo response may influence the study results based on the evaluation time, but also based on specific characteristics of the studied patient cohort. A meta-regression was conducted to evaluate the factors associated with the placebo response, revealing the impact of patient sex, with female sex being associated with a stronger placebo response. The reasons behind qualitative and quantitative sex differences in pain biology are undoubtedly complex, involving a combination of sociological, psychological, and biological factors (102). These differences in placebo response should be taken into account when treating knee OA. Moreover, as suggested by some authors (103), although the direct administration of placebos presents clear ethical concerns, enhancing the placebo response could be a strategy to improve the results of active treatments and thereby maximise overall benefits in specific patients. Understanding patient-related factors that may amplify the placebo response is of paramount importance, both for patient management and also to study new treatments by ensuring a proper and balanced representation of patients in the study groups.

Besides sex, other patient-related variables have been suggested as potential influencing factors of the placebo response. To this regard, Yu et al. showed that worse baseline functional scores can be associated with a stronger placebo response at mid-term (3 months) and long-term (6 months) follow-ups (104). However, the present meta-analysis was unable to confirm these findings. In fact, baseline PROMs scores, as well as mean patient age, BMI, symptom duration, the GDP per capita, and the HDI of the country where the studies were conducted, were not found to correlate with the magnitude of the placebo response in the performed meta-regression. The analysis underlined instead another interesting factor that should be considered when considering this field. An additional factor found to influence the reported response in placebo arms was the year of publication of the study, with a stronger placebo response observed in more recent studies. While the placebo response is expected to decrease over time, different aspects may contribute in determining these results. The observed results are obtained through an interplay of both placebo and nocebo effects, which should also be taken into account. It has been demonstrated that the nocebo effect in pain modulation is at least as strong as the placebo effect (105) and that certain trial-related procedures, such as obtaining informed consent, may influence this effect (106). The study setting, the social and cultural environment, as well as the administration of new and therefore ‘innovative’ treatments might affect the placebo response. The initial fear of a new treatment could, during the initial years following the introduction of a new drug, outweigh the positive expectations towards the treatment’s potential effectiveness, while the hype of the following years could work in the opposite direction, explaining the complexity of this field. In this context, unlike the previous literature findings on other pathologies, no difference was found among the different experimental treatments, thereby limiting the ability to understand the influence of patients' expectations regarding the type of treatment on the placebo response.

This study presents some limitations. At first, the meta-analysis showed a high heterogeneity in the results of the included trials, reflecting the high heterogeneity of the literature on intra-articular knee injections (107). The meta-regression was unable to analyse other potential influencing factors, such as physician mood and verbal suggestions, on the placebo response. Although some recent trials have questioned their relevance in the orthopaedic field, stronger evidence is needed to address this limitation in the present meta-analysis as well as in the overall literature (108, 109). Furthermore, meta-regression is not the ideal method to evaluate the influence of patient-level variables on the results, due to the risk of aggregation and ecological bias. For this purpose, patient-level data should be used to better characterise the influencing factors. Further limitations of the present study include the limited number of studies available for the analysis of KOOS sub-scores at the 1-month and 12-month follow-ups, which restricted the level of evidence supporting these results. In addition, it was not possible to conduct an analysis on IKDC due to the small number of studies reporting this outcome. Finally, some conclusions regarding the effectiveness of placebo were drawn based on published MCID values. While it is acknowledged that MCID is not intended for use with aggregated data, as in meta-analyses, the decision to use it was based on its potential applicability in this field as an indicator of a clinically relevant response to treatment.

Despite these limitations, the present study defined the magnitude of the placebo response previously suggested for VAS-pain and WOMAC sub-scores and quantified it for the KOOS sub-scores. Finally, the study results provided other new key findings, with new insights into the evolution over time and potential influencing factors of the placebo response of intra-articular injections for knee OA.

Conclusion

The placebo response of intra-articular injections is both statistically and clinically significant in knee OA in terms of pain and function improvement, as well as in the enhancement of patients' quality of life, with responses peaking at 4–8 months but evidence up to 12 months. Among patient factors, female sex seems to present a stronger placebo response. Finally, more placebos were found in recent publications, further emphasising the importance of performing placebo-controlled randomised clinical trials to evaluate the efficacy of knee OA treatments.

Supplementary materials

ICMJE Statement of Interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the work reported.

Funding Statement

This work did not receive any specific grant from any funding agency in the public, commercial, or not-for-profit sector.

Author contribution statement

DP contributed to conception and design, analysis and interpretation of the data, drafting of the article, final approval of the article, provision of study materials or patients, statistical expertise, collection and assembly of data. AB was responsible for conception and design, critical revision of the article for important intellectual content, provision of study materials or patients, collection and assembly of data. GDLF and GM helped in critical revision of the article for important intellectual content, provision of study materials or patients, collection and assembly of data. GF was responsible for conception and design, analysis and interpretation of the data, drafting of the article, critical revision of the article for important intellectual content, final approval of the article.

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