Abstract
Abstract
Purpose
Total knee replacement (TKR) and patellofemoral joint replacement (PFR) are both surgical options for patellofemoral joint osteoarthritis. This study aimed to determine which procedure is more cost-effective.
Methods
A Markov model was constructed to evaluate the cost-effectiveness of PFR compared with TKR, using revision risk and age-specific mortality derived from UK life tables. A model-based economic evaluation was conducted from an NHS healthcare perspective, with costs derived from NHS reference costs. The model used a 60-year time horizon with annual cycles. Utility values were derived from patient-reported outcome measures collected between 6 and 18 months postoperatively and linked to 900 PFR and 287 777 TKR cases from the National Joint Registry.
To ensure comparability between groups, inverse probability of treatment weighting was used to adjust for age, sex, American Society of Anaesthesiologists classification, social deprivation indices, anaesthesia type, healthcare provider, surgeon experience, Charlson Comorbidity Index and preoperative EQ-5D-3L and Oxford Knee Scores.
Results
PFR was associated with lower costs than TKR, with an initial per-patient saving of approximately £4000. In younger patients, PFR was associated with slightly lower quality-adjusted life years (QALYs) compared with TKR, whereas in older patients it was associated with marginally higher QALYs. These differences resulted in variation in incremental cost-effectiveness ratios (ICERs) across age groups, with a trend towards greater cost-effectiveness of PFR in older populations. Cost savings decreased with age due to lower revision rates in older populations. Similar trends were observed across both sexes, although males experienced greater QALY gains, while PFR was more cost-effective overall in females. In younger patients, TKR was linked to higher costs and marginally lower effectiveness, though the difference in cost-effectiveness between PFR and TKR in this group was minimal.
One-way sensitivity analysis demonstrated that the model was highly sensitive to assumptions regarding postoperative utility following both PFR and TKR, with variation sufficient to alter the direction of the ICER. In contrast, revision utility and discount rate had relatively minor effects.
Conclusion
PFR may be a cost-effective alternative to TKR under certain assumptions, particularly in older patients; however, substantial decision uncertainty remains, driven primarily by variation in postoperative utility.
Keywords: Knee, Adult orthopaedics, Orthopedics
STRENGTHS AND LIMITATIONS OF THIS STUDY.
This study uses a large, nationally representative dataset from the National Joint Registry, enhancing generalisability and statistical power.
A long-term (60 years) Markov model with NHS perspective and real-world cost data improves relevance to healthcare decision-making.
The model is highly sensitive to assumptions around postoperative utility, introducing substantial decision uncertainty.
Utility values were derived from EQ5D-3L at 6–18 months.
Introduction
Total knee replacement (TKR) and patellofemoral joint replacement (PFR) are surgical treatments that have both been recommended for patellofemoral joint osteoarthritis (PFJ OA). Advantages of PFR over TKR include less blood loss, shorter hospital stays, preservation of bone stock and ligaments resulting in higher functional outcome and better stair-climbing abilities.1–7 Despite these advantages, just like any partial knee replacement, it is associated with a higher revision rate compared with TKR.8
A revision of a PFR is often converted to a primary TKR, typically without the need for augments or stemmed components. On the contrary, revising a TKR is a costly procedure, with the key challenge in surgical planning being the management of tibial and femoral bone loss, which frequently requires augments, significantly increasing the overall costs.9–11
However, a TKR is recognised as a durable and reliable procedure, associated with a lower revision risk compared with partial knee arthroplasty, such as a PFR.12–15 It is understandable that surgeons may prefer the latter, which perhaps explains why PFR accounts for only 1% of the National Joint Registry (NJR), in contrast to TKR rates, which stand at 88% of joint registries.12 16 Nonetheless, the monetary and health implications of choosing between a PFR and TKR are not well understood. The purpose of this study was to compare the cost-effectiveness of PFR and TKR across various age groups.
Methods
Markov models to determine the cost-effectiveness and quality-adjusted life years (QALYs) of patients undergoing PFR or TKR surgery (figure 1) were constructed using risk of revision and mortality as potential states. Patients who underwent primary arthroplasty (PFR or TKR) were modelled with a specified annual risk of revision. Additionally, the Markov model incorporated age-related mortality risks, the probability of revision and patient-reported outcome measures (PROMs) (Oxford Knee Score and EQ5D-3L). To estimate the parameters, IPTW methods were used to make both treatment groups comparable and detailed in the Data section.
Figure 1. Markov model outline. The decision analytic model provides the framework for the analysis. PFR, patellofemoral joint replacement; TKR, total knee replacement.
After the first year, a recurring Markov cycle was applied each year over a 60-year time horizon to simulate mortality. The age for the cohort entering the model varied from 40 to 90. The time horizon varied according to the gender and age-specific mortality rate of UK life tables. The model contained costs associated with each procedure.
Data
The study population for estimation of revision included 900 PFRs and 287 777 TKRs from a prior study using NJR data linked to Hospital Episode Statistics and patient-reported outcomes data (PROMs) between 2009 and 2021.17 In this study, PROMs submitted between 6 and 18 months were used since the majority of improvement occurs in the first 6 months after joint replacement surgery, with only minor improvement thereafter.18
Patients who underwent a TKR or PFR were balanced using the following characteristics: gender, age, American Society of Anaesthesiologists (ASA) physical status classification system, indices of social deprivation, regional anaesthesia, provider (private or national health service), operating surgeon level (consultant grade vs non-consultant grade), Charlson Comorbidity Index and preoperative score (EQ5D-3L). This made sure that both groups were comparable. Balancing was conducted using inverse proportional treatment weighting (IPTW) methods (online supplemental appendix 1).
Population characteristics
The mean age of the population was 60.0 (SD 10.42), the majority were female and had an ASA-II. An overview of the demographic characteristics using propensity scores with inverse propensity treatment methods can be found in figure 2 (exact values can be found in online supplemental appendix table 1). The study was conducted using pseudo-anonymised data from the national clinical registry.
Figure 2. Standardised mean differences for covariates before and after inverse probability of treatment weighting, demonstrating the improved balance achieved between treatment groups post-weighting. ASA, American Society of Anaesthesiologists; CCI, Charlson Comorbidity Index.
Outcomes: mortality, revision and utility values
Table 1 outlines the parameters used in the analysis, along with their corresponding estimation methods, assumed probability distributions and sources of data. Annual all-cause mortality was obtained directly from UK national statistics.19 Postoperative 30-day mortality rates and risk of revision for the index procedure (PFR, TKR) were calculated from the current dataset. A detailed overview and values are provided in online supplemental appendix tables 1 and 2.
Table 1. Parameters used in the analysis.
| Category | Type of parameter | Uncertainty distribution | Method | Source |
|---|---|---|---|---|
| 30-day operative mortality | ||||
| omrPPFR Primary PFR |
Fixed value | Beta | Propensity score: inverse treatment weighting methods | National Joint Registry Data—Hospital Episode Statistics |
| omrRPFR Revision PFR |
Fixed value | Beta | Propensity score: inverse treatment weighting methods | National Joint Registry Data—Hospital Episode Statistics |
| omrPTKR Primary TKR |
Fixed value | Beta | Propensity score: inverse treatment weighting methods | National Joint Registry Data—Hospital Episode Statistics |
| omrRTKR Revision TKR |
Fixed value | Beta | Propensity score: inverse treatment weighting methods | National Joint Registry Data—Hospital Episode Statistics |
| Revision risks | ||||
| Revision risk PFR | Varied by gender | Beta | Propensity score: inverse treatment weighting methods | National Joint Registry Data—Hospital Episode Statistics |
| Revision risk TKR | Varied by gender | Beta | Propensity score: inverse treatment weighting methods | National Joint Registry Data—Hospital Episode Statistics |
| Re-revision risk of TKR | Fixed value | Beta | NJR data survival analysis | National Joint Registry 20th Annual Report |
| Utility value—EQ5D-3L | ||||
| PFR | Fixed value | Beta | Propensity score: inverse treatment weighting methods | National Joint Registry Data—patient reported outcomes dataset |
| TKR | Fixed value | Beta | Propensity score: inverse treatment weighting methods | National Joint Registry Data—patient reported outcomes dataset |
| Revision TKR | Fixed value | Beta | Assumed based on literature | Literature34(36) |
| Revision PFR | Fixed value | Beta | Propensity score: inverse treatment weighting methods | National Joint Registry Data—patient reported outcomes dataset |
PFR, patellofemoral joint replacement; TKR, total knee replacement.
Utility values were assigned to each transition state in the model. Utilities were derived from EQ-5D-3L PROMs collected between 6 and 18 months postoperatively in the NJR dataset,17 the UK EQ-5D-3L value set, produce values anchored between 0 (death) and 1 (perfect health).
The utility value for primary PFR and primary TKR was derived directly from the PROMs dataset.20 As revision of PFR is typically performed as conversion to a primary TKR, the utility value for revised PFR was assumed to be equivalent to that of primary TKR (0.78). Utility values for revised TKR were not available in the dataset and were therefore obtained from previously published literature.21 The utility values used in the model are presented in online supplemental appendix table 3. Utility values were assumed to remain constant within each health state for the duration of the model cycle. Utility values were used to estimate QALYs, calculated by multiplying the utility associated with a health state by the time spent in that state.
Cost estimates
Costs for each procedure were obtained from the HRG4+ 2024/2025 Local Payment Grouper and billing codes from the 2023/2025 NHS Payment Scheme (online supplemental appendix table 4).22 23 The implant cost of each prosthesis brand was taken from the average prices paid by a major hospital for North West London in 2023 (including all components and instrumentation) to reflect discounts negotiated on list prices: £1835 for TKR Smith & Nephew Journey, £1101 for PFR Smith & Nephew Journey and £9015 Attune TKR revision.
Cost-effective analysis
The cost-effectiveness of one treatment compared with the alternative was measured using an incremental cost-effectiveness ratio (ICER), which represents the incremental cost per QALY gained. The ICER is estimated by dividing the difference in costs between two comparators by the difference in QALYs between the same two comparators (Cost1−Cost2/QALY1−QALY2). A treatment was considered to be cost-effective if the ICER fell under a willingness to pay threshold of £12 936 which is endorsed by the National Institute for Health and Care Excellence.24 It is important to note that willingness to pay thresholds vary by country.25 The probability of either PFR or TKR being cost-effective was calculated for a range of cost-effectiveness thresholds and the cost-effectiveness acceptability curves were drawn for each patient subgroup (age and gender). Costs and QALYs were discounted at an annual rate of 3.5% as recommended by the EUnetHTA.26 A half-cycle correction was not applied in the Markov model.
The cost-effectiveness model was constructed in Microsoft Excel 2024 V.16.89 (Microsoft Corporation, Redmond, Washington, USA). The Markov model (figure 1, table 2) was simulated in Excel.
Table 2. Definitions of health states used in the Markov model.
| OmrPPFR | Operative 30-day mortality rate following primary patellofemoral arthroplasty |
|---|---|
| rrPFR | Relative revision risk following primary patellofemoral arthroplasty |
| Mr(age) | Yearly transition probabilities of death by age |
| OmrTKR | Operative 30-day mortality total knee replacement |
| rrTKR | Revision risk following primary total knee replacement |
| OmrRTKR | Operative 30-day mortality following revision total knee replacement |
| omrRTKR | Operative 30-day mortality revision total knee replacement |
| Re-revision risk TKR | Revision risk following revision total knee replacement |
PFR, patellofemoral joint replacement; TKR, total knee replacement.
Simulation
A probabilistic sensitivity analysis was performed using 1000 Monte Carlo microsimulations over 60 annual cycles. The simulated cohort entered the model at the mean age observed in the dataset and aged by 1 year during each cycle. Age-specific mortality probabilities were applied using UK life tables. Analyses were conducted separately for males and females to account for sex-specific mortality rates and revision risks. Health state utility values were derived from EQ-5D-3L PROMs data and were assumed to remain constant within each health state across cycles; utilities were therefore not adjusted according to age.
One-way sensitivity analysis
Deterministic one-way sensitivity analyses were performed by varying key model parameters individually across plausible ranges (±1 SD) while holding all other parameters constant (online supplemental appendix table 6). Analyses were conducted for all age- and sex-specific cohorts. The impact of parameter variation on ICERs was assessed and presented using tornado plots to identify the primary drivers of model uncertainty.
Patient and public involvement
A patient and public involvement meeting took place on 28 October 2020, where patients were engaged by social media to consult the authors on which patient outcomes were most relevant to them as patients. Patients expressed a preference for being informed of all available surgical options and the associated risks and benefits.
Importantly, patients emphasised a preference for smaller, less invasive procedures where appropriate, particularly if these offered satisfactory outcomes and a lower risk profile compared with more extensive surgery. From a health-economic perspective, this preference aligns with the importance of evaluating whether less invasive procedures can provide comparable clinical outcomes while potentially reducing the burden of surgery, recovery time and healthcare resource utilisation.
Patients were not involved in advising on study methodology or interpretation of results. However, they were subsequently informed of the study findings. Patients were not involved in dissemination of the results.
Results
PFR demonstrates comparable cost-effectiveness to TKR in younger patients, while becoming more cost-effective in older patients. In younger patients, the lower QALYs associated with PFR are offset by its reduced costs. For older patients, the difference in QALYs between PFR and TKR narrows with age and eventually shifts to favour PFR, as older individuals are less likely to undergo revision surgery to a TKR (figure 3).
Figure 3. Cost and QALY graphs for PFR and TKR procedures for female patient. PFR, patellofemoral joint replacement; QALY, quality-adjusted life year; TKR, total knee replacement.
The incremental cost, incremental QALY and total lifetime costs, health utility states (QALYs) as a function of age are presented in online supplemental appendix table 5). PFR is consistently less costly than TKR across all age groups. However, in patients under the age of 75, PFR is associated with lower QALYs, resulting in a trade-off between reduced cost and decreased health benefit. In contrast, for patients aged 75 years and older, PFR not only remains less expensive but also yields higher QALYs compared with TKR, indicating clear dominance in terms of both cost and effectiveness. Consequently, in this older cohort, PFR is the preferred option, so further cost-effectiveness analysis is not required. The data presented in figure 3 pertain to female patients; comparable findings for male patients are demonstrated in the corresponding graph in theonline supplemental appendix 1.
In figure 4, we move to cost-effectiveness. The incremental QALY represents the additional health benefit gained from PFR compared with TKR, measured in QALYs. The incremental QALYs in figure 4 have been converted to monetary terms using £12 936 per QALY, PFR is considered cost-effective whenever the incremental QALY value exceeds the incremental cost.
Figure 4. Incremental cost and quality-adjusted life years (QALYs) for female and male patients (patellofemoral joint replacement as compared with total knee replacement).
Figure 5 shows that the monetary value of QALYs gained from PFR over TKR increases significantly with age for both genders. There is a small difference in utility values between PFR and TKR (0.75 vs 0.78, patient aged 40), with PFR generally yielding lower QALYs. However, in older patients, this lower utility value is offset by a shorter life expectancy, which reduces the overall risk of requiring a revision procedure. If revision is needed, converting a PFR to a TKR typically results in higher utility value (0.78) than a revised TKR (0.55). This means that patients who start with a PFR and later convert to a TKR avoid the significantly lower utility values associated with revised TKRs, which may offset the QALY disadvantage seen initially with PFR.
Figure 5. Age- and gender-specific incremental cost-effectiveness of PFR compared with TKR. PFR, patellofemoral joint replacement; QALY, quality-adjusted life year; TKR, total knee replacement.
At younger ages (40–50 years), the incremental QALY gain for PFR is slightly negative compared with TKR but improves steadily with age. PFR remains consistently less costly than TKR, with initial savings of approximately £4000, although this difference decreases slightly with age.
In younger patients, this represents a trade-off (lower cost but slightly worse outcomes), and cost-effectiveness depends on the willingness-to-pay threshold. However, with increasing age, the QALY difference becomes positive, and PFR becomes both more effective and less costly. From approximately 75 years onward, PFR is dominant over TKR.
Figure 5 presents the net monetary benefit of PFR compared with TKR, using a £12 936 per QALY threshold. Values greater than zero favour PFR. Between ages 40 and 70, results are close to zero, indicating near indifference. Beyond age 75, PFR demonstrates clear cost-effectiveness and dominance.
Regarding gender differences, males experience greater QALY gains from PFR than females. However, PFR is more cost-effective in females, likely reflecting differences in costs and revision profiles. Overall, the cost-effectiveness of PFR improves with age, making it the preferred strategy in older patients (figures 6 and 7).
Figure 6. Incremental cost-effectiveness results across representative age groups relative to the national willingness-to-pay threshold.
Figure 7. Cost-effectiveness scatter plots for different age groups. QALY, quality-adjusted life year.
Sensitivity analysis
One-way sensitivity analysis (figure 8, online supplemental appendix table 6) demonstrated that model results were most sensitive to the utility associated with successful patellofemoral replacement. Variation in this parameter produced the largest changes in ICER across all cohorts, with lower values reducing the cost-effectiveness and higher values increasing the relative cost-effectiveness of PFR. Sensitivity to revision utilities was more pronounced in younger patients, reflecting their greater lifetime risk of revision. In contrast, variation in discount rate had minimal impact across all subgroups. Overall, the analysis indicates that the relative cost-effectiveness of PFR compared with TKR is highly dependent on assumptions regarding postoperative utility, although there is a trend towards greater cost-effectiveness in older patients.
Figure 8. One-way sensitivity (tornado) plots for PFR and TKR, illustrating the impact of key model parameters on incremental cost-effectiveness outcomes. ICER, incremental cost-effectiveness ratio; PFR, patellofemoral joint replacement; QALY, quality-adjusted life year; TKR, total knee replacement.
Discussion
This cost-effectiveness analysis suggests that PFR may be more cost-effective than TKR in both males and females, with this trend becoming more apparent from the age of 60 onwards. The similarity in QALYs is likely driven by comparable PROMs (EQD5-3L) between the two procedures. When considered alongside lower costs, this results in a tendency towards improved cost-effectiveness of PFR, particularly in older cohorts. However, these findings are sensitive to assumptions regarding postoperative utility (EQ5D-3L), and the relative cost-effectiveness of PFR compared with TKR is not robust across all parameter ranges.
Revision surgery represents an important contributor to overall costs within the model. While PFR is associated with a higher risk of revision compared with TKR, revision procedures following TKR are typically more expensive than a revision of a PFR to TKR.20 27 As a result, the economic impact of revision differs between the two treatments, with PFR incurring more frequent but less costly revisions and TKR incurring fewer but more expensive revision procedures.
When considering revision in younger patients, the higher revision risk associated with PFR may be less critical than it appears. If these patients were to undergo a TKR instead, they would likely require revision at a relatively young age.28 TKR revision is not only more costly but also a more technically challenging procedure, which is associated with bone loss and poor outcomes.9 29 Unlike a PFR in which a revision has been described as a primary TKR.11 Therefore, for younger patients, the lower costs of PFR are likely to be offset by the higher risk of revision because they are likely to live long enough to eventually need a revision, making the two alternatives comparable in terms of cost-effectiveness. For older patients, instead, the shorter residual life expectancy reduces the overall probability that the patient reaches an age when a revision is needed, making PFR substantially more cost effective for older patients.
With an increasing emphasis on cost-effective healthcare, it is crucial to evaluate the financial implications of each procedure.30 In certain age groups, for patients with isolated PFJ OA, PFR represents a viable and economically favourable treatment option. Sensitivity analysis indicated that the model was most responsive to the utility associated with successful PFR. Consequently, technological or surgical improvements that enhance postoperative patient-reported outcomes could further improve the cost-effectiveness profile of PFR.
Fredborg et al conducted a well-designed randomised controlled trial with data from 100 patients, using a PROM, EQ5D-3L representative of the Danish population.29 Although PFR implants are more expensive in Denmark than in the UK, the analysis still found that PFR was more cost-effective than TKR. This conclusion was driven by higher postoperative utility scores in the early period (a difference of 0.06), although this difference diminished over time.31
In contrast, the cost-effectiveness analysis conducted by Chawla et al is not directly comparable.30 32 This American study relied on revision rates from the UK NJR annual reports, complication rates from various case series publications, and utility measures derived from other American studies. The utility scores employed utility conversions that were initially validated using UK population data, which adds complexity to the applicability of their findings.33
Serino et al adopted a different methodological approach, using the costs of complications rather than patient-reported outcomes as the primary drivers of their cost-effectiveness model.32 Despite these methodological differences, all studies ultimately concluded that PFR is more cost-effective than TKR.
This study’s strengths include using a large dataset, incorporating patient-reported outcomes from over 900 individuals in each treatment group. Additionally, it uses real-world evidence to assess both the costs and health outcomes associated with PFR and TKR. As with any observational study, limitations exist, particularly the potential for confounding due to selection bias. For instance, surgical decision-making may be influenced by individual surgeon preferences, such as a greater inclination to perform TKR over PFR. Although propensity score matching was employed to adjust for known confounders, unmeasured factors may still introduce bias. One such limitation is the absence of linkage between registry data and radiographic imaging, which could offer insights into patterns of osteoarthritis that would help confirm the appropriateness of surgical indications.
One could argue that, as clinicians, we should prioritise treatments that offer the greatest patient benefits. However, large patient benefits should not be the sole criterion guiding decision-making. Sandman et al discuss that in a budget-constrained healthcare system, fair and effective resource allocation requires a more balanced approach, where a large patient benefit is not mandatory.33
Conclusion
PFR may represent a cost-saving alternative to TKR in patients with isolated patellofemoral osteoarthritis, with a trend towards greater cost-effectiveness in older patients. However, these findings are highly sensitive to assumptions regarding postoperative utility (EQ5D-3L). Improvements in patient-reported outcomes may enhance the relative cost-effectiveness of PFR. Further high-quality data are required to better define its economic value and inform clinical decision-making.
Supplementary material
Footnotes
Funding: This work was supported by OR UK (Grant number:551).
Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2026-116372).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Not applicable.
Ethics approval: This study involves human participants. The study was conducted using pseudo-anonymised data from the national clinical registry. The Health Research Authority guidance confirmed that ethical approval was not required. Participants gave informed consent to participate in the study before taking part.
Patient and public involvement: Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
Data availability statement
Data are available upon reasonable request.
References
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