Projected increase in total knee arthroplasty in the United States – an alternative projection model

Projected increase in total knee arthroplasty in the United States – an alternative projection model

Accepted Manuscript Projected Increase in Total Knee Arthroplasty in the United States - an Alternative Projection Model Maria C.S. Inacio, MS, PhD, E...

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Accepted Manuscript Projected Increase in Total Knee Arthroplasty in the United States - an Alternative Projection Model Maria C.S. Inacio, MS, PhD, Elizabeth W. Paxton, MA, Stephen E. Graves, MBBS, PhD, Robert S. Namba, MD, Szilard Nemes, PhD PII:

S1063-4584(17)31130-5

DOI:

10.1016/j.joca.2017.07.022

Reference:

YJOCA 4061

To appear in:

Osteoarthritis and Cartilage

Received Date: 15 November 2016 Revised Date:

30 June 2017

Accepted Date: 31 July 2017

Please cite this article as: Inacio MCS, Paxton EW, Graves SE, Namba RS, Nemes S, Projected Increase in Total Knee Arthroplasty in the United States - an Alternative Projection Model, Osteoarthritis and Cartilage (2017), doi: 10.1016/j.joca.2017.07.022. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Projected Increase in Total Knee Arthroplasty in the United States - an Alternative

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Projection Model

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Maria C. S. Inacio, MS, PhD1 Elizabeth W. Paxton, MA,2 Stephen E. Graves, MBBS, PhD,3

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Robert S. Namba, MD, 4 Szilard Nemes, PhD5

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1. Maria C.S. Inacio (corresponding author)

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Quality Use of Medicines and Pharmacy Research Centre

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Medicine and Device Surveillance Centre of Research Excellence

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Sansom Institute, School of Pharmacy and Medical Sciences

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GPO Box 2471, Adelaide 5001

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South Australia, Australia

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[email protected]

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Phone: +61 8302 133 33

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2. Surgical Outcomes and Analysis Department, Kaiser Permanente

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San Diego, CA, USA

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Email: [email protected]

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University of South Australia

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3. Australian Orthopaedic Association, National Total Joint Replacement Registry Adelaide, SA, Australia Email: [email protected]

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4. Department of Orthopedic Surgery, Kaiser Permanente, Orange County

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Irvine, CA, USA

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Email: [email protected]

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5. Swedish Hip Arthroplasty Register

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Gothenburg, Sweden

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Email: [email protected]

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ACCEPTED MANUSCRIPT Abstract

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Objective: The purpose of our study was to estimate the future incidence rate (IR) and

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volume of primary total knee arthroplasty (TKA) in the United States from 2015 to 2050

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using a conservative projection model that assumes a maximum IR of procedures.

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Furthermore, our study compared these projections to a model assuming exponential

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growth, as done in previous studies, for illustrative purposes.

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Methods: A population based epidemiological study was conducted using data from US

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National Inpatient Sample (NIS) and Census Bureau. Primary TKA procedures performed

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between 1993 and 2012 were identified. The IR, 95% confidence intervals (CI), or prediction

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intervals (PI) of TKA per 100,000 US citizens over the age of 40 years were calculated. The

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estimated IR was used as the outcome of a regression modelling with a logistic regression

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(i.e. conservative model) and Poisson regression equation (i.e. exponential growth model).

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Results: Logistic regression modelling suggests the IR of TKA is expected to increase 69% by

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2050 compared to 2012, from 429 (95%CI 374-453) procedures/100,000 in 2012 to 725

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(95%PI 121-1041) in 2050. This translates into a 143% projected increase in TKA volume.

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Using the Poisson model, the IR in 2050 was projected to increase 565%, to 2854 (95%CI

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2278-4004) procedures/100,000 IR, which is an 855% projected increase in volume

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compared to 2012.

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Conclusions: Even after using a conservative projection approach, the number of TKAs in the

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US, which already has the highest incidence rate of knee arthroplasty in the world, is

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expected to increase 143% by 2050.

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Keywords: total knee arthroplasty, projections, epidemiology, incidence rates

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Introduction The United States has the highest incidence rate of knee arthroplasty worldwide, with 235 procedures/100,000 habitants.1 In 2012 alone, the number of knee arthroplasties

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performed in the United States was over 700,000, which was 9% of the 8 million non-

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maternal and non-neonatal inpatient hospital stays where a procedures was performed.2

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Because of the high incidence of knee arthroplasty and its historical increase,3-7

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understanding the future healthcare demands of these procedures is important. Reliable

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projections of future surgery demand can assist healthcare providers, leaders, and services

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in preparing, through capacity building, staff training, financial commitment, and other

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important resource building strategies.

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Three separate projections studies of future demand for knee arthroplasty in the US have been published.3-5 In 2007, Kurtz et al., estimated that from 2005 to 2030 a 673%

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increase in the number of procedures would be observed, with an expected volume of 3.5

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million procedures being performed yearly by 2030.3 In 2014, Kurtz et al. revaluated their

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original models and new estimates were proposed, which were slightly lower for 2020,

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however, no figures could be extrapolated from their published graphs.4 A third study, by

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Bashnskaya et al. in 2012, proposed that a similar increase in volume as proposed by Kurtz et

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al. 3 was expected for 2030, and projected that 3 million procedures would occur annually

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by then.5 While these three studies have arrived at similarly high estimates of future

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demand they have used different modelling approaches. The first study used a Poisson

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regression model, which assumed an exponential growth in the incidence of knee

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arthroplasty. The second and third studies used linear regression models, which also

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assumed a continuous increase in demand. 4,5 Both models make projections that are not

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ACCEPTED MANUSCRIPT biologically plausible, or consistent with what we know about what drives the incidence of

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these procedures. To illustrate this point, the estimated prevalence of knee osteoarthritis

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according to the Global Burden of Disease 2010 study puts the global age-standardised

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prevalence of symptomatic radiographically confirmed knee osteoarthritis around 3.8%,8

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while the prevalence of knee osteoarthritis is estimated to be 10-13% among Americans.8,9

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This relatively low number of people with osteoarthritis, the already high incidence of knee

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arthroplasty in the US, and the fact that it is estimated that only about 50% of those with

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symptomatic osteoarthrtitis have surgery in the United States10 suggest that there will be a

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finite number of future patients undergoing surgery- and not a continuous projected growth

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as proposed by other authors.

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There is no way to test which methodology is best suited for joint arthroplasty

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projections, but biological plausibility and constraints to the healthcare system have

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prompted researchers to explore alternative projection models for this patient population.11-

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when overestimated and lack of preparedness when underestimated. Evaluating alternative

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projection models will increase our understanding of the modelling limitations and

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eventually reproducibility of findings will increase our confidence in projected estimates. In

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this study we used the more conservative projection model proposed by Nemes et al. in

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Sweden to estimate the future demand of knee arthroplasty in the US11,12 because there is

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an upper limit to total knee arthroplasty (TKA) incidence that prior projections have not

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considered. Failure of considering this upper limit, or asymptote, will ultimately lead to

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biased projected rates.14 The model is a logistic model, which has more parameters than the

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models used by the other US projection studies. The parameter of most interest in this

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Furthermore, inaccurate growth projection can lead to wasted or misplaced resources

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ACCEPTED MANUSCRIPT model is the asymptote, which in this case is the estimated maximum incidence of knee

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arthroplasty. This parameter has units that correspond to the outcome. The existence of

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such a maximum incidence is a strong assumption and an untestable one; however,

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employing such assumption is unlikely to attain numbers high enough to sustain the yearly

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growth in knee arthroplasty proposed by the models in the current published projection

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studies.

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The purpose of our study was to estimate the future incidence rate and volume of

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primary TKA in the United States from 2015 to 2050 using an alternative projection model

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that assumes a maximum incidence rate. Furthermore, our study compared these

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projections to a model assuming exponential growth for illustrative purposes.

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Methods A population based epidemiological study was conducted using data from US

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National (previously Nationwide) Inpatient Sample (NIS)15 and US Census Bureau.16 The NIS

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was developed by the Healthcare Cost and Utilisation Project (HCUP), which is sponsored by

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the Agency for Healthcare Research and Quality (AHQR). This ~20% stratified sample of

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patients who were discharged from 1000 hospital in 44 states in the US has been shown to

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be 95% representative of the US population.15

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Primary TKA procedures performed between 1993 and 2012 (most recent year

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available) were identified in the NIS using International Classification of Disease, 9th revision,

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Clinical Modification (ICD-9-CM) code 81.54. The new trend weights released with the 2012

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NIS data were used to estimate procedure yearly volumes.17

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The US Census historical population estimates for 1993-2012 were obtained from the

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intercensal estimates of the resident population by age18 and projected population

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estimates for 2015 to 2050 were obtained from the projections of the population for the

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US.19

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Historical changes in the total number of TKA per year were modelled with

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piecewise-linear regression splines. Piecewise-linear regression splines fit multiple

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regression lines to the data connected by a change-point. Model fitting and change-point

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estimation followed the algorithms outlined by Mueggo.20 The number of change points

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were selected by minimizing the Akaike Information Criterion, with the restriction that

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change-points cannot be placed at the extremes of the data. The incidence rate and 95%

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confidence intervals (CI) or prediction intervals (PI) of TKA per 100,000 US citizens over the 7

ACCEPTED MANUSCRIPT age of 40 years were calculated. Historical data was summarized as incidence rates and

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associated 95%CI, while projections were presented with 95%PI. The incidence in the

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population 40 years or older was chosen because the number of patients with joint

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arthroplasty younger than 40 is minimal (0.7% of TKAs). The estimated incidence rate was

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used as the outcome of a regression modelling with logistic regression and Poisson

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regression equation. Logistic regression is a conservative projection model that assumes a

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maximum incidence level exists and changes in estimates grow exponentially from the

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beginning to the half-way point of the maximum incidence and then decrease until

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maximum incidence is reached. This model is based on the logistic growth model and

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assumes a S-shape growth curve. The model parameters have clear meanings. According to

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this model the incidence in a time point is directly dependent on the incidence a time-unit

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before and can be modelled as

dy ' y  = β y 1 −  dt A 

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where y observed incidence, A the asymptote that has units equal to incidence and β the growth rate with units equal to t (years in our case). As one can see if the observed

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incidence is far from the asymptote the growth is accentuated. However, as the observed

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incidence y approaches the asymptote A the growth slows down. The model parameters are

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estimated using its integrated form and routine optimization methods. We used the

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following re-parametrised form

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A 1 + e(γ −t )/ξ

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Where the parameters of interest are A the asymptote that has units equal to

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incidence and γ a numeric parameter representing the year value at the inflection point of

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the curve. 8

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By comparison, Poisson regression assumes exponential growth through the whole time period. We used grid-search to estimate the parameters of the logistic regression

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equation. Grid search is an exploratory Monte Carlo optimization method.21,22 Parameters

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of the Poisson regression were estimated using maximum likelihood method. 95%PIs were

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constructed with Monte Carlo simulation for the logistic regression and with bootstrapping

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for Poisson regression. 95%PIs for incidence rates were calculated with the Wilson method.23

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All analyses were conducted using R 3.3.1.

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Review Board was not required.

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This study uses publicly available de-identified data so review by an Institutional

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Results Between 1993 and 2012 a total of 7.8 million primary TKAs were performed in US

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and the number of surgeries increased by 224% (Figure 1, Appendix A). Historically, the

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increase in yearly surgical volume was slower in the beginning of our study period then the

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pace picked-up after year 2000 (95 % CI 1997-2002), with the average yearly increase up to

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1999 of 10,520 (95% CI: 1490-19,540) cases/year. After 2000 the increase in yearly volume

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accelerated to average of 32,730 (95% CI: 29,190 -36,270) procedures/year. The model had

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good fit to the data, calendar year explaining 95.7 % of the observed variation in TKA

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incidence.

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Logistic regression modelling suggests that the upper incidence of TKA/100,000

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people over the age of 40 in the US is 746 (95%PI 117-1375). Using this model, the incidence

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rate of TKA is expected to increase 69% by 2050 compared to 2012, from 429 (95%CI 374-

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453) procedures/100,000 people over the age of 40 in 2012 to 725 (95%PI 121-1041) in 2050

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(Figure 2). This change in incidence rate translates into a 143% projected increase in

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procedure volume between 2012 and 2050 (Figure 3). The period between 1987- 2028

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coincides with the fastest growth in yearly volume. This increase continuously accelerated

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until 2007 after that growth rate while still increasing but the pace slows down (Appendix

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B).

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Poisson regression modelling forecasted a greater increase of the incidence rate of TKAs

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(Figure 2) than the logistic model. The incidence rate in 2050 using this model was 2854

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(95%CI 2278-4004) procedures/100,000 people over the age of 40, which is a 565% increase

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in incidence rate (Figure 2) and 855% projected increase in the volume (Figure 4) of 10

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be 5% (95%CI: 4.49-5.44) more TKA surgeries than in the previous year (Appendix B).

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Discussion According to our projection model, a 143% increase in the number of TKAs

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performed in the US between 2012 and 2050 is expected and we project that by 2050 the

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number of TKAs performed annually will reach 1.5 million cases/year. The rate of growth of

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these procedures started to slow down in 2007 and after 2028 it will decrease even more

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substantially.

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For comparison with previous models, projections for 2020 from our logistic model

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suggests that 882,000 procedures will be performed annually (Appendix A). For the same

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year Bashinskaya et al. forecasted 1.7 million yearly procedures, 5 Kurtz et al. 1.5 million in

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their original projections,3 and around 1.4 million in their 2014 update.4 Additionally in our

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Poisson regression, which is presented for illustrative purposes in this study, 1 million cases

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were projected (Appendix A). The results of the previous projection analyses are much

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higher compared to ours. Previous studies used linear or Poisson regression models. 3-5 The

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different model used is the main reason for the differences in projections proposed in this

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study and the other studies, but we highlight other notable differences among these studies

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from ours. Bashinskaya et al. stratified modelling by age groups while Kurtz et al. used a

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wider range of predictors, including age, gender, ethnicity, census region and calendar year

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in one study, and added economic parameters in the other study. 3-5 Kurtz et al. in their

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later publication4 followed the footsteps of Bashinskaya et al.5 and separated predictions for

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each age, gender, ethnicity and census region and combined the projections. This resulted in

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somewhat lower projected incidence, however, still resulted in exponential like growth

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curves (Kurtz et al. figure 4).4 Generally, linear regression commands a constant growth thus

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the exponential like growth curve of the aforementioned paper is likely to be the result of

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ACCEPTED MANUSCRIPT the weighting attributed to the different stratum. Given the splines used by Bashinskaya et

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al. and the weighting strategy used by Kurtz et al. one cannot draw far reaching conclusions

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of the appropriateness of the models. 4,5 However, because the previous studies used

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models that assume ever increasing constant growth they may not reflect biological

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plausibility, or consistency with what we know about the disease- that the need for the

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procedures are limited by the prevalence of the disease and the subset with severe disease

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requiring TKA. Other differences in the Poisson estimates between our study and previous

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studies could be due to our inclusion of more years of historical annual incidence from the

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NIS in our projections, the use of recently updated trend weights from NIS in our volume

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calculations, and our restriction of the population to those 40 years and older. This age

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restriction was chosen in an attempt to provide more realistic incidence rate estimates and

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remove the impact of a greater population increase in the younger groups to affect our

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population estimations.

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The logistic model we employed incorporates maximum incidence. So far only one prior study has compared these two regression methods. Nemes et al. projected the

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incidence and number of total hip arthroplasty (THA) in Sweden from 2013 to 2030.11 As of

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2016, there are publicly available data for 2013, 2014 and 2015 THA volume in Sweden,

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which allowed us to compare the projections with actual surgeries. Using the Poisson

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regression model in 2013 the authors projected 20,006 THAs, but only 16,348 were

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performed, similarly, in 2014 20,891 THAs were projected but only 16,562 were observed,

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and in 2015 21,816 THAs were projected and 16,617 were observed. Using an asymptotic

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regression model, closer estimates to the observed values were projected: 16,021 for 2013,

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16,318 for 2014 and 16, 595 for 2015. These numbers are slightly lower that the realized

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numbers.

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Our projections are inheritably limited by the modelling method used. The model only accounts for past and recent incidence of knee arthroplasty and projected population

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growth, and therefore it does not account for future changes in patient, surgeon, healthcare

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system, political, and other population factors. Some of these factors could directly affect

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the estimations, for example, the prevalence of symptomatic osteoarthritis, which is

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increasing nationally due to the aging and increasingly obese population9,24 Other factors

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could affect the estimations indirectly, for example healthcare policy, which will certainly

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change in the next 30 years, could change patients’ access to surgery. Also important are

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general extraneous factors like economic recessions, which occurred in the US in the 1990s

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and 2000s, which could have influenced the historical trends we observed. These factors

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could not be accounted for in our analysis due to data availability and modelling constraints

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and this likely means our projections could be underestimated. We support the conservative

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projection approach carried out in this study, however, we understand that possible

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underestimation of future volumes can contribute to a lack of preparedness and appropriate

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resource allocation. We hope that the limitations of our strategy, as in other models, are

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therefore clear. Our projections are also limited by the time period they cover, which means

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that the longer term projections can be more unreliable.

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Even after using a more conservative projection approach than previously proposed,

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the number of TKA procedures in the US, which already has the highest incidence rate of

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knee arthroplasty in the world, is expected to increase 143% by 2050. The projected increase 14

ACCEPTED MANUSCRIPT will translate into a projected yearly volume of 1.5 million cases by 2050. With the proposed

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model and all assumptions made, while the rate of demand started to slow down in 2007,

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and is expected to slow even more significantly after 2028, overall growth still continues.

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And as we modelled incidence pre 100,000 individuals older than 40 the absolute numbers

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of performed TKA will continue to increase in concordance in the aging of the population.

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These projection models can be useful in future planning and resource allocation for the

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delivery of necessary care to knee arthroplasty patients in the US.

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ACCEPTED MANUSCRIPT Acknowledgements: This work was supported by an Australian Government National Health

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and Medical Research Council (NHMRC) Centre of Research Excellence in Post-Marketing

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Surveillance of Medicines and Medical Devices grant (GNT1040938). No financial support or

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other benefits from commercial sources was received by any of the authors for the work

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reported on in the manuscript. The funders played no role in the analysis or interpretation of

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the data or in the preparation of this manuscript. The authors had full access to all of the

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data in the study.

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Authors’ contributions:

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Conception and design: MCSI, SEG, EWP, RSN, SN

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Acquisition of data: MCSI

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Analysis and interpretation of data: MCSI, SN

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Drafting and revising manuscript: MCSI, SEG, EWP, RSN, SN

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Final approval: MCSI, SEG, EWP, RSN, SN

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Role of the funding source: This work was supported by an Australian Government National

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Health and Medical Research Council (NHMRC) Centre of Research Excellence in Post-

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Marketing Surveillance of Medicines and Medical Devices grant (GNT1040938). No financial

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support or other benefits from commercial sources was received by any of the authors for

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the work reported on in the manuscript.

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Conflict of interest: None of the authors have any conflict of interest.

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growth in population size and the obesity epidemic. The Journal of bone and joint

362

surgery. American volume. 2012;94(3):201-207.

EP

364

AC C

363

TE D

360

19

ACCEPTED MANUSCRIPT Figure Legend

366

Figure 1.

367

Title: US Population and Primary Total Knee Arthroplasty Volume in Citizens Aged 40 Years

368

and Older, 1993-2012

369

Footnote: TKA=Total knee arthroplasty.

RI PT

365

370

Figure 2.

372

Title: Historical (1993-2012) and Projected (2015-2050) Incidence Rate (per 100,000) of

373

Primary Total Knee Arthroplasty Procedures in Citizens 40 Years and Older from Logistic and

374

Poisson Models

375

Footnote: TKA=total knee arthroplasty.

376

M AN U

SC

371

Figure 3.

378

Title: Historical (1993-2012) and Projected (2015-2050) Volume and 95% Prediction Intervals

379

of Primary Total Knee Arthroplasty Procedures in Citizens 40 Years and Older from Logistic

380

Model

381

Footnote: N=Number of total knee arthroplasty procedures.

EP

AC C

382

TE D

377

383

Figure 4.

384

Title: Historical (1993-2012) and Projected (2015-2050) Volume and 95% Prediction Intervals

385

of Primary Total Knee Arthroplasty Procedures in Citizens 40 Years and Older from Poisson

386

Model

387

Footnote: N=Number of total knee arthroplasty procedures.

388 20

ACCEPTED MANUSCRIPT Appendix A. US Population, Primary Total Knee Arthroplasty Volume, and Annual Crude Incidence Rate per 100,000 Citizens Aged 40 Years or Older, 1993-2012 Years

US

US Population

Volume of

Population

>40 years old

TKA, N

IR of TKA in US Population >40 years old (95%CI)

259,918,588

101,979,186

194,914

1994

263,125,821

104,326,960

208,440

1995

266,278,393

106,788,713

217,725

1996

269,394,284

109,298,512

241,687

1997

272,646,925

112,003,174

252,979

226 (197-256)

1998

275,854,104

114,684,128

245,763

214 (187-244)

1999

279,040,168

117,347,814

256,428

219 (190-248)

2000

282,162,411

120,015,599

274,463

229 (192-251)

2001

284,968,955

122,597,688

305,572

249 (211-272)

2002

287,625,193

125,107,164

339,681

272 (232-295)

2003

290,107,933

127,582,475

369,985

290 (249-314)

2004

292,805,298

130,064,179

419,774

323 (278-347)

2005

295,516,599

132,494,084

483,067

365 (317-390)

298,379,912

134,682,947

482,689

358 (310-383)

301,231,207

136,726,423

533,602

390 (339-415)

200 (173-228) 204 (176-232) 221 (193-252)

SC

M AN U

TE D

AC C

2007

EP

2006

191 (165-220)

RI PT

1993

2008

304,093,966

138,770,154

592,323

427 (373-452)

2009

306,771,529

140,875,878

597,541

424 (370-449)

2010

309,349,689

143,116,396

632,862

442 (386-467)

2011

311,582,564

145,220,219

618,604

426 (371-450)

2012

313,873,685

147,025,546

631,214

429 (374-453)

TKA=Total knee arthroplasty. IR=Incidence rate. CI=Confidence interval.

ACCEPTED MANUSCRIPT Appendix B. Projected Annual Incidence Rate per 100,000 Citizens Aged 40 Years or Older and Volumes, 2015-2050 Projected TKA IR (95%

Projected US

Approach

PI)

Population >40 Years Old

in TKA Volume

152,041,000

733,021 (178,854-760,519)

2020

548 (117-581)

160,871,000

882,034 (187,892-934,370)

20.3

2025

603 (115-661)

170,446,000

1,027,494 (196,487-1,127,105)

16.5

2030

645 (117-741)

180,381,000

1,163,697 (211,391-1,336,413)

13.3

2035

676 (120-819)

2040

699 (118-896)

2045

714 (118-970)

2050

725 (121-1041)

2015

522 (471-588)

152,041,000

794,211 (716,075-894,001)

2020

666 (591-766)

160,871,000

1,071,061 (950,707-1,232,312)

34.9

2025

849 (747-1011)

170,446,000

1,446,387 (1,273,189-1,723,209)

35.0

1082 (940-1331)

180,381,000

1,950,967 (1,695,536-2,400,916)

34.9

2030

M AN U

SC

482 (118-500)

190,195,000

1,286,531 (228,050-1,557,975)

10.6

198,034,000

1,383,809 (234,512-1,774,031)

7.6

204,851,000

1,463,313 (242,484-1,987,381)

5.7

211,259,000

1,531,566 (254,622-2,198,785)

4.7

TE D

EP

Poisson

% Change

2015

AC C

Logistic

Projected TKA Volume, N (95%PI)

RI PT

Modelling Year

2035

1379 (1175-1748)

190,195,000

2,621,920 (2,234,791-3,324,704)

34.4

2040

1757 (1467-2307)

198,034,000

3,479,536 (2,905,109-4,568,941)

32.7

2045

2239 (1825-3034)

204,851,000

4,5875,52 (3,738,428-6,215,640)

31.8

2050

2854 (2278-4004)

211,259,000

6,030,029 (4,812,322-8,459,655)

31.4

AC C

EP

TE D

M AN U

SC

RI PT

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EP

TE D

M AN U

SC

RI PT

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EP

TE D

M AN U

SC

RI PT

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