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Objective: We aimed to describe the natural history leading to end-stage knee osteoarthritis (esKOA), focusing on knee symptoms, radiographic severity, and the presence of limited mobility or instability., Methods: We performed knee-based analyses of Osteoarthritis Initiative data from 7691 knees (4165 participants). We used a validated definition of esKOA that relied on meeting one of two criteria: (1) severe radiographic knee osteoarthritis (Kellgren-Lawrence [KL] grade=4) with moderate-to-intense pain (Likert WOMAC pain+function>11/88) or (2) KL grade<4 with intense or severe pain (WOMAC pain+function>22) and limited mobility (flexion contracture≥5°) or instability (based on a varus and valgus stress test). We also introduced an alternate definition of esKOA that relied on meeting one of two criteria that omitted physical exam findings:(1) severe radiographic knee osteoarthritis (KL grade=4) with at least moderate symptoms or (2) KL grade=2 or 3 with intense or severe symptoms and persistent knee pain (frequent knee pain during three or more months in the past year). We used descriptive statistics to explore the frequency of components of esKOA at the index visit when they had incident esKOA, at the annual visit before developing esKOA, and the interval change between those visits., Results: Our analytic sample was mostly female (58%), without radiographic knee osteoarthritis (KL grade=0 or 1; 60%), without stability or mobility concerns (91%), and without persistent knee pain (77%). At the visit before incident esKOA, most knees already had moderate-to-severe radiographic osteoarthritis using the original (62%) or alternate (50%) definition (versus <15% for either definition of no esKOA). Over 80% of knees that reached the criteria for esKOA achieved this based on increased knee symptom severity - typically without worsening radiographic severity (80%)., Conclusion: Radiographic severity predisposed a knee to esKOA. However, worsening knee symptoms led to the development of incident esKOA. If investigators want to increase the chance of identifying incident esKOA as an outcome, they should enrich their study samples with people with moderate-to-severe radiographic osteoarthritis. Our findings also highlight the potential reversibility of esKOA (a knee that is classified with esKOA but later is not classified with esKOA). Reversibility is not a flaw of an outcome defining esKOA but rather a desirable clinical outcome to demonstrate a therapeutic intervention can help people with esKOA improve their knee symptoms and delay a knee replacement., Competing Interests: Declaration of Competing Interest JBD and TEM served on an advisory board for Novartis. The authors have no other conflicts of interest with regard to this work., (Copyright © 2022. Published by Elsevier Inc.)

Objective: We previously published data representing calculations for sample sizes assuming that the reduction of the incidence of knee joint replacement (KJR) would be an endpoint to prove efficacy of a disease-modifying drug in osteoarthritis (DMOAD). The sample sizes required for such hypothetical studies appeared to be high, rendering those studies unrealistic in the clinical research setting for practical reasons. The purpose of this work is to calculate sample sizes for hypothetical trials for DMOAD efficacy using a proxy for reaching end-stage knee osteoarthritis (esKOA) as an endpoint., Methods: Based on a sub-population of the Osteoarthritis Initiative, the cumulative incidence for both esKOA and KJR were calculated for a period of four years. The sample sizes of hypothetical DMOAD trials were then calculated for particular sub-cohorts of the OAI subpopulation, subdividing the groups according to age, Kellgren-Lawrence (KL) grades and gender., Results: Both the incidence for esKOA and for KJR over the four year period increase along with rising age, severity of OA and being female. The sample sizes to detect DMOAD efficacy are considerably smaller if reduction of the incidence of esKOA is chosen as an endpoint instead of reduction of the incidence of KJR., Conclusion: In the future, generating health-economic data may become increasingly important to gain reimbursement. By choosing esKOA as an endpoint in DMOAD trials, we are able to show in our work that clinical trials in the field of OA are feasible, merely including a few hundred study participants per study arm., (Copyright © 2018 Elsevier Inc. All rights reserved.)