Evidence map›Paper›PMID 32144896›Full record

Trial reportArthritis care & research2021

Precision Medicine Approach to Develop and Internally Validate Optimal Exercise and Weight-Loss Treatments for Overweight and Obese Adults With Knee Osteoarthritis: Data From a Single-Center Randomized Trial.

Xiaotong Jiang, Amanda E Nelson, Rebecca J Cleveland, Daniel P Beavers, Todd A Schwartz, Liubov Arbeeva, Carolina Alvarez, Leigh F Callahan, Stephen Messier, Richard Loeser and 1 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Arthritis care & research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Deconstructing the "types" of osteoarthritis.Osteoarthritis imaging · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Xiaotong JiangUniversity of North Carolina, Chapel Hill.
Amanda E NelsonUniversity of North Carolina, Chapel Hill.
Rebecca J ClevelandUniversity of North Carolina, Chapel Hill.
Daniel P BeaversWake Forest School of Medicine, Winston-Salem, North Carolina.
Todd A SchwartzUniversity of North Carolina, Chapel Hill.
Liubov ArbeevaUniversity of North Carolina, Chapel Hill.
Carolina AlvarezUniversity of North Carolina, Chapel Hill.
Leigh F CallahanUniversity of North Carolina, Chapel Hill.
Stephen MessierWake Forest University, Winston-Salem, North Carolina.
Richard LoeserUniversity of North Carolina, Chapel Hill.ORCID 0000-0003-2832-6144
Michael R KosorokUniversity of North Carolina, Chapel Hill.

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
Statistical Methods for Cancer Clinical TrialsP01CA142538 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KOSOROK, MICHAEL R · 2010 to 2019
$21.3M
UNC Core Center for Clinical ResearchP30AR072580 · NIAMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LEIGH Fleming CALLAHAN, Amanda E Nelson · 2019 to 2026
$6.1M
NIAMS Multidisciplinary Clinical Research CenterP60AR064166 · NIAMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SCHWARTZ, TODD A · 2013 to 2017
$5.8M
Intensive Dietary Restriction with Exercise in ArthritisR01AR052528 · NIAMS · WAKE FOREST UNIVERSITY · PI MESSIER, STEPHEN P · 2006 to 2010
$2.9M
NCATS NIH HHS UL1 TR002489NCI NIH HHS P01 CA142538NIAMS NIH HHS P30 AR072580NIAMS NIH HHS P60 AR064166NIAMS NIH HHS R01 AR052528
6 · The paper itself

Abstract

objectiveTo apply a precision medicine approach to determine the optimal treatment regime for participants in an exercise (E), dietary weight loss (D), and D + E trial for knee osteoarthritis that would maximize their expected outcomes.

methodsUsing data from 343 participants of the Intensive Diet and Exercise for Arthritis (IDEA) trial, we applied 24 machine-learning models to develop individualized treatment rules on 7 outcomes: Short Form 36 physical component score, weight loss, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain/function/stiffness scores, compressive force, and interleukin-6 level. The optimal model was selected based on jackknife value function estimates that indicate improvement in the outcomes if future participants follow the estimated decision rule compared to the optimal single, fixed treatment model.

resultsMultiple outcome random forest was the optimal model for the WOMAC outcomes. For the other outcomes, list-based models were optimal. For example, the estimated optimal decision rule for weight loss indicated assigning the D + E intervention to participants with baseline weight not exceeding 109.35 kg and waist circumference above 90.25 cm, and assigning D to all other participants except those with a history of a heart attack. If applied to future participants, the optimal rule for weight loss is estimated to increase average weight loss to 11.2 kg at 18 months, contrasted with 9.8 kg if all participants received D + E (P = 0.01).

conclusionThe precision medicine models supported the overall findings from IDEA that the D + E intervention was optimal for most participants, but there was evidence that a subgroup of participants would likely benefit more from diet alone for 2 outcomes.

Indexed as

Caloric RestrictionClinical Decision RulesExercise TherapyPrecision MedicineWeight LossAgedClinical Decision-MakingFemaleHumansKnee JointMachine LearningMaleMiddle AgedObesityOsteoarthritis, KneePredictive Value of Tests

Identifiers

PMID32144896
PMCPMC7483572

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.