Evidence map›Paper›PMID 26834468›Full record

ArticleInternational journal of chronic obstructive pulmonary disease2016

COPD exacerbations associated with the modified Medical Research Council scale and COPD assessment test among Humana Medicare members.

Margaret K Pasquale, Yihua Xu, Christine L Baker, Kelly H Zou, John G Teeter, Andrew M Renda, Cralen C Davis, Theodore C Lee, Joel Bobula

Open access · goldAbstract readComparative Study
In one paragraph

Article in International journal of chronic obstructive pulmonary disease, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 22% of its field
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
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

9 authors at 3 institutions in 2 countries.

Margaret K PasqualeComprehensive Health Insights, Inc., Humana Inc., Louisville, KY.
Yihua XuComprehensive Health Insights, Inc., Humana Inc., Louisville, KY.
Christine L BakerOutcomes and Evidence, Global Health & Value, Pfizer Inc., New York, NY.
Kelly H ZouStatistical Center for Outcomes, Real-World and Aggregate Data, Global Innovative Pharma Business, Pfizer Inc., New York, NY.
John G TeeterGlobal Medical Development, Global Innovative Pharma Business, Pfizer Inc., Groton, CT, KY.
Andrew M RendaRetail Strategy & Execution, Humana Inc., Louisville, KY.
Cralen C DavisComprehensive Health Insights, Inc., Humana Inc., Louisville, KY.
Theodore C LeeGlobal Medical Affairs, Global Innovative Pharma Business, Pfizer Inc., New York, NY, USA.
Joel BobulaOutcomes and Evidence, Global Health & Value, Pfizer Inc., New York, NY.
Pfizer (United States) · USComprehensive Clinical Research · USHumana (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Global initiative for chronic Obstructive Lung Disease guidelines recommend assessment of COPD severity, which includes symptomatology using the modified Medical Research Council (mMRC) or COPD assessment test (CAT) score in addition to the degree of airflow obstruction and exacerbation history. While there is great interest in incorporating symptomatology, little is known about how patient reported symptoms are associated with future exacerbations and exacerbation-related costs.

methodsThe mMRC and CAT were mailed to a randomly selected sample of 4,000 Medicare members aged >40 years, diagnosed with COPD (≥2 encounters with International Classification of Dis eases-9th Edition Clinical Modification: 491.xx, 492.xx, 496.xx, ≥30 days apart). The exacerbations and exacerbation-related costs were collected from claims data during 365-day post-survey after exclusion of members lost to follow-up or with cancer, organ transplant, or pregnancy. A logistic regression model estimated the predictive value of exacerbation history and symptomatology on exacerbations during follow-up, and a generalized linear model with log link and gamma distribution estimated the predictive value of exacerbation history and symptomatology on exacerbation-related costs.

resultsAmong a total of 1,159 members who returned the survey, a 66% (765) completion rate was observed. Mean (standard deviation) age among survey completers was 72.0 (8.3), 53.7% female and 91.2% white. Odds ratios for having post-index exacerbations were 3.06, 4.55, and 16.28 times for members with 1, 2, and ≥3 pre-index exacerbations, respectively, relative to members with 0 pre-index exacerbations (P<0.001 for all). The odds ratio for high vs low symptoms using CAT was 2.51 (P<0.001). Similarly, exacerbation-related costs were 73% higher with each incremental pre-index exacerbation, and over four fold higher for high-vs low-symptom patients using CAT (each P<0.001). The symptoms using mMRC were not statistically significant in either model (P>0.10).

conclusionThe patient-reported symptoms contribute important information related to future COPD exacerbations and exacerbation-related costs beyond that explained by exacerbation history.

Indexed as

Pulmonary Disease, Chronic ObstructiveAgedComorbidityDisease ProgressionFemaleHumansMaleMedicareMiddle AgedOutcome Assessment, Health CareRespiratory Function TestsSeverity of Illness IndexSymptom AssessmentSymptom Flare UpUnited StatesCOPD symptomatologyexacerbation-related costexacerbationsGlobal initiative for chronic Obstructive Lung Diseasesurvey data

Identifiers

PMID26834468
PMCPMC4716734
OpenAlexW2239307315

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.