Evidence map›Paper›PMID 25187004›Full record

ArticleJournal of cancer survivorship : research and practice2015

An algorithm to identify the development of lymphedema after breast cancer treatment.

Tina W F Yen, Purushuttom W Laud, Rodney A Sparapani, Jianing Li, Ann B Nattinger

Abstract readValidation Study
In one paragraph

Article in Journal of cancer survivorship : research and practice, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Observational
  2. 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

5 authors at 1 institution in 1 country.

Tina W F YenDivision of Surgical Oncology, Medical College of Wisconsin, 9200 W. Wisconsin Avenue, Milwaukee, WI, 53226, USA, tyen@mcw.edu.
Purushuttom W Laud
Rodney A Sparapani
Jianing Li
Ann B Nattinger
Medical College of Wisconsin · US

Funding

OUTCOMES OF OLDER WOMEN WITH EARLY STAGE BREAST CANCERR01CA081379 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI NATTINGER, ANN B · 2000 to 2008
$3.0M
SES Disparities in Breast Cancer: Effect of Pharmaceutical CoverageR01CA127648 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI NATTINGER, ANN B · 2009 to 2013
$2.4M
Lymphedema incidence and risk factors among older breast cancer patientsK07CA125586 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI YEN, TINA WF · 2007 to 2011
$789k
NCI NIH HHS K07 CA125586NCI NIH HHS K07CA125586NCI NIH HHS K07CA125586-03S1NCI NIH HHS R01 CA081379NCI NIH HHS R01 CA127648NCI NIH HHS R01CA127648NCI NIH HHS R01CA81379
6 · The paper itself

Abstract

purposeLarge, population-based studies are needed to better understand lymphedema, a major source of morbidity among breast cancer survivors. One challenge is identifying lymphedema in a consistent fashion. We sought to develop and validate an algorithm using Medicare claims to identify lymphedema after breast cancer surgery.

methodsFrom a population-based cohort of 2,597 elderly (65+) women who underwent incident breast cancer surgery in 2003 and completed annual telephone surveys through 2008, two algorithms were developed using Medicare claims from half of the cohort and validated in the remaining half. A lymphedema-positive case was defined by patient report.

resultsA simple two ICD-9 code algorithm had 69 % sensitivity, 96 % specificity, positive predictive value >75 % if prevalence of lymphedema is >16 %, negative predictive value >90 %, and area under receiver operating characteristic curve (AUC) of 0.82 (95 % CI 0.80-0.85). A more sophisticated, multi-step algorithm utilizing diagnostic and treatment codes, logistic regression methods, and a reclassification step performed similarly to the two-code algorithm.

conclusionsGiven the similar performance of the two validated algorithms, the ease of implementing the simple algorithm and the fact that the simple algorithm does not include treatment codes, we recommend that this two-code algorithm be validated in and applied to other population-based breast cancer cohorts. IMPLICATIONS FOR CANCER SURVIVORS: This validated lymphedema algorithm will facilitate the conduct of large, population-based studies in key areas (incidence rates, risk factors, prevention measures, treatment, and cost/economic analyses) that are critical to advancing our understanding and management of this challenging and debilitating chronic disease.

Indexed as

AlgorithmsAgedAged, 80 and overBreast NeoplasmsCohort StudiesFemaleHumansLymphedemaMedicarePrevalenceRisk FactorsSensitivity and SpecificitySurvivorsUnited States

Identifiers

PMID25187004
PMCPMC4362809
OpenAlexW2030498796

What OpenQuestion holds

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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.