Evidence map›Paper›PMID 31567871›Full record

ArticleMenopause (New York, N.Y.)2019

Development of a comprehensive health-risk prediction tool for postmenopausal women.

Haley Hedlin, Julie Weitlauf, Carolyn J Crandall, Rami Nassir, Jane A Cauley, Lorena Garcia, Robert Brunner, Jennifer Robinson, Marica L Stefanick, John Robbins

Open access · greenAbstract readMulticenter StudyValidation Study
In one paragraph

Article in Menopause (New York, N.Y.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 34% 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, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Differential effects ofFrontiers in endocrinology · 2022
    Article
  4. Article
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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

10 authors at 8 institutions in 2 countries.

Haley HedlinQuantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, CA.
Julie WeitlaufVA Palo Alto Health Care System, Palo Alto, CA.
Carolyn J CrandallDivision of General Internal Medicine and Health Services Research, David Geffen School of Medicine at University of California, Los Angeles, CA.
Rami NassirDepartment of Pathology, Umm Al-Qura'a University, Mecca, Saudi Arabia.
Jane A CauleyDepartment of Epidemiology, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, PA.
Lorena GarciaDepartment of Public Health Sciences, UC Davis School of Medicine, Sacramento, CA.
Robert BrunnerDepartment of Medicine, University of Nevada, Reno School of Medicine, Reno, NV.
Jennifer RobinsonDepartments of Epidemiology & Medicine, College of Public Health, University of Iowa, Iowa City, IA.
Marica L StefanickStanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA.
John RobbinsDepartment of Medicine, University of California Davis School of Medicine, Sacramento, CA.
Stanford University · USUmm al-Qura University · SAUniversity of California, Davis · USUniversity of California, Los Angeles · USUniversity of Iowa · USUniversity of Nevada, Reno · USUniversity of Pittsburgh · USVA Palo Alto Health Care System · US

Funding

Translational Oncology Research Program (Project-005)P30CA124435 · NCI · STANFORD UNIVERSITY · PI Vittorio Sebastiano · 2007 to 2026
$71.4M
VANGUARD CENTER FOR WOMEN'S HEALTH INITIATIVEN01WH032113 · WH · UNIVERSITY OF CALIFORNIA DAVIS · PI ROBBINS, JOHN A · 1993 to 2000
$615k
NCI NIH HHS P30 CA124435NHLBI NIH HHS HHSN268201100001INHLBI NIH HHS HHSN268201100002INHLBI NIH HHS HHSN268201100003INHLBI NIH HHS HHSN268201100004INHLBI NIH HHS HHSN268201100046CWHI NIH HHS HHSN268201100001CWHI NIH HHS HHSN268201100002CWHI NIH HHS HHSN268201100003CWHI NIH HHS HHSN268201100004CWHI NIH HHS N01 WH032113
6 · The paper itself

Abstract

objectiveThe aim of the study was to develop a web-based calculator that predicts the likelihood of experiencing multiple, competing outcomes prospectively over 5, 10, and 15 years.

methodsBaseline demographic and medical data from a healthy and racially and ethnically diverse cohort of 161,808 postmenopausal women, aged 50 to 79 at study baseline, who participated in the Women's Health Initiative (WHI), were used to develop and evaluate a risk-prediction calculator designed to predict individual risk for morbidity and mortality outcomes. Women were enrolled from 40 sites arranged in four regions of the United States. The calculator predicts all-cause mortality, adjudicated outcomes of health events (ie, myocardial infarction [MI], stroke, and hip fracture), and disease (lung, breast, and colorectal cancer). A proportional subdistribution hazards regression model was used to develop the calculator in a training dataset using data from three regions. The calculator was evaluated using the C-statistic in a test dataset with data from the fourth region.

resultsThe predictive validity of our calculator measured by the C-statistic in the test dataset for a first event at 5 and 15 years was as follows: MI 0.77, 0.61, stroke 0.77, 0.72, lung cancer 0.82, 0.79, breast cancer 0.60, 0.59, colorectal cancer 0.67, 0.60, hip fracture 0.79, 0.76, and death 0.74, 0.72.

conclusionThis study represents the first large-scale study to develop a risk prediction calculator that yields health risk prediction for several outcomes simultaneously. Development of this tool is a first step toward enabling women to prioritize interventions that may decrease these risks. : Video Summary:http://links.lww.com/MENO/A463.

Indexed as

Health StatusAgedFemaleHumansMiddle AgedMortalityPostmenopauseProportional Hazards ModelsProspective StudiesRisk AssessmentRisk FactorsTime FactorsWomen's Health

Identifiers

PMID31567871
PMCPMC6893122
OpenAlexW2974754530

What OpenQuestion holds

Textmetadata
LicenceTDM
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.