Evidence map›Paper›PMID 27771357›Full record

ArticleJournal of clinical epidemiology2017

A pseudo-random patient sampling method evaluated.

Nicole L De La Mata, Mi-Young Ahn, Nagalingeswaran Kumarasamy, Penh Sun Ly, Oon Tek Ng, Kinh Van Nguyen, Tuti Parwati Merati, Thuy Thanh Pham, Man Po Lee, Nicolas Durier and 1 more

Abstract readMulticenter Study
In one paragraph

Article in Journal of clinical epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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

7 citing papers in PubMed.

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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.

Nicole L De La MataThe Kirby Institute, UNSW Australia, Wallace Wurth Building, Sydney, NSW 2052, Australia. Electronic address: ndelamata@kirby.unsw.edu.au.
Mi-Young AhnDepartment of Internal Medicine and AIDS Research Institute, Yonsei University College of Medicine, Severance Hospital, Seoul, South Korea.
Nagalingeswaran KumarasamyChennai Antiviral Research and Treatment Clinical Research Site (CART CRS), YRGCARE Medical Centre, VHS, Chennai, India.
Penh Sun LyNational Center for HIV/AIDS, Dermatology & STDs, Phnom Penh, Cambodia.
Oon Tek NgDepartment of Infectious Diseases, Tan Tock Seng Hospital, Tan Tock Seng, Singapore.
Kinh Van NguyenNational Hospital for Tropical Diseases, Hanoi, Vietnam.
Tuti Parwati MeratiDepartment of Internal Medicine, Udayana University, Sanglah Hospital, Bali, Indonesia.
Thuy Thanh PhamBach Mai Hospital, Hanoi, Vietnam.
Man Po LeeDepartment of Medicine, Queen Elizabeth Hospital, Hong Kong, China.
Nicolas DurierTREAT Asia, amfAR-The Foundation for AIDS Research, Bangkok, Thailand.
Matthew G LawThe Kirby Institute, UNSW Australia, Wallace Wurth Building, Sydney, NSW 2052, Australia.

Funding

The Asia-Pacific HIV Research CollaborationU01AI069907 · NIAID · FOUNDATION FOR AIDS RESEARCH · PI ANNETTE H SOHN · 2006 to 2026
$44.8M
NIAID NIH HHS U01 AI069907
6 · The paper itself

Abstract

objectivesTo compare two human immunodeficiency virus (HIV) cohorts to determine whether a pseudo-random sample can represent the entire study population. STUDY DESIGN AND

settingHIV-positive patients receiving care at eight sites in seven Asian countries. The TREAT Asia HIV Observational database (TAHOD) pseudo-randomly selected a patient sample, while TREAT Asia HIV Observational database-Low Intensity Transfer (TAHOD-LITE) included all patients. We compared patient demographics, CD4 count, and HIV viral load testing for each cohort. Risk factors associated with CD4 count response, HIV viral load suppression (<400 copies/mL), and survival were determined for each cohort.

resultsThere were 2,318 TAHOD patients and 14,714 TAHOD-LITE patients. Patient demographics, CD4 count, and HIV viral load testing rates were broadly similar between the cohorts. CD4 count response and all-cause mortality were consistent among the cohorts with similar risk factors. HIV viral load response appeared to be superior in TAHOD and many risk factors differed, possibly due to viral load being tested on a subset of patients.

conclusionOur study gives the first empirical evidence that analysis of risk factors for completely ascertained end points from our pseudo-randomly selected patient sample may be generalized to our larger, complete population of HIV-positive patients. However, results can significantly vary when analyzing smaller or pseudo-random samples, particularly if some patient data are not completely missing at random, such as viral load results.

Indexed as

Epidemiologic Research DesignAdultAnti-HIV AgentsAsiaCD4 Lymphocyte CountCohort StudiesDatabases, FactualDemographyFemaleHIV InfectionsHumansMaleMiddle AgedObservational Studies as TopicPopulation SurveillanceRisk FactorsAnti-HIV AgentsAsiaCohortHIVObservational dataPatient samplingSelection bias

Identifiers

PMID27771357
PMCPMC5318236

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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.