Evidence map›Paper›PMID 26928707›Full record

ReviewEpidemiology (Cambridge, Mass.)2016

Review Article: The Role of Molecular Pathological Epidemiology in the Study of Neoplastic and Non-neoplastic Diseases in the Era of Precision Medicine.

Shuji Ogino, Reiko Nishihara, Tyler J VanderWeele, Molin Wang, Akihiro Nishi, Paul Lochhead, Zhi Rong Qian, Xuehong Zhang, Kana Wu, Hongmei Nan and 7 more

Open access · greenAbstract readReview
In one paragraph

Review in Epidemiology (Cambridge, Mass.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
120citing papers in PubMed, 8 pooled it
18.0field-weighted citation impact, top 1% 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

120 citing papers in PubMed, 8 syntheses or guidelines pooled it, 172 citations in OpenAlex.

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  10. The Prostate, Lung, Colorectal and Ovarian Cancer (PLCO) Screening Trial Pathology Tissue Resource.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2016
    Trial
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  12. Can We Interpret Analyses of Etiologic Heterogeneity When Molecular Markers Are Used to Classify Tumors?Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
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60 more citing papers are in PubMed but not listed here.

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

17 authors at 1 institution in 1 country.

Shuji OginoFrom the aDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; bDivision of MPE Molecular Pathological Epidemiology, Brigham and Women's Hospital, Boston, MA; cDepartment of Pathology, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA; dDepartment of Medical Oncology, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA; eDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA; fDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA; gYale Institute for Network Science, Yale University, New Haven, CT; hInstitute of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom; iDivision of Gastroenterology, Massachusetts General Hospital, Boston, MA; jChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA; kDepartment of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, IN; lDivision of Rheumatology, Immunology and Allergy, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA; mDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA; nDivision of Adolescent/Young Adult Medicine, Boston Children's Hospital, Boston, MA; and oDepartment of Emergency Medicine, Massachusetts General Hospital, Boston, MA.
Reiko Nishihara
Tyler J VanderWeele
Molin Wang
Akihiro Nishi
Paul Lochhead
Zhi Rong Qian
Xuehong Zhang
Kana Wu
Hongmei Nan
Kazuki Yoshida
Danny A Milner
Andrew T Chan
Alison E Field
Carlos A Camargo
Michelle A Williams
Edward L Giovannucci
Brigham and Women's Hospital · US

Funding

Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
Inflammation and Colorectal NeoplasiaR01CA137178 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI CHAN, ANDREW T · 2009 to 2019
$6.5M
Accelerating Transdisciplinary Epidemiology of Colorectal CancerR35CA197735 · NCI · DANA-FARBER CANCER INST · PI OGINO, SHUJI · 2015 to 2021
$6.0M
Epigenetic Events and Colorectal Cancer EpidemiologyR01CA151993 · NCI · DANA-FARBER CANCER INST · PI OGINO, SHUJI · 2010 to 2014
$2.6M
Mentored Patient-Oriented Research in Digestive DiseasesK24DK098311 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI CHAN, ANDREW T · 2013 to 2017
$930k
Lifestyle, genetics and colonoscopy for colorectal cancer preventionK07CA190673 · NCI · DANA-FARBER CANCER INST · PI NISHIHARA, REIKO · 2014 to 2018
$609k
NCATS NIH HHS UL1 TR001108NCI NIH HHS K07 CA190673NCI NIH HHS R01 CA137178NCI NIH HHS R01 CA151993NCI NIH HHS R35 CA197735NIDDK NIH HHS K24 DK098311
6 · The paper itself

Abstract

Molecular pathology diagnostics to subclassify diseases based on pathogenesis are increasingly common in clinical translational medicine. Molecular pathological epidemiology (MPE) is an integrative transdisciplinary science based on the unique disease principle and the disease continuum theory. While it has been most commonly applied to research on breast, lung, and colorectal cancers, MPE can investigate etiologic heterogeneity in non-neoplastic diseases, such as cardiovascular diseases, obesity, diabetes mellitus, drug toxicity, and immunity-related and infectious diseases. This science can enhance causal inference by linking putative etiologic factors to specific molecular biomarkers as outcomes. Technological advances increasingly enable analyses of various -omics, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics, microbiome, immunomics, interactomics, etc. Challenges in MPE include sample size limitations (depending on availability of biospecimens or biomedical/radiological imaging), need for rigorous validation of molecular assays and study findings, and paucities of interdisciplinary experts, education programs, international forums, and standardized guidelines. To address these challenges, there are ongoing efforts such as multidisciplinary consortium pooling projects, the International Molecular Pathological Epidemiology Meeting Series, and the Strengthening the Reporting of Observational Studies in Epidemiology-MPE guideline project. Efforts should be made to build biorepository and biobank networks, and worldwide population-based MPE databases. These activities match with the purposes of the Big Data to Knowledge (BD2K), Genetic Associations and Mechanisms in Oncology (GAME-ON), and Precision Medicine Initiatives of the United States National Institute of Health. Given advances in biotechnology, bioinformatics, and computational/systems biology, there are wide open opportunities in MPE to contribute to public health.

Indexed as

Cardiovascular DiseasesDiabetes MellitusMolecular EpidemiologyNeoplasmsObesityPathology, MolecularPrecision MedicineCommunicable DiseasesDrug-Related Side Effects and Adverse ReactionsEpigenomicsGene Expression ProfilingGenomicsHumansMetabolomicsMicrobiotaObservational Studies as Topic

Identifiers

PMID26928707
PMCPMC4892980
OpenAlexW2291499494

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.