Evidence map›Paper›PMID 27738762›Full record

ReviewJournal of gastroenterology2017

Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis.

Tsuyoshi Hamada, NaNa Keum, Reiko Nishihara, Shuji Ogino

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of gastroenterology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 3 pooled it
–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

62 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. 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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  11. KRAS: A Druggable Target in Colon Cancer Patients.International journal of molecular sciences · 2022
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2 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

4 authors.

Tsuyoshi HamadaDepartment of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Ave., Room SM1036, Boston, MA, 02215, USA.
NaNa KeumDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Reiko NishiharaDepartment of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Ave., Room SM1036, Boston, MA, 02215, USA. rnishiha@hsph.harvard.edu.
Shuji OginoDepartment of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Ave., Room SM1036, Boston, MA, 02215, USA. shuji_ogino@dfci.harvard.edu.ORCID http://orcid.org/0000-0002-3909-2323

Funding

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
Lifestyle, genetics and colonoscopy for colorectal cancer preventionK07CA190673 · NCI · DANA-FARBER CANCER INST · PI NISHIHARA, REIKO · 2014 to 2018
$609k
NCI NIH HHS K07 CA190673NCI NIH HHS R01 CA151993NCI NIH HHS R35 CA197735
6 · The paper itself

Abstract

Molecular pathological epidemiology (MPE) is an integrative field that utilizes molecular pathology to incorporate interpersonal heterogeneity of a disease process into epidemiology. In each individual, the development and progression of a disease are determined by a unique combination of exogenous and endogenous factors, resulting in different molecular and pathological subtypes of the disease. Based on "the unique disease principle," the primary aim of MPE is to uncover an interactive relationship between a specific environmental exposure and disease subtypes in determining disease incidence and mortality. This MPE approach can provide etiologic and pathogenic insights, potentially contributing to precision medicine for personalized prevention and treatment. Although breast, prostate, lung, and colorectal cancers have been among the most commonly studied diseases, the MPE approach can be used to study any disease. In addition to molecular features, host immune status and microbiome profile likely affect a disease process, and thus serve as informative biomarkers. As such, further integration of several disciplines into MPE has been achieved (e.g., pharmaco-MPE, immuno-MPE, and microbial MPE), to provide novel insights into underlying etiologic mechanisms. With the advent of high-throughput sequencing technologies, available genomic and epigenomic data have expanded dramatically. The MPE approach can also provide a specific risk estimate for each disease subgroup, thereby enhancing the impact of genome-wide association studies on public health. In this article, we present recent progress of MPE, and discuss the importance of accounting for the disease heterogeneity in the era of big-data health science and precision medicine.

Indexed as

Colorectal NeoplasmsDiseaseEpidemiologyGene-Environment InteractionGenome-Wide Association StudyHumansImmunityMicrobiologyPathology, MolecularPharmacoepidemiologyPrecision MedicineColorectal neoplasmsDrug therapyImmunologyMicrobiologyPersonalized therapy

Identifiers

PMID27738762
PMCPMC5325774

What Socratic 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 Socratic graph.