Evidence map›Paper›PMID 32077048›Full record

ReviewJournal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract2020

Big Data vs. Clinical Trials in HPB Surgery.

Susanna W L de Geus, Teviah E Sachs, Jennifer F Tseng

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

3 authors at 1 institution in 1 country.

Susanna W L de GeusDepartment of Surgery, Boston Medical Center, Boston University School of Medicine, Boston, MA, USA.ORCID http://orcid.org/0000-0001-8995-2304
Teviah E SachsDepartment of Surgery, Boston Medical Center, Boston University School of Medicine, Boston, MA, USA.
Jennifer F TsengDepartment of Surgery, Boston Medical Center, Boston University School of Medicine, Boston, MA, USA. Jennifer.Tseng@BMC.org.
Boston University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Randomized controlled clinical trials (RCTs) are at the heart of "evidence-based" medicine. However, in surgical practice, RCTs remain uncommon. Conducting well-designed RCTs for surgical procedures is often challenged by inadequate recruitment accrual, blinding, or standardization of the surgical procedure, as well as lack of funding and evolution of the treatment strategy during the many years over which such trials are conducted. In addition, most clinical trials are performed in academic high-volume centers in highly selected patients, which may not necessarily reflect a "real-world" practice setting. Over the past decades, surgical outcomes research using nationwide administrative and registry databases has become increasingly common. Large databases provide easy and inexpensive access to data on a large and diverse patient population at a variety of treatment centers. Furthermore, large database studies provide the opportunity to answer questions that would be impossible or very arduous to answer using RCTs, including questions regarding health policy efficacy, trends in surgical practice, access to health care, impact of hospital volume, and adherence to practice guidelines, as well as research questions regarding rare disease, infrequent surgical outcomes, and specific subpopulation. Prospective data registries may also allow for quality benchmarking and auditing. This review outlines the role, advantages, and limitations of RCTs and large database studies in answering important research questions in surgery.

Indexed as

Big DataOutcome Assessment, Health CareDatabases, FactualEvidence-Based MedicineHumansRegistrieslarge database studiesRandomized clinical trials

Identifiers

PMID32077048
OpenAlexW3008808831

What OpenQuestion holds

Textmetadata
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.