Evidence map›Paper›PMID 34375608›Full record

ArticleCancer cell2021

Multiplex computational pathology for treatment response predication.

Ming Y Lu, Houssein A Sater, Faisal Mahmood

Abstract readComment
PubMed Publisher
In one paragraph

Article in Cancer cell, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Ming Y LuDepartment of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Cancer Program, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Cancer Data Science Program, Dana-Farber Cancer Institute, Boston, MA 02115, USA.
Houssein A SaterCleveland Clinic Martin Health Center for Clinical Research, Stuart, FL 34994, USA.
Faisal MahmoodDepartment of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Cancer Program, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Cancer Data Science Program, Dana-Farber Cancer Institute, Boston, MA 02115, USA. Electronic address: faisalmahmood@bwh.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently published in Science, AstroPath outlines a standardized workflow for multiplex immunofluorescence (mIF) panel development, imaging, and analysis; showcases its potential in biomarker discovery for predicting response to anti-PD-1 treatment; and paves the way for large-scale computational pathology studies on high-quality mIF datasets using data-driven machine-learning techniques.

Indexed as

Machine LearningFluorescent Antibody TechniqueHumansWorkflow

Identifiers

PMID34375608

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.