Evidence map›Paper›PMID 30042820›Full record

ArticleOncotarget2018

Heuristic value-based framework for lung cancer decision-making.

Isa Mambetsariev, Rebecca Pharaon, Arin Nam, Kevin Knopf, Benjamin Djulbegovic, Victoria M Villaflor, Everett E Vokes, Ravi Salgia

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. 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

8 authors at 4 institutions in 1 country.

Isa Mambetsariev *Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA, USA.
Rebecca Pharaon *Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA, USA.
Arin Nam *Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA, USA.
Kevin KnopfCalifornia Pacific Medical Center Research Institute, San Francisco, CA, USA.
Benjamin DjulbegovicDepartment of Clinical Supportive Care, City of Hope, Duarte, CA, USA.
Victoria M VillaflorDepartment of Medicine (Hematology and Oncology), Northwestern University, Chicago, IL, USA.
Everett E VokesDepartment of Medicine, University of Chicago, Chicago, IL, USA.
Ravi SalgiaDepartment of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA, USA.
City of Hope · USCalifornia Pacific Medical Center · USNorthwestern University · USUniversity of Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heuristics and the application of fast-and-frugal trees may play a role in establishing a clinical decision-making framework for value-based oncology. We determined whether clinical decision-making in oncology can be structured heuristically based on the timeline of the patient's treatment, clinical intuition, and evidence-based medicine. A group of 20 patients with advanced non-small cell lung cancer (NSCLC) were enrolled into the study for extensive treatment analysis and sequential decision-making. The extensive clinical and genomic data allowed us to evaluate the methodology and efficacy of fast-and-frugal trees as a way to quantify clinical decision-making. The results of the small cohort will be used to further advance the heuristic framework as a way of evaluating a large number of patients within registries. Among the cohort whose data was analyzed, substitution and amplification mutations occurred most frequently. The top five most prevalent genomic alterations were TP53 (45%), ALK (40%), LRP1B (30%), CDKN2A (25%), and MYC (25%). These 20 cases were analyzed by this clinical decision-making process and separated into two distinctions: 10 straightforward cases that represented a clearer decision-making path and 10 complex cases that represented a more intricate treatment pathway. The myriad of information from each case and their distinct pathways was applied to create the foundation of a framework for lung cancer decision-making as an aid for oncologists. In late-stage lung cancer patients, the fast-and-frugal heuristics can be utilized as a strategy of quantifying proper decision-making with limited information.

Indexed as

fast-and-frugal treesframeworkgenomicsheuristicsnon-small cell lung cancer

Identifiers

PMID30042820
PMCPMC6057456
OpenAlexW2878977063

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.