Evidence map›Paper›PMID 25315184›Full record

ArticleHealth care management science2015

Breast cancer therapy planning - a novel support concept for a sequential decision making problem.

Alexander Scherrer, Ilka Schwidde, Andreas Dinges, Patrick Rüdiger, Sherko Kümmel, Karl-Heinz Küfer

Abstract read
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In one paragraph

Article in Health care management science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Internet Usage Trends in Thoracic Surgery Patients and Their Caregivers.Journal of cancer education : the official journal of the American Association for Cancer Education · 2017
    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

6 authors.

Alexander ScherrerDepartment of Optimization, Fraunhofer Institute for Industrial Mathematics (ITWM), Fraunhofer-Platz 1, 67663, Kaiserslautern, Germany, alexander.scherrer@itwm.fraunhofer.de.
Ilka Schwidde
Andreas Dinges
Patrick Rüdiger
Sherko Kümmel
Karl-Heinz Küfer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is the most common carcinosis with the largest number of mortalities in women. Its therapy comprises a wide spectrum of different treatment modalities a breast oncologist decides about for the individual patient case. These decisions happen according to medical guide lines, current scientific publications and experiences acquired in former cases. Clinical decision making therefore involves the time-consuming search for possible therapy options and their thorough testing for applicability to the current patient case.This research work addresses breast cancer therapy planning as a multi-criteria sequential decision making problem. The approach is based on a data model for patient cases with therapy descriptions and a mathematical notion for therapeutic relevance of medical information. This formulation allows for a novel decision support concept, which targets at eliminating observed weaknesses in clinical routine of breast cancer therapy planning.

Indexed as

Decision Support TechniquesAntineoplastic AgentsBreast NeoplasmsDecision MakingFemaleHumansModels, TheoreticalAntineoplastic Agents

Identifiers

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.