Evidence map›Paper›PMID 29046867›Full record

ArticleFrontiers in oncology2017

Use of Multicenter Data in a Large Cancer Registry for Evaluation of Outcome and Implementation of Novel Concepts.

Gabriele Schubert-Fritschle, Stephanie E Combs, Thomas Kirchner, Volkmar Nüssler, Jutta Engel

Abstract read
In one paragraph

Article in Frontiers in oncology, 2017. 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. Article
  2. Article
  3. Article
  4. Health services research in German radiation oncology: new opportunities to advance cancer care.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2018
    Review
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

5 authors.

Gabriele Schubert-FritschleMunich Cancer Registry (MCR) of the Munich Tumour Centre (TZM), Institute for Medical Information Processing, Biometry and Epidemiology (IBE), University Hospital of Munich, Ludwig-Maximilians-University (LMU), Munich, Germany.
Stephanie E CombsMunich Tumour Centre (TZM), Medical Faculties, Ludwig-Maximilians-University (LMU) and the Technical University of Munich (TUM), Munich, Germany.
Thomas KirchnerMunich Tumour Centre (TZM), Medical Faculties, Ludwig-Maximilians-University (LMU) and the Technical University of Munich (TUM), Munich, Germany.
Volkmar NüsslerMunich Tumour Centre (TZM), Medical Faculties, Ludwig-Maximilians-University (LMU) and the Technical University of Munich (TUM), Munich, Germany.
Jutta EngelMunich Cancer Registry (MCR) of the Munich Tumour Centre (TZM), Institute for Medical Information Processing, Biometry and Epidemiology (IBE), University Hospital of Munich, Ludwig-Maximilians-University (LMU), Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large clinical cancer registries (CCRs) in Germany shall be strengthened by the German Social Code Book V (SGB V) and implemented until the end of 2017. There are currently several large cancer registries that support clinical data for outcome analysis and knowledge acquisition. The various examples of the Munich Cancer Registry outlined in this paper present many-sided possibilities using and analyzing registry data. The main objective of population-based cancer registration within a defined area and the performance of outcomes research is to provide feedback regarding the results to the broad public, the reporting doctors, and the scientific community. These tasks determine principles of operation and data usage by CCRs. Each clinical department delivers its own findings and applied therapy. The compilation of these data in CCRs provides information on patient progress through the regional network of medical care and delivers meaningful information on the course of oncological diseases. Successful implementation of CCRs allows for presenting the statistical outcomes of health-care delivery, improving the quality of care within the region, accelerating the process of implementing innovative therapies, and generating new hypotheses as a stimulus for research activities.

Indexed as

cancer incidencecancer mortalitycomparative effectiveness researchdata analysisquality assurancesurvivaltrends

Identifiers

PMID29046867
PMCPMC5632760

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.