Evidence map›Paper›PMID 23108385›Full record

ArticleStrahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]2012

[Database supported electronic retrospective analyses in radiation oncology: establishing a workflow using the example of pancreatic cancer].

K A Kessel, D Habermehl, C Bohn, A Jäger, R O Floca, L Zhang, N Bougatf, R Bendl, J Debus, S E Combs

Abstract read
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In one paragraph

Article in Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al], 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Automated data mining of a plan-check database and example application.Journal of applied clinical medical physics · 2018
    Article
  2. Article
  3. Review
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  5. Article
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  8. Comparison of four target volume definitions for pancreatic cancer. Guidelines for treatment of the lymphatics and the primary tumor.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2013
    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

10 authors at 6 institutions in 1 country.

K A KesselAbteilung für Radioonkolgie und Strahlentherapie, Universitätsklinikum Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Deutschland. Kerstin.Kessel@med.uni-heidelberg.de
D Habermehl
C Bohn
A Jäger
R O Floca
L Zhang
N Bougatf
R Bendl
J Debus
S E Combs
University Hospital Heidelberg · DEDKFZ-ZMBH Alliance · DEChirurgische Universitätsklinik Heidelberg · DEGerman Cancer Research Center · DEHeidelberg University · DEHeilbronn University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeEspecially in the field of radiation oncology, handling a large variety of voluminous datasets from various information systems in different documentation styles efficiently is crucial for patient care and research. To date, conducting retrospective clinical analyses is rather difficult and time consuming. With the example of patients with pancreatic cancer treated with radio-chemotherapy, we performed a therapy evaluation by using an analysis system connected with a documentation system. MATERIALS AND

methodsA total number of 783 patients have been documented into a professional, database-based documentation system. Information about radiation therapy, diagnostic images and dose distributions have been imported into the web-based system.

resultsFor 36 patients with disease progression after neoadjuvant chemoradiation, we designed and established an analysis workflow. After an automatic registration of the radiation plans with the follow-up images, the recurrence volumes are segmented manually. Based on these volumes the DVH (dose volume histogram) statistic is calculated, followed by the determination of the dose applied to the region of recurrence. All results are saved in the database and included in statistical calculations.

conclusionThe main goal of using an automatic analysis tool is to reduce time and effort conducting clinical analyses, especially with large patient groups. We showed a first approach and use of some existing tools, however manual interaction is still necessary. Further steps need to be taken to enhance automation. Already, it has become apparent that the benefits of digital data management and analysis lie in the central storage of data and reusability of the results. Therefore, we intend to adapt the analysis system to other types of tumors in radiation oncology.

Indexed as

Databases, FactualWorkflowChemoradiotherapyDatabase Management SystemsDecision Support TechniquesDisease ProgressionDocumentationDose-Response Relationship, RadiationElectronic Data ProcessingGermanyHumansMathematical ComputingNeoadjuvant TherapyNeoplasm Recurrence, LocalNumerical Analysis, Computer-AssistedPancreatic Neoplasms

Identifiers

PMID23108385
OpenAlexW140385798

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.