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Objective consensus from decision trees.

Putora PM, Panje CM, Papachristofilou A, Dal Pra A, Hundsberger T, Plasswilm L - Radiat Oncol (2014)

Bottom Line: An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties.Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters.Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiation Oncology, Kantonsspital St. Gallen, Rorschacherstr. 95, 9007, St. Gallen, Switzerland. paul.putora@kssg.ch.

ABSTRACT

Background: Consensus-based approaches provide an alternative to evidence-based decision making, especially in situations where high-level evidence is limited. Our aim was to demonstrate a novel source of information, objective consensus based on recommendations in decision tree format from multiple sources.

Methods: Based on nine sample recommendations in decision tree format a representative analysis was performed. The most common (mode) recommendations for each eventuality (each permutation of parameters) were determined. The same procedure was applied to real clinical recommendations for primary radiotherapy for prostate cancer. Data was collected from 16 radiation oncology centres, converted into decision tree format and analyzed in order to determine the objective consensus.

Results: Based on information from multiple sources in decision tree format, treatment recommendations can be assessed for every parameter combination. An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties. In the clinical example involving prostate cancer therapy, three parameters were used with two cut-off values each (Gleason score, PSA, T-stage) resulting in a total of 27 possible combinations per decision tree. Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters.

Conclusion: Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.

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Related in: MedlinePlus

Nine sample decision trees are named “A” to “I”. Each tree starts at the root on the left side of the tree. Based on the parameters and their values it is possible to follow each decision tree from left to right to reach a specific treatment recommendation. The recommendations are “Nothing”, “Drug A”, “Radiotherapy” and “Operation” in these examples.
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Fig1: Nine sample decision trees are named “A” to “I”. Each tree starts at the root on the left side of the tree. Based on the parameters and their values it is possible to follow each decision tree from left to right to reach a specific treatment recommendation. The recommendations are “Nothing”, “Drug A”, “Radiotherapy” and “Operation” in these examples.

Mentions: For exploration, simple random criteria were defined (e.g. age, visibility, histology) to include different data types and ranges, i.e. numeric values with a range (age: 0–140 years), Boolean (visibility: true/false) or categorical (histology: benign/malignant). These parameters were randomly combined to create nine different decision trees of varying complexity [17] (Figure 1). To provide altering treatment recommendations “radiotherapy”, “operation”, “DrugA” and “nothing” were randomly assigned to the decision tree branches.Figure 1


Objective consensus from decision trees.

Putora PM, Panje CM, Papachristofilou A, Dal Pra A, Hundsberger T, Plasswilm L - Radiat Oncol (2014)

Nine sample decision trees are named “A” to “I”. Each tree starts at the root on the left side of the tree. Based on the parameters and their values it is possible to follow each decision tree from left to right to reach a specific treatment recommendation. The recommendations are “Nothing”, “Drug A”, “Radiotherapy” and “Operation” in these examples.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4269842&req=5

Fig1: Nine sample decision trees are named “A” to “I”. Each tree starts at the root on the left side of the tree. Based on the parameters and their values it is possible to follow each decision tree from left to right to reach a specific treatment recommendation. The recommendations are “Nothing”, “Drug A”, “Radiotherapy” and “Operation” in these examples.
Mentions: For exploration, simple random criteria were defined (e.g. age, visibility, histology) to include different data types and ranges, i.e. numeric values with a range (age: 0–140 years), Boolean (visibility: true/false) or categorical (histology: benign/malignant). These parameters were randomly combined to create nine different decision trees of varying complexity [17] (Figure 1). To provide altering treatment recommendations “radiotherapy”, “operation”, “DrugA” and “nothing” were randomly assigned to the decision tree branches.Figure 1

Bottom Line: An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties.Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters.Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiation Oncology, Kantonsspital St. Gallen, Rorschacherstr. 95, 9007, St. Gallen, Switzerland. paul.putora@kssg.ch.

ABSTRACT

Background: Consensus-based approaches provide an alternative to evidence-based decision making, especially in situations where high-level evidence is limited. Our aim was to demonstrate a novel source of information, objective consensus based on recommendations in decision tree format from multiple sources.

Methods: Based on nine sample recommendations in decision tree format a representative analysis was performed. The most common (mode) recommendations for each eventuality (each permutation of parameters) were determined. The same procedure was applied to real clinical recommendations for primary radiotherapy for prostate cancer. Data was collected from 16 radiation oncology centres, converted into decision tree format and analyzed in order to determine the objective consensus.

Results: Based on information from multiple sources in decision tree format, treatment recommendations can be assessed for every parameter combination. An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties. In the clinical example involving prostate cancer therapy, three parameters were used with two cut-off values each (Gleason score, PSA, T-stage) resulting in a total of 27 possible combinations per decision tree. Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters.

Conclusion: Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.

Show MeSH
Related in: MedlinePlus