Clinical Oncology(1992) 4:306-312 © 1992The RoyalCollegeof Radiologists

Clinical Oncology

Original Article Decision Analysis in Oncology: Panacea or Chimera? A. J. Munro Department of Radiotherapy, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK

Abstract. A review of the literature on the use of decision analysis in clinical oncology shows that, although these techniques have been available for more than 25 years, they have not been widely applied: only 19 decision analyses of therapeutic management in clinical oncology were found. The main disadvantages concern the difficulty of accurately assessing probabilities and defining measures of outcome. Time-consuming analysis may produce results that are either equivocal or simply confirm the expectations of common sense. If the basic design fails to include all relevant factors then any conclusions will be of little value. The main advantages are that, by demanding that problems be explicitly stated and analysed in a logical fashion, deficiencies in current knowledge, belief and practice are identified. The usefulness of these techniques lies in formulating management guidelines, either for treatment or for follow-up. They have only a limited role in decision making for individual patients. Keywords: Decision analysis; Decision support systems

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INTRODUCTION Panacea: a universal remedy Chimera: a mere wild fancy, an unfounded conception, a monster with a lion's head and a goat's body The cluster of techniques, collectively known as decision analysis, purports to facilitate decisionmaking under conditions of uncertainty [1, 2], but in spite of considerable promise, has found little acceptance in clinical medicine. First applied to a clinical problem in oncology nearly 25 yeas ago [3], it has not been adopted into routine clinical practice. Decision analysis has been defined [2] as "a systemic approach to decision making under conditions of uncertainty". This is too loose, most of us like to think our decisions are made systematically. Decision analysis provides a formalized system but even inserting the word formal into the definition is inadequate. For example the I Ching [4] provides a formal system to guide decisions, but patients might Correspondence and offprint requests to: A. J. Munro, Department of Radiotherapy,St Bartholomew'sHospital, West Smithfield, LondonEC1A 7BE, UK.

feel uneasy if they felt their clinical management was dictated by randomly cast patterns of yarrow stalks interpreted through a dictionary of hexagrams. A better definition might be that 'decision analysis provides a systematic formalized method for decision making under conditions of uncertainty in which a linear, logical, approach governs both the structuring and dissection of the the problem'. The techniques are tedious to perform by hand but the necessary calculations are easily performed by microcomputers. Software for decision analysis is readily available and, as well as performing straightforward analyses, most programs permit more sophisticated analyses using Markov processes, Boolean nodes, cost effectiveness estimations and Monte Carlo simulations.

USE IN THERAPY The easiest way to approach decision analysis is via the consideration of an oversimplified clinical problem expressed in the form of a decision tree (Fig. 1). This tree fairly crudely models alternate management strategies for a patient with a stage TiNoM0 carcinoma of the vocal cord. For the sake of demonstration the management alternatives are total laryngectomy and radical radiotherapy. By convention the points at which the decision tree branches are termed nodes. There are two types of node: decision nodes, at which actions are determined by conscious choices and chance nodes where the outcomes are beyond direct control and governed simply by chance or probability. Thus, choice of treatment is a decision node but the possible outcomes of that treatment are represented by chance nodes. The decision tree is constructed so that each path through the tree eventually leads, via the final branches of the tree (the terminal branches), to the final outcomes. Each outcome has to be defined in terms of its 'utility'. Utility can be expressed as quality adjusted survival in which the years of survival resulting from a given policy are multiplied by a quality factor, ranging from 0 to 1, which is a measure of the extent to which the quality of that survival is impaired. This results in the well known unit, the QALY (quality adjusted life year) [5]. Once utilities have been defined the analysis of the decision tree proceeds by a simple process called 'folding back'. Starting peripherally, the utility of

Decision Analysis in Oncology

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each branch is multiplied by the probability of its occurrence until branches of the central decision node are reached. Each branch will have a utility value associated with it which represents the overall value, appropriately weighted, of all the possible outcomes occurring distal to it. In the example given, the choice is for radical radiotherapy since it yields 17.8 QALYs compared with 14.4 for radical surgery. Decision analysis includes the fact that we do not know anything with certainty. We are unsure, for example whether an individual patient will survive disease-free 5 years after laryngectomy for Tt carcinoma of the larynx. We may use a probability of 0.9 in our analysis, but only choose this because it represents a compromise within the realistic range of values extending from 0.85 to 0.95. The techniques of sensitivity analysis permit the incorporation of this type of uncertainty into the decision. Having performed the analysis using the baseline value (0.9) we can then perform a series of analyses varying the value between 0.85 and 0.95. This may not affect the choice; alternatively, at some threshold value, the balance may tip from favouring radiotherapy to favouring surgery. In the example, surgery becomes preferable when the primary control rate with radiotherapy falls below 59.8%. More sophisticated versions of sensitivity analysis enable more than one variable to be varied at a time. For example, it is possible to analyse simultaneously (1) the effect of varying the probability of disease-free survival after radiotherapy and (2) the quality factor by which survival must be multiplied for those patients who require laryngectomy. Only when the quality adjustment factor is >0.95 and the primary control rate with radiotherapy is

Decision analysis in oncology: panacea or chimera?

A review of the literature on the use of decision analysis in clinical oncology shows that, although these techniques have been available for more tha...
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