Multicriteria decision analysis in oncology

Integrating Shared Decision-Making into Undergraduate Oncology Education: A Pedagogical Framework

The integration of shared decision-making (SDM) into undergraduate oncology education represents a critical evolution in medical pedagogy, reflecting the growing complexity and patient-centric focus of contemporary healthcare. This paper introduces a comprehensive pedagogical framework designed to embed SDM within the undergraduate medical curriculum, particularly in oncology, where the multiplicity of treatment options and their profound impact on patient life underscore the necessity of this approach. Grounded in a systematic literature review and aligned with established educational theories, this framework proposes twelve strategic approaches to cultivate future physicians proficient in both clinical acumen and patient-collaborative decision-making. The framework emphasizes real-world clinical experience, role-playing, case studies, and decision aids to deepen students' understanding of SDM. It advocates for the development of communication skills, ethical deliberation, and cultural competence, recognizing the multifaceted nature of patient care. The inclusion of patient narratives and evidence-based decision-making further enriches the curriculum, offering a holistic view of patient care. Additionally, the integration of digital tools within the SDM process acknowledges the evolving technological landscape in healthcare. The paper also addresses challenges in implementing this framework, such as curricular constraints and the need for educator training. It underscores the importance of continual evaluation and adaptation of these strategies to the dynamic field of medical education and practice. Overall, this comprehensive approach aims not only to enhance the quality of oncological care but also to prepare medical students for the complexities of modern medicine, where patient involvement in decision-making is both a necessity and an expectation.

Multi-criteria decision analysis method for differential diagnosis of tropical febrile diseases

This paper employs the Analytical Hierarchy Process (AHP) to enhance the accuracy of differential diagnosis for febrile diseases, particularly prevalent in tropical regions where misdiagnosis may have severe consequences. The migration of health workers from developing countries has resulted in frontline health workers (FHWs) using inadequate protocols for the diagnosis of complex health conditions. The study introduces an innovative AHP-based Medical Decision Support System (MDSS) incorporating disease risk factors derived from physicians' experiential knowledge to address this challenge. The system's aggregate diagnostic factor index determines the likelihood of febrile illnesses. Compared to existing literature, AHP models with risk factors demonstrate superior prediction accuracy, closely aligning with physicians' suspected diagnoses. The model's accuracy ranges from 85.4% to 96.9% for various diseases, surpassing physicians' predictions for Lassa, Dengue, and Yellow Fevers. The MDSS is recommended for use by FHWs in communities lacking medical experts, facilitating timely and precise diagnoses, efficient application of diagnostic test kits, and reducing overhead expenses for administrators.

Assessing neuro-oncology clinical trial impact and value: Testing a novel multi-criteria decision analysis app

BACKGROUND

Many clinical trials are conducted globally, creating challenges in deciding which trial outcomes deserve a clinician's focus and where to direct limited resources. Determining the 'value' of a clinical trial relative to others could be useful in this context. The aim of this study was to test a novel web-based application using multi-criteria decision analysis (MCDA) to rank clinical trial value.

METHODS

The MCDA tool combines seven metrics: unmet need; target population size; access; outcomes; cost; academic impact and use of results. Clinical trials were ranked according to their calculated 'value' - meaning the importance or worth of a trial. We determined face validity of the app using a set of ten published Phase 3 neuro-oncology clinical trials. A survey of neuro-oncology clinicians asked them to rank the same ten clinical trials, and to rank the seven metrics in terms of importance.

RESULTS

The two highest app-ranked trials were in concordance with that of the survey respondents, and consistent with the two studies that have had the most impact on routine clinical practice in neuro-oncology. Of the seven metrics, surveyed clinicians considered patient outcomes and unmet need to be the most important when determining clinical trial value.

CONCLUSIONS

The metrics app was able to rank and produce a numerical 'value' for existing phase 3 neuro-oncology clinical trials. In the future, a related app to prospectively rank future trials at the startup stage could be developed to help centers determine which should be prioritized to be conducted at their site.

Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value

BACKGROUND

Demonstrating safety and efficacy of new medical treatments requires clinical trials but clinical trials are costly and may not provide value proportionate to their costs. As most health systems have limited resources, it is therefore important to identify the trials with the highest value. Tools exist to assess elements of a clinical trial such as statistical validity but are not wholistic in their valuation of a clinical trial. This study aims to develop a measure of clinical trials value and provide an online tool for clinical trial prioritisation.

METHODS

A search of the academic and grey literature and stakeholder consultation was undertaken to identify a set of criteria to aid clinical trial valuation using multi-criteria decision analysis. Swing weighting and ranking exercises were used to calculate appropriate weights of each of the included criteria and to estimate the partial-value function for each underlying metric. The set of criteria and their respective weights were applied to the results of six different clinical trials to calculate their value.

RESULTS

Seven criteria were identified: 'unmet need', 'size of target population', 'eligible participants can access the trial', 'patient outcomes', 'total trial cost', 'academic impact' and 'use of trial results'. The survey had 80 complete sets of responses (51% response rate). A trial designed to address an 'Unmet Need' was most commonly ranked as the most important with a weight of 24.4%, followed by trials demonstrating improved 'Patient Outcomes' with a weight of 21.2%. The value calculated for each trial allowed for their clear delineation and thus a final value ranking for each of the six trials.

CONCLUSION

We confirmed that the use of the decision tool for valuing clinical trials is feasible and that the results are face valid based on the evaluation of six trials. A proof-of-concept applying this tool to a larger set of trials with an external validation is currently underway.

Breast cancer treatment planning using a novel spherical fuzzy CRITIC-REGIME

Breast cancer is the leading cause of cancer-related deaths, and choosing a suitable treatment plan for this disease has proved difficult for oncologists owing to the variety of criteria and alternatives that must be considered during the decision-making process. Since prospective treatment options influence patients’ health-related quality of life in a variety of ways, a methodology that can completely and objectively evaluate alternative treatments has become an essential issue. This paper proposes a novel multi-criteria decision-making (MCDM) methodology by integrating the CRiteria Importance Through Intercriteria Correlation (CRITIC) and the REGIME techniques and handles the problem of breast cancer treatment selection problem. CRITIC enables the determination of objective criterion weights based on the decision matrix, while REGIME ranks the options without the need for lengthy computations or normalization procedures. The suggested methodology is demonstrated in a spherical fuzzy atmosphere, which allows decision experts to independently express their degrees of membership, non-membership, and hesitancy in a broad three-dimensional spherical space. In the numerical example provided, three oncologists evaluate four breast cancer treatment alternatives, namely, surgery, radiotherapy, chemotherapy, and hormone therapy, with respect to five criteria, which are disease or tumor type, stage of disease, patient type, side effects, and financial status of the patient. The tumor type is determined to be the most important assessment criterion, and surgery is selected as the best course of action. The stability and validity of the proposed methodology are verified through sensitivity and comparative studies. The discussions, limitations, and future research avenues are also given within the study.

Treatment Preference for Alzheimer's Disease: A Multicriteria Decision Analysis with Caregivers, Neurologists, and Payors

INTRODUCTION

Alzheimer's disease (AD) is a chronic neurodegenerative disorder associated with a high burden of illness. New therapies under development include agents that target amyloid-beta (Aβ), a key component in AD pathogenesis. Understanding the decision-making process for new AD drugs would help determine if such therapies should be adopted by society. Multicriteria decision analysis (MCDA) was applied to three key stakeholder groups to assess treatment alternatives for AD based on a multitude of decision trade-offs covering main components of care.

METHODS

AD caregivers (n = 117), neurologists (n = 90), and payors (n = 90) from the USA received an online survey. The decision problem was broken down into four decision criterion and 12 subcriteria for two treatment scenarios: an Aβ-targeted therapy vs. the standard of care (SOC). Respondents were asked to indicate how much they preferred one option over another on a scale from 1 (equal preference) to 9 (high preference) based on each criterion and subcriterion. The decision criteria and subcriteria were weighted and presented as partial utility scores (pUS), with higher scores suggesting an increased preference for that decision-making component.

RESULTS

Caregivers and payors applied the highest value to need for intervention (mean pUS = 0.303 and 0.259) and clinical outcomes (mean pUS = 0.286 and 0.377). In contrast, neurologists placed the highest value on clinical outcomes and types of benefits (mean pUS = 0.436 and 0.248). When decision subcriteria were examined, efficacy (mean pUS = 0.115, 0.219, and 0.166) and the type of patient benefits (mean pUS = 0.135, 0.178, and 0.126) were among the most valued by caregivers, neurologists, and payors.

CONCLUSION

All groups placed the highest value on drug efficacy and types of benefit derived by patients. In contrast, cost implications were among the least important aspects in their decision-making.

Cost-Effectiveness Analysis of Pertuzumab Plus Trastuzumab and Docetaxel Compared With Trastuzumab and Docetaxel in the Adjuvant Treatment of Human Epidermal Growth Factor Receptor 2-Positive Metastatic Breast Cancer in Colombia

OBJECTIVES

The addition of pertuzumab to the scheme of docetaxel plus trastuzumab (TH) in patients with metastatic breast cancer with overexpression of human epidermal growth factor receptor 2 increases survival. Nevertheless, this addition could represent a high cost for the health system of a middle-income country such as Colombia. Therefore, it is necessary to evaluate the efficiency of the pertuzumab plus TH (PTH) scheme in comparison with TH.

METHODS

A partitioned survival model-based cost-utility analysis was performed. Progression-free survival and overall survival curves for each scheme were obtained from the CLEOPATRA study. The time horizon was 30 years with a discount rate of 5% for costs and quality-adjusted life-years. Total direct costs were calculated using national tariffs. Utilities were obtained from external sources. Model uncertainty was evaluated by deterministic and probabilistic sensitivity analysis. A willingness to pay value of 5180 US dollars was used.

RESULTS

The discounted total average costs of TH and PTH were $24 109 and $60 846, respectively. These regimens' average life-years were 5.78 and 8.38, and their quality-adjusted life-years were 3.28 and 4.51, respectively. The incremental cost-effectiveness ratio was $29 867. One-way sensitivity analysis showed that the cost of pertuzumab was the variable that explained the uncertainty in the model. The probability that PTH is cost-effective in the probabilistic sensitivity analysis is 0.0724.

CONCLUSIONS

The addition of pertuzumab to the TH regimen in patients with human epidermal growth factor receptor 2-positive metastatic breast cancer has a low probability of being cost-effective from the payer's perspective in the Colombian health system.

Decision criteria for resource allocation: an analysis of CONITEC oncology reports

In health technology assessment (HTA), decision criteria are considered relevant to support the complex deliberative process that requires simultaneous consideration of multiple factors. The aim was to identify and analyze the decision criteria that have been used by the National Health Technology Assessment Commission (CONITEC) when recommending the incorporation of technologies for the treatment of cancer. Descriptive study, based on reports from CONITEC, between 2012 and 2018, on oncology technologies. The data were collected in a specific extraction form and analyzed using descriptive statistics. 39 reports were analyzed, 15 of them did not present any explicit decision criteria. Medicines were the most frequently evaluated type of technology. The most frequent types of cancers were: breast cancer, head and neck cancer, colorectal cancer, non-Hodgkin's lymphoma and lung cancer. The most frequently considered criteria were: financial impact and effectiveness. The study identified the decision criteria that have been most used in the area of ​​oncology, however, the lack of transparency in relation to the weight of these criteria makes it difficult to understand their influence on the result of the decisions taken.

Evaluating the Efficacy of Probiotics in IBS Treatment Using a Systematic Review of Clinical Trials and Multi-Criteria Decision Analysis

The evaluation of probiotics' efficacy in treating irritable bowel syndrome is supported by an increasing number of clinical studies based on a heterogeneous approach of products tested and the patient cohort involved. Although the role of gut microbiota dysbiosis in IBS pathogenesis and the beneficial contribution of probiotics were demonstrated, a tool to discriminate symptom-specific strains and a personalised medicine protocol are still lacking. Thus, this study employs, for the first time, a method that combines the preferred reporting items for systematic reviews and meta-analysis and multi-criteria decision analysis methods in a structured decision-making tool to analyze the efficacy of probiotic mix, in order to identify the most effective formulation and to discriminate which probiotics are more efficient in treating different symptoms. The PRISMA methodology resulted in a qualitative and quantitative analysis of 104 clinical studies from 2011 to 2021, revealing a prevalence of Lactobacillus rhamnosus, Lactobacillus acidophilus, and Bifidobacterium animalis subsp. lactis. MCDA analysis showed that formulations based on Lactobacillus rhamnosus and Lactobacillus acidophilus have the highest efficacy, especially on quality of life, bloating, and abdominal pain. This methodological approach could become more specific by modelling clinical studies according to the age and gender of patients and probiotic strain.

Early Access to Medicines: Use of Multicriteria Decision Analysis (MCDA) as a Decision Tool in Catalonia (Spain)

Early access to medicines allows the prescription of a medicine before it is available in the public formulary to patients with severe or rare diseases with high unmet needs who have no authorised therapeutic alternatives available. In this context, consistent decision making is difficult, and a systematic assessment procedure could be useful to tackle complex situations and guarantee the equity of medicines’ access. A multidisciplinary panel (MP) conducted four workshops to develop an early access framework based on a reflective multiple criteria decision analysis (MCDA). A set of 12 criteria was agreed: eight quantitative (severity of disease, urgency, efficacy, safety, internal and external validity, therapeutic benefit and plausibility) and four qualitative (therapeutic alternative, existence of precedents, management impact and costs). Quantitative criteria were weighted using a five-point scale. The relative importance of quantitative criteria had mean weights from 4.7 to 3.6, showing its relevance in the decisions. The framework was tested using two case studies, and reliability was assessed by re-test. The re-test revealed no statistical differences, indicating the consistency and replicability of the framework developed. MCDA may help to structure discussions for heterogeneous treatment requests, providing predictability and robustness in decision making involving sensitive and complex situations.

Decision criteria for resource allocation: an analysis of CONITEC oncology reports

Abstract In health technology assessment (HTA), decision criteria are considered relevant to support the complex deliberative process that requires simultaneous consideration of multiple factors. The aim was to identify and analyze the decision criteria that have been used by the National Health Technology Assessment Commission (CONITEC) when recommending the incorporation of technologies for the treatment of cancer. Descriptive study, based on reports from CONITEC, between 2012 and 2018, on oncology technologies. The data were collected in a specific extraction form and analyzed using descriptive statistics. 39 reports were analyzed, 15 of them did not present any explicit decision criteria. Medicines were the most frequently evaluated type of technology. The most frequent types of cancers were: breast cancer, head and neck cancer, colorectal cancer, non-Hodgkin’s lymphoma and lung cancer. The most frequently considered criteria were: financial impact and effectiveness. The study identified the decision criteria that have been most used in the area of oncology, however, the lack of transparency in relation to the weight of these criteria makes it difficult to understand their influence on the result of the decisions taken.

Multicriteria decision analysis in health care decision in oncology: a systematic review

INTRODUCTION

Multicriteria decision analysis (MCDA) has been used to inform health decisions in health technology assessments (HTA) processes. This is particularly important to complex treatment decisions in oncology.

AREAS COVERED

Five databases (PubMed, EMBASE, LILACS, Web of Science and CRD's NHS Economic Evaluation Database) were searched for studies comparing health technologies in oncology, involving the concept MCDA. The ISPOR MCDA Good Practices Guidelines were used to assess the reporting quality. Study selection, appraisal, and data extraction were performed by two reviewers. Fifteen studies were included. The main decision problem was related to health technology assessment of cancer treatments. Clinicians and public health experts were the most frequent stakeholders. The most frequently included criteria comprised therapeutic benefit, and socio-economic impact. Value measurement approach, direct rating techniques, and additive model for aggregation were used in most studies. Uncertainty analysis revealed the impact of posology and costs on the studies' results. All studies showed some level of overlapping decision criteria.

EXPERT OPINION

There is considerable diversity of methods in MCDA for healthcare decision-making in oncology. The evidence presented can serve as a resource when considering which stakeholders, criteria, and techniques to include in future MCDA studies in oncology.

How to Value Orphan Drugs? A Review of European Value Assessment Frameworks

Background: Decision-makers have implemented a variety of value assessment frameworks (VAFs) for orphan drugs in European jurisdictions, which has contributed to variations in access for rare disease patients. This review provides an overview of the strengths and limitations of VAFs for the reimbursement of orphan drugs in Europe, and may serve as a guide for decision-makers.

Methods: A narrative literature review was conducted using the databases Pubmed, Scopus and Web of Science. Only publications in English were included. Publications known to the authors were added, as well as conference or research papers, or information published on the website of reimbursement and health technology assessment (HTA) agencies. Additionally, publications were included through snowballing or focused searches.

Results: Although a VAF that applies a standard economic evaluation treats both orphan drugs and non-orphan drugs equally, its focus on cost-effectiveness discards the impact of disease rarity on data uncertainty, which influences an accurate estimation of an orphan drug’s health benefit in terms of quality-adjusted life-years (QALYs). A VAF that weighs QALYs or applies a variable incremental cost-effectiveness (ICER) threshold, allows the inclusion of value factors beyond the QALY, although their methodologies are flawed. Multi-criteria decision analysis (MCDA) incorporates a flexible set of value factors and involves multiple stakeholders’ perspectives. Nevertheless, its successful implementation relies on decision-makers’ openness toward transparency and a pragmatic approach, while allowing the flexibility for continuous improvement.

Conclusion: The frameworks listed above each have multiple strengths and weaknesses. We advocate that decision-makers apply the concept of accountability for reasonableness (A4R) to justify their choice for a specific VAF for orphan drugs and to strive for maximum transparency concerning the decision-making process. Also, in order to manage uncertainty and feasibility of funding, decision-makers may consider using managed-entry agreements rather than implementing a separate VAF for orphan drugs.

Combining Quantitative Risk Assessment of Human Health, Food Waste, and Energy Consumption: The Next Step in the Development of the Food Cold Chain?

The preservation of perishable food via refrigeration in the supply chain is essential to extend shelf life and provide consumers with safe food. However, electricity consumed in refrigeration processes has an economical and an environmental impact. This study focuses on the cold chain of cooked ham, including transport, cold room in supermarket, display cabinet, transport by consumer, and domestic refrigerator, and aims to predict the risk for human health associated with Listeria monocytogenes, the amount of food wasted due to the growth of spoilage bacteria, and the electrical consumption to maintain product temperature through the cold chain. A set of eight intervention actions were tested to evaluate their impact on the three criteria. Results show that the modification of the thermostat of the domestic refrigerator has a high impact on food safety and food waste and a limited impact on the electrical consumption. Inversely, the modification of the airflow rate in the display cabinet has a high impact on electrical consumption and a limited impact on food safety and food waste. A cost-benefit analysis approach and two multicriteria decision analysis methods were used to rank the intervention actions. These three methodologies show that setting the thermostat of the domestic refrigerator to 4 °C presents the best compromise between the three criteria. The impact of decisionmaker preferences (criteria weight) and limitations of these three approaches are discussed. The approaches proposed by this study may be useful in decision making to evaluate global impact of intervention actions in issues involving conflicting outputs.

Multi-criteria decision analysis (MCDA): testing a proposed MCDA framework for orphan drugs

Background

Since the introduction of the orphan drugs legislation in Europe, it has been suggested that the general method of assessing drugs for reimbursement is not necessarily suitable for orphan drugs. The National Institute for Health and Clinical Excellence indicated that several criteria other than cost and efficacy could be considered in reimbursement decisions for orphan drugs. This study sought to explore the multi-criteria decision analysis (MCDA) framework proposed by (Orphanet J Rare Dis 7:74, 2012) to a range of orphan drugs, with a view to comparing the aggregate scores to the average annual cost per patient for each product, and thus establishing the merit of MCDA as a tool for assessing the value of orphan drugs in relation to their pricings.

Methods

An MCDA framework was developed using the nine criteria proposed by (Orphanet J Rare Dis 7:74, 2012) for the evaluation of orphan drugs, using the suggested numerical scoring system on a scale of 1 to 3 for each criterion. Correlations between the average annual cost of the drugs and aggregate MCDA scores were tested and plotted graphically. Different weightings for each of the attributes were also tested. A further analysis was conducted to test the impact of including the drug cost as an attribute in the aggregate index scores.

Results

In the drugs studied, the R², that statistically measures how close the data are to the fitted regression line was 0.79 suggesting a strong correlation between the drug scores and the average annual cost per patient.

Conclusion

Despite several limitations of the proposed model, this quantitative study provided insight into using MCDA and its relationship to the average annual costs of the products.

Discrepancies between multicriteria decision analysis-based ranking and intuitive ranking for pharmaceutical benefit-risk profiles in a hypothetical setting

WHAT IS KNOWN AND OBJECTIVE

Multicriteria decision analysis (MCDA) has been generally considered a promising decision-making methodology for the assessment of drug benefit-risk profiles. There have been many discussions in both public and private sectors on its feasibility and applicability, but it has not been employed in official decision-makings. For the purpose of examining to what extent MCDA would reflect the first-hand, intuitive preference of evaluators in practical pharmaceutical assessments, we conducted a questionnaire survey involving the participation of employees of pharmaceutical companies.

METHODS

Showing profiles of the efficacy and safety of four hypothetical drugs, each respondent was asked to rank them following the standard MCDA process and then to rank them intuitively (i.e. without applying any analytical framework).

RESULTS AND DISCUSSION

These two approaches resulted in substantially different ranking patterns from the same individuals, and the concordance rate was surprisingly low (17%). Although many respondents intuitively showed a preference for mild, balanced risk-benefit profiles over profiles with a conspicuous advantage in either risk or benefit, the ranking orders based on MCDA scores did not reflect the intuitive preference.

WHAT IS NEW AND CONCLUSION

Observed discrepancies between the rankings seemed to be primarily attributed to the structural characteristics of MCDA, which assumes that evaluation on each benefit and risk component should have monotonic impact on final scores. It would be difficult for MCDA to reflect commonly observed non-monotonic preferences for risk and benefit profiles. Possible drawbacks of MCDA should be further investigated prior to the real-world application of its benefit-risk assessment.

The Value of Medicines: A Crucial but Vague Concept

Health Technology Assessment is increasingly used to evaluate the value of healthcare products and to prioritize resources; however, defining exactly what value is and how it should be measured remains a challenge. In this article, we report the results of a literature review, focusing on nine European countries, with the aim of investigating how value is defined from the perspective of different stakeholders, how definitions of value are used, and how value is incorporated into decision making. Only three articles were identified that presented definitions of value, and there was no single shared definition of value in healthcare, which appears to be a highly subjective concept. The majority of the countries investigated combine clinical assessment with economic evaluation to make reimbursement recommendations; the quality-adjusted life-year is the most commonly used measure of value but does not capture broader aspects of value that may be important to patients and healthcare systems. We describe the use of value-based pricing and multi-criteria decision analysis, two approaches to the incorporation of broader aspects of value into decision making. Overall, we have identified considerable variation in how a product's value is defined by different stakeholders. Although a universal understanding of value in healthcare is important, it is clear that current definitions are insufficient, potentially leading to inconsistent reimbursement decisions. Ultimately, the establishment of clearer policies for defining and measuring value in healthcare is needed, and is likely to lead to improvements in the consistency of decision making.

Addressing preference heterogeneity in public health policy by combining Cluster Analysis and Multi-Criteria Decision Analysis: Proof of Method

The use of subgroups based on biological-clinical and socio-demographic variables to deal with population heterogeneity is well-established in public policy. The use of subgroups based on preferences is rare, except when religion based, and controversial. If it were decided to treat subgroup preferences as valid determinants of public policy, a transparent analytical procedure is needed. In this proof of method study we show how public preferences could be incorporated into policy decisions in a way that respects both the multi-criterial nature of those decisions, and the heterogeneity of the population in relation to the importance assigned to relevant criteria. It involves combining Cluster Analysis (CA), to generate the subgroup sets of preferences, with Multi-Criteria Decision Analysis (MCDA), to provide the policy framework into which the clustered preferences are entered. We employ three techniques of CA to demonstrate that not only do different techniques produce different clusters, but that choosing among techniques (as well as developing the MCDA structure) is an important task to be undertaken in implementing the approach outlined in any specific policy context. Data for the illustrative, not substantive, application are from a Randomized Controlled Trial of online decision aids for Australian men aged 40-69 years considering Prostate-specific Antigen testing for prostate cancer. We show that such analyses can provide policy-makers with insights into the criterion-specific needs of different subgroups. Implementing CA and MCDA in combination to assist in the development of policies on important health and community issues such as drug coverage, reimbursement, and screening programs, poses major challenges -conceptual, methodological, ethical-political, and practical - but most are exposed by the techniques, not created by them.

Clinical preference for factors in treatment of geriatric depression

Little is known about symptom preferences of clinical psychiatrists in the treatment of geriatric depression and preferences for avoiding adverse drug effects. Participants (board-certified psychiatrists) were recruited prior to a lecture on geriatric depression during a continuing education program. An analytic hierarchy process was performed and participants were asked for pairwise comparison of criteria guiding them in appraising therapeutic efficacy, and in avoiding toxicity and adverse events. Of the 61 participants from the continuing education program, 42 (69%) returned their data sheet. Avoidance of cardiotoxicity was regarded as more important than avoidance of hepatotoxicity or hematotoxicity. Concerning adverse events, highest preference was given to avoidance of falls and drug interactions, followed by avoidance of sedation, weight change, and impairment of sexual function. The most important preferences for appraisal of therapeutic efficacy were suicidality over ability to concentrate and sleep. Clinical psychiatrists have a hierarchy of preferences for treatment goals and avoidance of adverse events and toxicity. This raises the question for future research whether these preferences cause differences in prescription patterns in clinical practice even though a multitude of antidepressants are similarly effective when judged with instruments used in clinical trials.