Patient preferences for the pharmacological treatment of osteoarthritis using adaptive choice-based conjoint (ACBC) analysis: A pilot study

Background: Patient preferences for pharmaceutical treatment of osteoarthritis have been investigated using Conjoint Analysis. Studies have identified the importance of side effects in determining preferences, but noted that methodological limitations precluded further investigation of additional attributes such as hepatic and renal toxicity. Objective: Following on from a feasibility study of adaptive choice-based conjoint (ACBC) analysis, the aim of this study was to evaluate 8 medication attributes for the pharmaceutical treatment of osteoarthritis (OA). Setting and Participants: Eleven participants were recruited from members of a Research Users’ Group (RUG) who had been diagnosed with osteoarthritis. RUG members individually complete the ACBC task. Main outcome measures: The relative importance of each attribute and the utilities (part-worth) of each level of each attribute were estimated using ACBC built-in Hierarchical Bayes (HB). Results: The combined relative importance of the 4 risk side-effect attributes when selecting osteoarthritis medication (kidney and liver side effects, heart attack and stroke side effects, stomach side effects and addiction) was 66% while the effectiveness attribute accounted for 8% of the relative importance of the medication decision. Conclusions: In this study, the gap between relative importance of 4 side-effect attributes and expected benefit was 66% vs 8%. These preliminary findings indicate that OA patients are most concerned with the avoidance of adverse events and that there is a threshold above which expected benefit has little impact on patients’ medication preferences. The study highlights methodological features of ACBC that may be useful more generally in health services research, but the results must be interpreted in conjunction with the study limitations

Patients’ Preferences Regarding Osteoarthritis Medications: An Adaptive Choice-Based Conjoint Analysis Study

Background and Objective: Osteoarthritis (OA) patients consider ranges of harms and benefits offered by alternative pharmaceutical treatments. Choice-based experiments provide a mechanism to value outcomes, but they can pose a significant burden on respondents. Thus, the number of attributes studied is typically artificially restricted. We used an adaptive choice-based conjoint (ACBC) method that allows the inclusion of more attributes affecting patients’ preferences regarding non-invasive pharmaceutical treatment for OA than traditional choice-based technique to better understand the trade-offs that OA patients consider, without increasing respondents’ burden. Methods: After consulting with OA patients and public involvement (PPI) group, we constructed an online ACBC survey consisting of 9 attributes and a total of 31 levels (two benefits, four harms and three concerning the availability and modality of treatment). A cohort of patients with a diagnosis of OA and reporting joint pain within the last 12 months were recruited. Results: Our study (n 43) showed that the most important factor in choosing OA medication was the risk of heart attacks and strokes (19.5%), followed by the risk of addiction (18.4%), risk of kidney and liver side effects (17.5%), risk stomach side effects (14.6%), availability (11.6%), frequency of use (5.3%), pain reduction (5%), way of taking medication (4.6%) and mobility improvement (3.5%). Conclusion: ACBC provides a mechanism for understanding patient preferences that address the limitations of traditional choice-based experiments. For OA patients, avoidance of the risk of side effects were the most affecting medication choices, and reductions in pain and mobility were the least. Clinicians discussing options for medication with OA patients should discuss the potential trade-offs in terms of risks and benefits

Nursing people with osteoarthritis

Osteoarthritis (OA) refers to a clinical syndrome of joint pain accompanied by varying degrees of functional limitation and reduced quality of life (National Institute for Health and Care Excellence (NICE), 2014). The most affected peripheral joints are the knees, hips, and small hand joints. Pain, reduced function, and effects on a person's ability to carry out their day-to-day activities can be important consequences. Pain in itself is also a complex biopsychosocial issue, related in part to a person's expectations and self-efficacy (that is, their belief in their ability to complete tasks and reach goals), and is associated with changes in mood, sleep and coping abilities. There is often a poor link between changes visible on an X-ray and symptoms of osteoarthritis: minimal changes can be associated with a lot of pain, or modest structural changes to joints can occur with minimal accompanying symptoms. Contrary to popular belief, OA is not caused by ageing and does not necessarily deteriorate (NICE, 2014)

Systematic Review of Studies Using Conjoint Analysis Techniques to Investigate Patients’ Preferences Regarding Osteoarthritis Treatment

Background: The use of conjoint analysis (CA) to elicit patients’ preferences for osteoarthritis (OA) treatment has the potential to contribute to tailoring treatments and enhancing patients’ compliance and adherence. This review’s main aim was to identify and summarise the evidence that used conjoint analysis techniques to quantify patient preferences for OA treatments. Methods: A comprehensive search strategy was conducted using electronic databases and hand reference checks. Databases were searched from their inception until 10th June 2019. All OA and CA related terms were used to conduct the search. The authors reviewed the papers and used the International Society of Pharmacoeconomics and Outcomes Research (ISPOR) checklist to assess the quality of the included studies. Results: The search identified 534 records. Sixteen records were selected for full-text review and quality assessment and all were included in the narrative data synthesis. All included studies suggested that the severity of symptoms influenced the patients’ preference for OA treatment. All included studies recognised CA as a useful method to investigate patients’ preferences concerning OA treatment. Conclusion: Patients preference for OA treatment is driven by the severity of patients’ symptoms and the desire to avoid treatment side effects and CA is a useful tool to investigate patients’ preferences for OA treatment

The Role of Web-Based Adaptive Choice-Based Conjoint Analysis Technology in Eliciting Patients’ Preferences for Osteoarthritis Treatment

Objective: To assess the feasibility of using adaptive choice-based conjoint (ACBC) analysis to elicit patients’ preferences for pharmacological treatment of osteoarthritis (OA), patients’ satisfaction with completing the ACBC questionnaire, and factors associated with questionnaire completion time. Methods: Adult patients aged 18 years and older with a medical diagnosis of OA, experiencing joint pain in the past 12 months, and living in the Northeast of England participated in the study. The participants completed a web-based ACBC questionnaire about their preferences regarding pharmaceutical treatment for OA using a touchscreen laptop independently, and accordingly, the questionnaire completion time was measured. Moreover, the participants completed a pen-and-paper feedback form about their experience in completing the ACBC questionnaire. Results: Twenty participants aged 40 years and older, 65% females, 75% had knee OA, and suffering from OA for more than 5 years participated in the study. About 60% of participants reported completing a computerized questionnaire in the past. About 85% of participants believed that the ACBC task helped them in making decisions regarding their OA medications, and 95% agreed or strongly agreed that they would be happy to complete a similar ACBC questionnaire in the future. The average questionnaire completion time was 16 min (range 10–24 min). The main factors associated with longer questionnaire completion time were older age, never using a computer in the past, and no previous experience in completing a questionnaire. Conclusions: The ACBC analysis is a feasible and efficient method to elicit patients’ preferences for pharmacological treatment of OA, which could be used in clinical settings to facilitate shared decision-making and patient-centered care. The ACBC questionnaire completion consumes a significantly longer time for elderly participants, who never used a computer, and never completed any questionnaire previously. Therefore, the contribution of patients and public involvement (PPI) group in the development of the ACBC questionnaire could facilitate participants’ understanding and satisfaction with the task. Future research including patients with different chronic conditions may provide more useful information about the efficiency of ACBC analysis in eliciting patients’ preferences for osteoarthritis treatment

Using Adaptive Choice Based Conjoint (ACBC) analysis to predict individual patient preferences for pharmaceutical treatment of osteoarthritis

Background: Eliciting individual patient preferences is important alongside eliciting group preferences. Group results are used to understand general population preferences and develop guidelines, while individual patient preferences assist patient-clinician shared decision-making. Aim: To examine whether predicted preferences derived from individual patients through ACBC match their expressed preferences for pharmaceutical treatment of osteoarthritis. Methods: 11 participants with osteoarthritis (over 50 years of age) were recruited from the Research Users’ Group at the Arthritis Research UK Primary Care Centre, Keele University. Participants completed a computerised interactive ACBC questionnaire involving 8 attributes: medication availability, frequency, route of administration, expected benefit, risk of addiction, risk of stomach side effects, risk of kidney and liver side effects, and risk of heart attacks and strokes. Individual data were analysed using monotone regression. Patients were individually interviewed after being shown the ACBC predicted results. Results: For each individual, the ACBC-predicted individual patient’s preferences were in concordance with his or her expressed preferences of different attributes. Furthermore, ACBC assisted patients to trade-off attributes-levels against each other and make decisions about their preferences. Conclusion: ACBC is a practical tool that can be used in primary care to analyse individual patient preference prior to consultation, without unduly consuming clinicians' time

Using adaptive choice based conjoint (ACBC) analysis to study patients’ preferences regarding pharmaceutical treatment for osteoarthritis (OA)

Background: Adaptive Choice Based Conjoint (ACBC) is a technique for eliciting and quantifying people’s preferences. This is the first application of ACBC in rheumatology research. The advantage of this method is that it adapts to patients’ responses to different medication scenarios. This research is concerned with the extent to which the benefits of medication are traded-off against serious adverse effects such as kidney impairment and stroke. Objectives: To determine the relative importance of 8 medication attributes, using the Adaptive Choice Based Conjoint. Methods: 11 participants were recruited from the Research User Group (RUG) at the Arthritis Research UK Primary Care Centre, Keele University, UK, to evaluate a newly developed ACBC questionnaire. Participants were over 50 years of age and suffering from OA in at least one of their joints. Participants completed an ACBC questionnaire involving 8 attributes: medication availability, frequency, route of administration, expected benefit, risk of addiction, risk of stomach side effects, risk of kidney and liver side effects, and risk of heart attacks and strokes. The relative importance of the 8 attributes, which sum to 100%, was calculated using Hierarchical Bayes (HB) estimation. Results: Rather than medication benefits being the top priority, the greatest impact on patients’ preference regarding medication was the risk of kidney and liver side effects (22%), followed by the risk of heart attacks and strokes (17%), then the risk of stomach side effects (16%). The route of administration, frequency, and expected benefit were the least important factors influencing patients’ preference (7%). Conclusions: ACBC reveals information about patients’ preferences and the precise trade-offs that patients are willing to make. For example, OA patients are willing to trade off the benefits of medication for low risks of adverse effects. The benefits that patients expect from the medication are not very important when traded-off against serious medication adverse effects such as kidney and liver side effects. This shows the importance of making patients aware of OA medication side effects within the context of other treatment options

An updated pharmacological insight into calotropin as a potential therapeutic agent in cancer

Calotropin is a pharmacologically active compound isolated from milkweed plants like Calotropis procera, Calotropis gigantea, and Asclepias currasavica that belong to the Asclepiadaceae family. All of these plants are recognised as medical traditional plants used in Asian countries. Calotropin is identified as a highly potent cardenolide that has a similar chemical structure to cardiac glycosides (such as digoxin and digitoxin). During the last few years, cytotoxic and antitumor effects of cardenolides glycosides have been reported more frequently. Among cardenolides, calotropin is identified as the most promising agent. In this updated and comprehensive review, we aimed to analyze and discuss the specific mechanisms and molecular targets of calotropin in cancer treatment to open new perspectives for the adjuvant treatment of different types of cancer. The effects of calotropin on cancer have been extensively studied in preclinical pharmacological studies in vitro using cancer cell lines and in vivo in experimental animal models that have targeted antitumor mechanisms and anticancer signaling pathways. The analyzed information from the specialized literature was obtained from scientific databases until December 2022, mainly from PubMed/MedLine, Google Scholar, Scopus, Web of Science, and Science Direct databases using specific MeSH search terms. The results of our analysis demonstrate that calotropin can be a potential chemotherapeutic/chemopreventive adjunctive agent in cancer pharmacotherapeutic management

Systematic review of studies investigating ventilator associated pneumonia diagnostics in intensive care

Abstract Background Ventilator-associated pneumonia (VAP) is an important diagnosis in critical care. VAP research is complicated by the lack of agreed diagnostic criteria and reference standard test criteria. Our aim was to review which reference standard tests are used to evaluate novel index tests for suspected VAP. Methods We conducted a comprehensive search using electronic databases and hand reference checks. The Cochrane Library, MEDLINE, CINHAL, EMBASE, and web of science were searched from 2008 until November 2018. All terms related to VAP diagnostics in the intensive treatment unit were used to conduct the search. We adopted a checklist from the critical appraisal skills programme checklist for diagnostic studies to assess the quality of the included studies. Results We identified 2441 records, of which 178 were selected for full-text review. Following methodological examination and quality assessment, 44 studies were included in narrative data synthesis. Thirty-two (72.7%) studies utilised a sole microbiological reference standard; the remaining 12 studies utilised a composite reference standard, nine of which included a mandatory microbiological criterion. Histopathological criteria were optional in four studies but mandatory in none. Conclusions Nearly all reference standards for VAP used in diagnostic test research required some microbiological confirmation of infection, with BAL culture being the most common reference standard used