Redevelopment of the Predict: Breast Cancer website and recommendations for developing interfaces to support decision-making

Information and communication priorities of patients and healthcare professionals in shared decision making regarding adjuvant systemic breast cancer treatment: A survey study

PURPOSE

To assess information and communication priorities of patients and healthcare professionals in Shared Decision Making about adjuvant systemic treatment of primary breast cancer and identify key decision-relevant information accordingly.

METHODS

Patients (N = 122) and professionals working with breast cancer patients (N = 118), of whom 38 were nurse practitioners and 32 nurses, were recruited using convenience sampling, and surveyed about information/communication aspects key to decision-making, using ranking assignments. We further posed a simple open question, questions about receiving population-based statistics versus personalized statistics concerning treatment outcomes, and their attitude and experience concerning Shared Decision Making. Data were analyzed using descriptive analysis and a qualitative analysis.

RESULTS

Both patients and professionals prioritized information about treatment outcomes (i.e., survival, recurrence) as key decision-relevant information for patients. Patients prioritized information about relatively severe treatment side-effects and late effects (e.g., blood clot, stroke), whilst professionals prioritized information about effects that occur relatively often (e.g., hair loss, fatigue). Patients specifically wanted to know if the benefit of treatment is worth the negative impact. Both groups prioritized personalized statistics over population-based statistics.

CONCLUSIONS

Some differences between patients and professionals were found in information and communication priorities, specifically related to the different side-effects. It seems worthwhile to precisely address these side-effects in Shared Decision Making concerning adjuvant systemic treatment. Furthermore, it seems important to deliberate together on the question if expected benefit of treatment is worth the potential negative impact for the individual patient.

Trust and acceptability of data-driven clinical recommendations in everyday practice: A scoping review

BACKGROUND

Increasing attention is being given to the analysis of large health datasets to derive new clinical decision support systems (CDSS). However, few data-driven CDSS are being adopted into clinical practice. Trust in these tools is believed to be fundamental for acceptance and uptake but to date little attention has been given to defining or evaluating trust in clinical settings.

OBJECTIVES

A scoping review was conducted to explore how and where acceptability and trustworthiness of data-driven CDSS have been assessed from the health professional's perspective.

METHODS

Medline, Embase, PsycInfo, Web of Science, Scopus, ACM Digital, IEEE Xplore and Google Scholar were searched in March 2022 using terms expanded from: "data-driven" AND "clinical decision support" AND "acceptability". Included studies focused on healthcare practitioner-facing data-driven CDSS, relating directly to clinical care. They included trust or a proxy as an outcome, or in the discussion. The preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) is followed in the reporting of this review.

RESULTS

3291 papers were screened, with 85 primary research studies eligible for inclusion. Studies covered a diverse range of clinical specialisms and intended contexts, but hypothetical systems (24) outnumbered those in clinical use (18). Twenty-five studies measured trust, via a wide variety of quantitative, qualitative and mixed methods. A further 24 discussed themes of trust without it being explicitly evaluated, and from these, themes of transparency, explainability, and supporting evidence were identified as factors influencing healthcare practitioner trust in data-driven CDSS.

CONCLUSION

There is a growing body of research on data-driven CDSS, but few studies have explored stakeholder perceptions in depth, with limited focused research on trustworthiness. Further research on healthcare practitioner acceptance, including requirements for transparency and explainability, should inform clinical implementation.

"All about the value?" Decisional needs of breast reconstruction for breast cancer patients in the Chinese context: A mixed-methods study

OBJECTIVE

To explore breast cancer (BC) patients' participation in breast reconstruction (BR) decision-making and specific decisional needs, especially the manifestations and causes of decisional conflicts, in China.

METHODS

A mixed-methods study was conducted using triangulation of data from interviews and a questionnaire survey with health care professionals (HCPs) and BC patients with BR decision-making experience at 5 Beijing centers. The Ottawa Decision Support Framework guided (ODSF) the qualitative and quantitative data analyses.

RESULTS

A total of 82.53% of Chinese BC patients would consider BR. Seven themes captured patients' BR decisional needs per the ODSF: inadequate support/resources (100%, 58.82%) and knowledge (75%, 52.94%) were most frequently cited. Health beliefs (unclear values) reflected Chinese characteristics. Patients had inadequate knowledge (M=19.99/50, SD=8.67) but positive BR attitudes (M=59.48/95, SD=10.45).

CONCLUSIONS

BR decisions for Chinese BC patients are complex and often accompanied by decisional conflicts. Inadequate knowledge and inadequate support and resources contribute to these conflicts, emphasizing the need for culturally tailored information and support to promote SDM.

PRACTICE IMPLICATIONS

HCPs need specialized training in SDM to guide patients in decision-making. It is essential to provide relevant resources and support that are culturally and clinically appropriate for Chinese patients.

What Affects Perceived Trustworthiness of Online Medical Information and Subsequent Treatment Decision Making? Randomized Trials on the Role of Uncertainty and Institutional Cues

Background. Online, algorithmically driven prognostic tools are increasingly important in medical decision making. Institutions developing such tools need to be able to communicate the precision and accuracy of the information in a trustworthy manner, and so many attempt to communicate uncertainties but also use institutional logos to underscore their trustworthiness. Bringing together theories on trust, uncertainty, and psychological distance in a novel way, we tested whether and how the communication of uncertainty and the presence of institutional logos together affected trust in medical information, the prognostic tool itself, and treatment decisions. Methods. A pilot and 2 online experiments in which UK (experiment 1) and worldwide (experiment 2) participants (Ntotal = 4,724) were randomized to 1 of 12 arms in a 3 (uncertainty cue) × 4 (institutional cue) between-subjects design. The stimulus was based on an existing medical prognostic tool. Results. Institutional trust was consistently associated with trust in the prognostic tool itself, while uncertainty information had no consistent effect. Institutional trust predicted the amount of weight participants reported placing on institutional endorsements in their decision making and the likelihood of switching from passive to active treatment in a hypothetical scenario. There was also a significant effect of psychological distance to (perceived hypotheticality of) the scenario. Conclusions/Implications. These results underline the importance of institutions demonstrating trustworthiness and building trust with their users. They also suggest that users tend to be insensitive to communications of uncertainty and that communicators may need to be highly explicit when attempting to warn of low precision or quality of evidence. The effect of the perceived hypotheticality of the scenario underscores the importance of realistic decision-making scenarios for studies and the role of familiarity with the decision dilemma generally.

Highlights

In a world where information for medical decision making is increasingly going to be provided through digital, online tools, institutions providing such tools need guidance on how best to communicate about their trustworthiness and precision.We find that people are fairly insensitive to cues designed to communicate uncertainty around the outputs of such tools. Even putting "ATTENTION" in bold font or explicitly pointing out the weaknesses in the data did not appear to affect people's decision making using the tool's outputs. Institutions should take note, and further work is required to determine how best to communicate uncertainty in a way that elicits appropriate caution in lay users.People were much more sensitive to institutional logos associated with the outputs. Generalized institutional trust (rather than trust in the specific institution whose logo was shown) was associated with how trustworthy, accurate, and reliable the tool, its algorithm, and the numbers it produced were perceived to be. This underscores the role of societal trust in institutions at large.Finally, as a note to researchers, we found a significant effect of how hypothetical or believable participants felt the experimental scenario was. This is a variable that seems rarely controlled for in studies and yet played as much of a role as some of our variables of interest, so we suggest that it is measured in future experiments.

A Machine Learning Algorithm for Predicting 6-Week Survival in Spinal Metastasis: An External Validation Study Using 2,768 Taiwanese Patients

INTRODUCTION

There are predictive algorithms for predicting 3-month and 1-year survival in patients with spinal metastasis. However, advance in surgical technique, immunotherapy, and advanced radiation therapy has enabled shortening of postoperative recovery, which returns dividends to the overall quality-adjusted life-year. As such, the Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) was proposed to predict 6-week survival in patients with spinal metastasis, whereas its utility for patients treated with nonsurgical treatment was untested externally. This study aims to validate the survival prediction of the 6-week SORG-MLA for patients with spinal metastasis and provide the measurement of model consistency (MC).

METHODS

Discrimination using area under the receiver operating characteristic curve, calibration, Brier score, and decision curve analysis were conducted to assess the model's performance in the Taiwanese-based cohort. MC was also applied to detect the proportion of paradoxical predictions among 6-week, 3-month, and 1-year survival predictions. The long-term prognosis should not be better than the shorter-term prognosis in that of an individual.

RESULTS

The 6-week survival rate was 84.2%. The SORG-MLA retained good discrimination with an area under the receiver operating characteristic curve of 0.78 (95% confidence interval, 0.75 to 0.80) and good prediction accuracy with a Brier score of 0.11 (null model Brier score 0.13). There is an underestimation of the 6-week survival rate when the predicted survival rate is less than 50%. Decision curve analysis showed that the model was suitable for use over all threshold probabilities. MC showed suboptimal consistency between 6-week and 90-day survival prediction (78%).

CONCLUSIONS

The results of this study supported the utility of the algorithm. The online tool ( https://sorg-apps.shinyapps.io/spinemetssurvival/ ) can be used by both clinicians and patients in informative decision-making discussion before management of spinal metastasis.

Co-Creation of Breast Cancer Risk Communication Tools and an Assessment of Risk Factor Awareness: A Qualitative Study of Patients and the Public in India

BACKGROUND

Low awareness of BC and its associated risk factors causes delays in diagnosis and impacts survival. It is critical to communicate BC risk to patients in a format that they are easily able to understand. Our study aim was to develop easy-to-follow transmedia prototypes to communicate BC risk and evaluate user preferences, alongside exploring awareness of BC and its risk factors.

METHODS

Prototypes of transmedia tools for risk communication were developed with multidisciplinary input. A qualitative in-depth online interview study was undertaken using a pre-defined topic guide of BC patients (7), their relatives (6), the general public (6), and health professionals (6). Interviews were analyzed using a thematic approach.

FINDINGS

Most participants preferred pictographic representations (frequency format) of lifetime risk and risk factors and storytelling using short animations and comic strips (infographics) for communicating genetic risk and testing: "In a short time, they explained it very well, and I liked it". Suggestions included minimizing technical terminology, decreasing the delivery speed, "two-way dialogue", and using local "language for different locations". There was low awareness of BC, with some understanding of age and hereditary risk factors but limited knowledge of reproductive factors.

INTERPRETATION

Our findings support use of multiple context-specific multimedia tools in communicating cancer risk in an easy-to-understand way. The preference for storytelling using animations and infographics is a novel finding and should be more widely explored.

myBeST-A Web-Based Survival Prognostic Tool for Women with Breast Cancer in Malaysia: Development Process and Preliminary Validation Study

Women with breast cancer are keen to know their predicted survival. We developed a new prognostic model for women with breast cancer in Malaysia. Using the model, this study aimed to design the user interface and develop the contents of a web-based prognostic tool for the care provider to convey survival estimates. We employed an iterative website development process which includes: (1) an initial development stage informed by reviewing existing tools and deliberation among breast surgeons and epidemiologists, (2) content validation and feedback by medical specialists, and (3) face validation and end-user feedback among medical officers. Several iterative prototypes were produced and improved based on the feedback. The experts (n = 8) highly agreed on the website content and predictors for survival with content validity indices ≥ 0.88. Users (n = 20) scored face validity indices of more than 0.90. They expressed favourable responses. The tool, named Malaysian Breast cancer Survival prognostic Tool (myBeST), is accessible online. The tool estimates an individualised five-year survival prediction probability. Accompanying contents were included to explain the tool's aim, target user, and development process. The tool could act as an additional tool to provide evidence-based and personalised breast cancer outcomes.

Efficacy of Three Numerical Presentation Formats on Lay People's Comprehension and Risk Perception of Fact Boxes-A Randomized Controlled Pilot Study

(1) Background: Fact boxes present the benefits and harms of medical interventions in the form of tables. Some studies suggest that people with a lower level of education could profit more from graphic presentations. The objective of the study was to compare three different formats in fact boxes with regard to verbatim and gist knowledge in general and according to the educational background. (2) Methods: In May 2020, recruitment started for this randomized controlled trial. Participants were given one out of three presentation formats: natural frequencies, percentages, and graphic. We used Limesurvey® to assess comprehension/risk perception as the primary outcome. The Kruskal-Wallis test and the Mann-Whitney U test were used in addition to descriptive analyses. (3) Results: A total of 227 people took part in the study. Results of the groups were nearly identical in relation to the primary outcome verbatim knowledge, likewise in gist knowledge. However, participants with lower educational qualifications differed from participants with higher educational qualifications in terms of verbatim knowledge in the group percentages. (4) Conclusions: The results indicate that all three forms of presentation are suitable for conveying the content. Further research should take the individual preferences regarding the format into account.

Physiotherapy in the prevention and treatment of upper limb complications in women with breast cancer

Breast cancer is the one that most affects the female population in Brazil and the world. Upper limb complications are common after cancer treatment, including conservative procedures. Old studies have already shown the effectiveness of physiotherapy in the rehabilitation of these complications. However, currently, physiotherapeutic care must be initiated from the diagnosis of the disease. Pre-rehabilitation prepares the patient to receive cancer treatment and promotes a reduction in rehabilitation time. Rehabilitation decreased the axillary cord by 57%, increased the range of motion (ROM) by 45º for flexion and 70º for shoulder abduction, the incidence of lymphedema was 11%, and there was a decrease of 3.4 points concerning pain on the Visual Scale Analog (EVA). The physical therapist should work with breast cancer to diagnose, prevent, and rehabilitate after cancer treatment, promoting functionality and quality of life for patients with breast cancer.

Evaluation of Prognostic and Predictive Models in the Oncology Clinic

Predictive and prognostic models hold great potential to support clinical decision making in oncology and could ultimately facilitate a paradigm shift to a more personalised form of treatment. While a large number of models relevant to the field of oncology have been developed, few have been translated into clinical use and assessment of clinical utility is not currently considered a routine part of model development. In this narrative review of the clinical evaluation of prediction models in oncology, we propose a high-level process diagram for the life cycle of a clinical model, encompassing model commissioning, clinical implementation and ongoing quality assurance, which aims to bridge the gap between model development and clinical implementation.

Redevelopment of the Predict: Breast Cancer website and recommendations for developing interfaces to support decision-making

Objectives

To develop a new interface for the widely used prognostic breast cancer tool: Predict: Breast Cancer. To facilitate decision‐making around post‐surgery breast cancer treatments. To derive recommendations for communicating the outputs of prognostic models to patients and their clinicians.

Method

We employed a user‐centred design process comprised of background research and iterative testing of prototypes with clinicians and patients. Methods included surveys, focus groups and usability testing.

Results

The updated interface now caters to the needs of a wider audience through the addition of new visualisations, instantaneous updating of results, enhanced explanatory information and the addition of new predictors and outputs. A programme of future research was identified and is now underway, including the provision of quantitative data on the adverse effects of adjuvant breast cancer treatments.

Based on our user‐centred design process, we identify six recommendations for communicating the outputs of prognostic models including the need to contextualise statistics, identify and address gaps in knowledge, and the critical importance of engaging with prospective users when designing communications.

Conclusions

For prognostic algorithms to fulfil their potential to assist with decision‐making they need carefully designed interfaces. User‐centred design puts patients and clinicians needs at the forefront, allowing them to derive the maximum benefit from prognostic models.