Influencing factors of lung cancer patients' participation in shared decision-making: a cross-sectional study

Prediction of prognosis in lung cancer using machine learning with inter-institutional generalizability: A multicenter cohort study (WJOG15121L: REAL-WIND)

OBJECTIVES

Predicting the prognosis of lung cancer is crucial for providing optimal medical care. However, a method to accurately predict the overall prognosis in patients with stage IV lung cancer, even with the use of machine learning, has not been established. Moreover, the inter-institutional generalizability of such algorithms remains unexplored. This study aimed to establish machine learning-based algorithms with inter-institutional generalizability to predict prognosis.

MATERIALS AND METHODS

This multicenter, retrospective, hospital-based cohort study included consecutive patients with stage IV lung cancer who were randomly categorized into the training and independent test cohorts with a 2:1 ratio, respectively. The primary metric to assess algorithm performance was the area under the receiver operating characteristic curve in the independent test cohort. To assess the inter-institutional generalizability of the algorithms, we investigated their ability to predict patient outcomes in the remaining facility after being trained using data from 15 other facilities.

RESULTS

Overall, 6,751 patients (median age, 70 years) were enrolled, and 1,515 (22 %) showed mutated epidermal growth factor receptor expression. The median overall survival was 16.6 (95 % confidence interval, 15.9-17.5) months. Algorithm performance metrics in the test cohort showed that the areas under the curves were 0.90 (95 % confidence interval, 0.88-0.91), 0.85 (0.84-0.87), 0.83 (0.81-0.85), and 0.85 (0.82-0.87) at 180, 360, 720, and 1,080 predicted survival days, respectively. The performance test of 16 algorithms for investigating inter-institutional generalizability showed median areas under the curves of 0.87 (range, 0.84-0.92), 0.84 (0.78-0.88), 0.84 (0.76-0.89), and 0.84 (0.75-0.90) at 180, 360, 720, and 1,080 days, respectively.

CONCLUSION

This study developed machine learning algorithms that could accurately predict the prognosis in patients with stage IV lung cancer with high inter-institutional generalizability. This can enhance the accuracy of prognosis prediction and support informed and shared decision-making in clinical settings.

Nurses' self-regulation after engaging in end-of-life conversations with advanced cancer patients: a qualitative study

BACKGROUND

Self-regulation is crucial for nurses who engage in in-depth end-of-life conversations with advanced cancer patients, especially in cultural contexts featuring death taboos. An improved understanding of the self-regulation process of nurses can help them address negative emotions and promote self-growth more effectively. Therefore, this study aimed to explore nurses' self-regulation process after end-of-life conversations with advanced cancer patients.

METHODS

This study employed a descriptive, qualitative approach. Seventeen nurses from four hospitals and a hospice unit in mainland China were interviewed between September 2022 and June 2023. Data were collected through face-to-face semistructured interviews. A thematic analysis method was used to analyse the data following the guidance of regulatory focus theory.

RESULTS

Three main themes were developed: self-regulation antecedents include personality, experience, and support; promotion or prevention is a possible self-regulation process for nurses; both self-exhaustion and self-growth may be the outcomes of self-regulation, as did seven subthemes. Personality tendencies, life experience, and perceived support may affect nurses' self-regulation, thereby affecting their self-regulation outcomes.

CONCLUSIONS

Nurses exhibit different self-regulatory tendencies and self-regulation outcomes. The provision of peer support and counselling support to nurses is highly important with regard to achieving good self-regulation outcomes.

Factors Impacting on Patient-Centered Communication Skills and Their Opportunities to Be Involved in Decision-making From the Perspective of Patients With Cancer, Informal Caregivers, and/or Healthcare Professionals: A Systematic Review

BACKGROUND

Active participation of cancer patients and their caregivers in decision-making, along with high-quality communication, is crucial in patient-centered cancer management. Although numerous factors affecting patients' communication and decision-making involvement have been identified, it is still unclear which ones are the most prevalent and critical.

OBJECTIVE

To identify factors that contribute to high-quality patient-centered communication and decision-making participation from the perspectives of cancer patients, informal caregivers, and/or healthcare professionals.

METHODS

A systematic review was conducted, using 9 databases to retrieve primary research articles published from 2010 to February 17, 2023, updated on December 13, 2023. Methodological quality was assessed using the Mixed Methods Appraisal Tool (version 18). The socioecological model of communication was utilized as analytical framework for summarizing the results.

RESULTS

Fifty-two studies were included. The most frequently reported factors were predominantly articulated at the individual, interpersonal, and societal levels. Although the patients' lack of knowledge and limited language proficiency were the frequent patient-level barriers, the perceived lack of knowledge and lack of training of professionals were the crucial and current professional-level barriers, as reported in studies published in 2016 onward. To circumvent these factors, it is critical to enhance professionals' knowledge, communication skills, and patient relationships.

CONCLUSIONS

Recognizing barriers and facilitators could help in the development of strategies to overcome these barriers and enhance patient participation in clinical communication.

IMPLICATION FOR PRACTICE

The findings could guide the development of programs to enhance patient-professional communication skills. Further cross-cultural studies are needed to understand culture's impact on communication effectiveness and decision-making participation.

A scoping review into the explanations for differences in the degrees of shared decision making experienced by patients

OBJECTIVES

In order to improve the degree of shared decision making (SDM) experienced by patients, it is necessary to gain insight into the explanations for the differences in these degrees.

METHODS

A scoping review of the literature on the explanations for differences in the degree of SDM experienced by patients was conducted. We assessed 21,329 references. Ultimately, 308 studies were included. The explanations were divided into micro, meso, and macro levels.

RESULTS

The explanations are mainly related to the micro level. They include explanations related to the patient and healthcare professionals, the relationship between the patient and the physician, and the involvement of the patient's relatives. On the macro level, explanations are related to restrictions within the healthcare system such as time constraints, and adequate information about treatment options. On the meso level, explanations are related to the continuity of care and the involvement of other healthcare professionals.

CONCLUSIONS

SDM is not an isolated process between the physician and patient. Explanations are connected to the macro, meso, and micro levels.

PRACTICE IMPLICATIONS

This scoping review suggests that there could be more focus on explanations related to the macro and meso levels, and on how explanations at different levels are interrelated.

Analysis of factors that promote the participation of patients with chronic diseases in shared decision making on medication: a cross-sectional survey in Hubei Province, China

BACKGROUND

Shared decision making (SDM) improves the health status of patients with chronic diseases, especially in the condition of poly-medicated patients. This study aims to find the factors associated with participation of patients with chronic diseases in SDM on medication.

METHODS

A total of 1,196 patients with chronic diseases were selected in Hubei Province of China using cluster sampling methods. The random forest method was applied to rank the importance of independent variables by Mean Decrease Gini and out-of- bag (OOB) curve. Multivariate logistic regression was used to explore the independent variables' effect direction and relative hazard.

RESULTS

In this study, 5.18% of patients used patient-directed decision making (PDM, a decision-making model led by patients), 37.79% of patients used SDM (a collaborative decision-making model by patients and doctors), and 57.02% of patients used doctor-directed decision making (DDM, or paternalistic decision making, a decision-making model led by doctors). The random forest analysis demonstrated that the top 5 important factors were age, education, exercise, disease course, and medication knowledge. The OOB curve showed that the error rate reached minimum when top 5 variables in importance ranking composed an optimal variable combination. In multivariate logistic regression, we chose SDM as a reference group, and identified medication knowledge (OR = 2.737, 95%CI = 1.524 ~ 4.916) as the influencing factor between PDM and SDM. Meanwhile, the influencing factors between DDM and SDM were age (OR = 0.636, 95%CI = 0.439 ~ 0.921), education (OR = 1.536, 95%CI = 1.122 ~ 2.103), exercise (OR = 1.443, 95%CI = 1.109 ~ 1.877), disease course (OR = 0.750, 95%CI = 0.584 ~ 0.964), and medication knowledge (OR = 1.446, 95%CI = 1.120 ~ 1.867).

CONCLUSION

Most Chinese patients with chronic diseases used DDM during their medication decision-making, and some patients used PDM and SDM. The participation in SDM should be taken seriously among elderly patients with lower education levels. The SDM promotion should focus on transformation of patients' traditional perception and enhance their medication knowledge.

Status quo of advanced cancer patients participating in shared decision-making in China: a mixed study

PURPOSE

Patients with advanced cancer are usually willing to participate in shared decision-making (SDM), but in clinical practice, patient participation is easily ignored. This study aimed to analyze the current SDM status of advanced cancer patients and related factors.

METHODS

In quantitative research, we administered a cross-sectional survey to 513 advanced cancer patients in 16 tertiary hospitals in China. A sociodemographic information questionnaire, the Control Preference Scale (CPS), and Perceived-Involvement in Care Scale (PICS) were used to analyze current SDM status and influencing factors. Our qualitative research was based on the Ottawa Decision Support Framework (ODSF), and 17 advanced cancer patients were interviewed to explore their perceptions of SDM.

RESULTS

Our quantitative results show that patients' actual and expected decision-making participation differed; statistically significant influencing factors were age, insurance, and whether patients were worried about the therapeutic effects. We also found that dynamic decision-making mode changes, disease information acquisition, decision-making participation obstacles, and family members' roles affected patients' SDM through qualitative interviews.

CONCLUSION

Advanced cancer patients' SDM in China is dominated by sharing and continuously fluctuates. Influenced by Chinese traditional culture, family members play an important role in SDM. In clinical work, we should pay attention to the dynamic changes in patients' participation in decision-making and the role of family members.

Providers' shared decision-making as a predictor of healthcare outcomes for college-aged adults managing upper respiratory tract infections

OBJECTIVES

Strategies that assist patients with upper respiratory tract infections (URTIs) to endorse non-antibiotic treatments are vital to curbing antibiotic resistance. This study examines the potential of shared decision-making (SDM) for improving stewardship-relevant outcomes and investigates patient affect as a mechanism that explains the beneficial impact of perceived SDM.

METHOD

Patients (N = 433) seeking care for URTIs at a university student health center and not prescribed antibiotics completed a pre-visit questionnaire and two surveys one day and 14 days post-visit. The day-one survey assessed perceived SDM, affect, and immediate stewardship-relevant outcomes, and the day-14 survey assessed long-term stewardship-relevant outcomes.

RESULTS

Perceived SDM was negatively associated with negative affect and positively associated with positive affect, favorable perceptions of non-antibiotic treatments and providers, and self-efficacy to manage symptoms and obtain follow-up care. Patient affect and day-one outcomes were mediators between perceived SDM and retrospective self-efficacy two weeks post-visit.

CONCLUSION

The study illustrated the beneficial influence of patient perceived SDM on antibiotic stewardship in both short and long terms and elucidated the mechanisms through which the influence occurs.

PRACTICE IMPLICATIONS

SDM can be an effective strategy for primary care providers to improve patients' outcomes with URTI visits without prescribing unwarranted antibiotics.