Search

Introduction Guidelines on chronic kidney disease (CKD) recommend that nephrologists use clinical prediction models (CPMs). However, the actual use of CPMs seems limited in clinical practice. We conducted a national survey study to evaluate: 1) to what extent CPMs are used in Dutch CKD practice, 2) patients’ and nephrologists’ needs and preferences regarding predictions in CKD, and 3) determinants that may affect the adoption of CPMs in clinical practice. Methods We conducted semi-structured interviews with CKD patients to inform the development of two online surveys; one for CKD patients and one for nephrologists. Survey participants were recruited through the Dutch Kidney Patient Association and the Dutch Federation of Nephrology. Results A total of 126 patients and 50 nephrologists responded to the surveys. Most patients (89%) reported they had discussed predictions with their nephrologists. They most frequently discussed predictions regarded CKD progression: when they were expected to need kidney replacement therapy (KRT) (n = 81), and how rapidly their kidney function was expected to decline (n = 68). Half of the nephrologists (52%) reported to use CPMs in clinical practice, in particular CPMs predicting the risk of cardiovascular disease. Almost all nephrologists (98%) reported discussing expected CKD trajectories with their patients; even those that did not use CPMs (42%). The majority of patients (61%) and nephrologists (84%) chose a CPM predicting when patients would need KRT in the future as the most important prediction. However, a small portion of patients indicated they did not want to be informed on predictions regarding CKD progression at all (10–15%). Nephrologists not using CPMs (42%) reported they did not know CPMs they could use or felt that they had insufficient knowledge regarding CPMs. According to the nephrologists, the most important determinants for the adoption of CPMs in clinical practice were: 1) understandability for patients, 2) integration as standard of care, 3) the clinical relevance. Conclusion Even though the majority of patients in Dutch CKD practice reported discussing predictions with their nephrologists, CPMs are infrequently used for this purpose. Both patients and nephrologists considered a CPM predicting CKD progression most important to discuss. Increasing awareness about existing CPMs that predict CKD progression may result in increased adoption in clinical practice. When using CPMs regarding CKD progression, nephrologists should ask whether patients want to hear predictions beforehand, since individual patients’ preferences vary.

INTRODUCTION: In addition to clinical trials, real-world data is needed to verify the effectiveness of the CDK 4/6 inhibitor palbociclib. The primary aim was to examine real-world variation in treatment modification strategies for neutropenia and its relation to progression-free survival (PFS). The secondary aim was to assess if there is a gap between real-world and clinical trial outcomes. MATERIALS AND METHODS: In this multicenter, retrospective observational cohort study 229 patients were analyzed who started palbociclib and fulvestrant as second- or later-line therapy for HR-positive, HER2-negative metastatic breast cancer in the Santeon hospital group in the Netherlands between September 2016 and December 2019. Data were manually retrieved from patients' electronic medical records. PFS was examined using the Kaplan-Meier method to compare neutropenia-related treatment modification strategies within the first three months after neutropenia grade 3 - 4 occurred, as well as patients' eligibility to have participated in the PALOMA-3 clinical trial or not. RESULTS: Even though treatment modification strategies differed from those in PALOMA-3 (dose interruptions: 26 vs 54%, cycle delays: 54 vs 36%, and dose reductions: 39 vs 34%), these did not influence PFS. Patients who were PALOMA-3 ineligible experienced a shorter median PFS than those who were eligible (10.2 vs. 14.1 months; HR 1.52; 95% CI 1.12 - 2.07). An overall longer median PFS was found compared to PALOMA-3 (11.6 vs. 9.5 months; HR 0.70; 95% CI 0.54 - 0.90). CONCLUSION: This study suggests no impact of neutropenia-related treatment modifications on PFS and confirms inferior outcomes outside clinical trial eligibility.

PURPOSE To develop and evaluate a tool for patients with stage IV non–small-cell lung cancer and their thoracic oncologists (TOs) that provides insight into real-world effectiveness of systemic treatments to support informed clinical decision making in the palliative setting. METHODS A participatory design approach was used to acquire insights from patients and TOs into preferences regarding the content and design of the web-based tool. Implementation was investigated by means of an adoption and usage rate. The appreciation of the tool was evaluated through a telephone survey with patients and a questionnaire for TOs. RESULTS From clinical data of 2,989 patients with stage IV non–small-cell lung cancer diagnosed in one of the Santeon hospitals, an interface was developed to show treatments plus both real-world outcomes and clinical trial results after selecting patient characteristics (patients like me). This prototype of the tool was finalized after discussion in a focus group with four TOs and semi-structured interviews with six patients. The tool was implemented and used by TOs in three of six Santeon hospitals (50% adoption rate). The tool was used in 48 patients (29% usage rate), of which 17 participated in the telephone survey. Ten TOs responded to the questionnaire. The responses varied from positive reactions on the clear overview of treatment outcomes to statements that the tool rarely changed treatment decisions. Overall, the majority of patients and TOs scored the tool as of added value (71% and 83%, respectively). CONCLUSION Our real-world data tool in metastatic lung cancer was appreciated in clinical practice by both patients and TOs. However, the efficacy of the implementation can be improved.

Additional file 1. Supplementary materials

Background The eHealth Impact Questionnaire (eHIQ) provides a standardized method to measure attitudes of electronic health (eHealth) users toward eHealth. It has previously been validated in a population of eHealth users in the United Kingdom and consists of 2 parts and 5 subscales. Part 1 measures attitudes toward eHealth in general and consists of the subscales attitudes towards online health information (5 items) and attitudes towards sharing health experiences online (6 items). Part 2 measures the attitude toward a particular eHealth application and consists of the subscales confidence and identification (9 items), information and presentation (8 items), and understand and motivation (9 items). Objective This study aimed to translate and validate the eHIQ in a Dutch population of eHealth users. Methods The eHIQ was translated and validated in accordance with the COnsensus-based Standards for the selection of health status Measurement INstruments criteria. The validation comprised 3 study samples, with a total of 1287 participants. Structural validity was assessed using confirmatory factor analyses and exploratory factor analyses (EFAs; all 3 samples). Internal consistency was assessed using hierarchical omega (all 3 samples). Test-retest reliability was assessed after 2 weeks, using 2-way intraclass correlation coefficients (sample 1). Measurement error was assessed by calculating the smallest detectable change (sample 1). Convergent and divergent validity were assessed using correlations with the remaining measures (all 3 samples). A graded response model was fit, and item information curves were plotted to describe the information provided by items across item trait levels (all 3 samples). Results The original factor structure showed a bad fit in all 3 study samples. EFAs showed a good fit for a modified factor structure in the first study sample. This factor structure was subsequently tested in samples 2 and 3 and showed acceptable to good fits. Internal consistency, test-retest reliability, convergent validity, and divergent validity were acceptable to good for both the original as the modified factor structure, except for test-retest reliability of one of the original subscales and the 2 derivative subscales in the modified factor structure. The graded response model showed that some items underperformed in both the original and modified factor structure. Conclusions The Dutch version of the eHIQ (eHIQ-NL) shows a different factor structure compared with the original English version. Part 1 of the eHIQ-NL consists of 3 subscales: attitudes towards online health information (5 items), comfort with sharing health experiences online (3 items), and usefulness of sharing health experiences online (3 items). Part 2 of the eHIQ-NL consists of 3 subscales: motivation and confidence to act (10 items), information and presentation (13 items), and identification (3 items).

Background: Although many cancer survivors could benefit from supportive care, they often do not utilize such services. Previous studies have shown that patient-reported outcomes (PROs) could be a solution to meet cancer survivors’ needs, for example through an eHealth application that monitors quality of life and provides personalized advice and supportive care options. In order to develop an effective application that can successfully be implemented in current health care, it is important to include health care professionals in the development process. Objective: The aim of this study was to investigate health care professionals’ perspectives toward follow-up care and an eHealth application, OncoKompas, in follow-up cancer care that monitors quality of life via PROs, followed by automatically generated tailored feedback and personalized advice on supportive care. Methods: Health care professionals involved in head and neck cancer care (N=11) were interviewed on current follow-up care and the anticipated value of the proposed eHealth application (Step 1). A prototype of the eHealth application, OncoKompas, was developed (Step 2). Cognitive walkthroughs were conducted among health care professionals (N=21) to investigate perceived usability (Step 3). Interviews were recorded, transcribed verbatim, and analyzed by 2 coders. Results: Health care professionals indicated several barriers in current follow-up care including difficulties in detecting symptoms, patients’ perceived need for supportive care, and a lack of time to encourage survivors to obtain supportive care. Health care professionals expected the eHealth application to be of added value. The cognitive walkthroughs demonstrated that health care professionals emphasized the importance of tailoring care. They considered the navigation structure of OncoKompas to be complex. Health care professionals differed in their opinion toward the best strategy to implement the application in clinical practice but indicated that it should be incorporated in the HNC cancer care pathway to ensure all survivors would benefit. Conclusions: Health care professionals experienced several barriers in directing patients to supportive care. They were positive toward the development and implementation of an eHealth application and expected it could support survivors in obtaining supportive care tailored to their needs. The cognitive walkthroughs revealed several points for optimizing the application prototype and developing an efficient implementation strategy. Including health care professionals in an early phase of a participatory design approach is valuable in developing an eHealth application and an implementation strategy meeting stakeholders’ needs. [J Med Internet Res 2015;17(10):e235]