Introduction Although various phrases to communicate prognoses based on a certain concept have been proposed, no study has systematically investigated preferences of patients with cancer for actual phrases. We investigated whether phrases with a wider range and additional “hope for the best, and prepare for the worst” (hope/prepare) statement would be more preferable and explored variables associated with patients’ preferences. Materials and Methods In a cross‐sectional survey, 412 outpatients with cancer self‐assessed their preferences for 13 phrases conveying prognostic information (e.g., phrases with or without median, typical range, and/or best/worst cases, and those with or without a hope/prepare statement) on a 6‐point scale (1 = not at all preferable; 6 = very preferable). We evaluated demographic data and the Coping Inventory for Stressful Situations and conducted multivariate regression analysis. Results Regarding phrases with various ranges, the one including the median, typical range, and best/worst cases was more preferable (mean ± SD, 3.8 ± 1.3; 95% confidence interval [CI], 3.6–3.9) than the one with the median and typical range (3.4 ± 1.2; 3.3–3.6) or the one with only the median (3.2 ± 1.3; 3.1–3.3). Concerning the hope/prepare statement, the phrase including the median, typical range, uncertainty, and hope/prepare statement was more preferable (3.8 ± 1.4; 3.7–3.9) than the one without the statement (3.5 ± 1.2; 3.4–3.6). In multivariate analyses, task‐oriented coping was significantly correlated with preferences for phrases with explicit information. Conclusion Overall, phrases with a wider range and the hope/prepare statement were preferable to those without them. When patients with cancer ask about prognoses, especially those with task‐oriented coping, clinicians may provide explicit information with a wider range and the hope/prepare statement. Implications for Practice Discussing prognoses with patients with advanced cancer is among the most important conversations for clinicians. In this cross‐sectional survey to systematically investigate preferences of 412 patients with cancer for phrases conveying prognostic information, phrases with the median, typical range, and best/worst cases and those with the “hope for the best and prepare for the worst” (hope/prepare) statement were the most preferred. When patients with cancer ask about prognoses, clinicians may provide explicit information with a wider range and include the hope/prepare statement.

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BackgroundWe aimed to develop an adaptable prognosis prediction model that could be applied at any time point during the treatment course for patients with cancer receiving chemotherapy, by applying time-series real-world big data.MethodsBetween April 2004 and September 2014, 4,997 patients with cancer who had received systemic chemotherapy were registered in a prospective cohort database at the Kyoto University Hospital. Of these, 2,693 patients with a death record were eligible for inclusion and divided into training (n = 1,341) and test (n = 1,352) cohorts. In total, 3,471,521 laboratory data at 115,738 time points, representing 40 laboratory items [e.g., white blood cell counts and albumin (Alb) levels] that were monitored for 1 year before the death event were applied for constructing prognosis prediction models. All possible prediction models comprising three different items from 40 laboratory items (40C3 = 9,880) were generated in the training cohort, and the model selection was performed in the test cohort. The fitness of the selected models was externally validated in the validation cohort from three independent settings.ResultsA prognosis prediction model utilizing Alb, lactate dehydrogenase, and neutrophils was selected based on a strong ability to predict death events within 1–6 months and a set of six prediction models corresponding to 1,2, 3, 4, 5, and 6 months was developed. The area under the curve (AUC) ranged from 0.852 for the 1 month model to 0.713 for the 6 month model. External validation supported the performance of these models.ConclusionBy applying time-series real-world big data, we successfully developed a set of six adaptable prognosis prediction models for patients with cancer receiving chemotherapy.

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No abstract

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Background: Junior physicians' perceived difficulty in end-of-life care of patients with cancer has not been structurally investigated; therefore, current challenges and solutions in this area remain unknown. Objectives: To identify some difficulties junior physicians face in delivering end-of-life care for patients with cancer and to clarify the support required to reduce these difficulties. Design: A nationwide survey was conducted in over 300 institutions selected randomly from 1037 clinical training hospitals in Japan. Participants: From each of these institutions, two resident physicians of postgraduate year (PGY) 1 or 2, two clinical fellows of PGY 3–5, and an attending physician were requested to respond to the survey. Measurements: The survey investigated issues regarding end-of-life care using the palliative care difficulties scale with two additional domains (“discussion about end-of-life care” and “death pronouncement”). Items related to potential solutions for alleviating the difficulties as well were investigated. Results: A total of 198 resident physicians, 134 clinical fellows, and 96 attending physicians responded to the survey (response rate: 33.0%, 22.3%, and 32.0%). The results revealed that junior physicians face difficulties within specific domains of end-of-life care. The most challenging domain comprised communication and end-of-life discussion with patients and family members, symptom alleviation, and death pronouncement. The most favored supportive measure for alleviating these difficulties was mentorship, rather than educational opportunities or resources regarding end-of-life care. Conclusion: The findings of this study reveal the need for further effort to enrich the mentorship and support systems for junior physicians delivering end-of-life care.