Using three scenarios to explain life expectancy in advanced cancer: attitudes of patients, family members, and other healthcare professionals

Aim To evaluate a web-based tool for estimating and explaining three scenarios for expected survival time to people with advanced cancer (patients), their family members (FMs), and other healthcare professionals (HCPs). Methods Thirty-three oncologists estimated the “median survival of a group of si...

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Veröffentlicht in:Supportive care in cancer 2022-09, Vol.30 (9), p.7763-7772
Hauptverfasser: Nahm, Sharon H., Stockler, Martin R., Martin, Andrew J., Grimison, Peter, Fox, Peter, Zielinski, Rob, Hawson, Geoffrey AT, Tattersall, Martin HN, Kiely, Belinda E.
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container_end_page 7772
container_issue 9
container_start_page 7763
container_title Supportive care in cancer
container_volume 30
creator Nahm, Sharon H.
Stockler, Martin R.
Martin, Andrew J.
Grimison, Peter
Fox, Peter
Zielinski, Rob
Hawson, Geoffrey AT
Tattersall, Martin HN
Kiely, Belinda E.
description Aim To evaluate a web-based tool for estimating and explaining three scenarios for expected survival time to people with advanced cancer (patients), their family members (FMs), and other healthcare professionals (HCPs). Methods Thirty-three oncologists estimated the “median survival of a group of similar patients” for patients seeking quantitative prognostic information. The web-based tool generated worst-case, most likely, and best-case scenarios for survival based on the oncologist’s estimate. Oncologists presented the scenarios to each patient and provided a printed summary to patients, FMs, and HCPs. Attitudes to the information were assessed by questionnaires. Observed survival for each patient was compared with the oncologist’s estimated survival and the three scenarios. Results Prognosis was discussed with 222 patients: median age 67 years; 61% male; most common primary sites pancreas 15%, non-small-cell lung 15%, and colorectal 12%. The median (range) for observed survival times was 9 months (0.5–43) and for oncologist’s estimated survival times was 12 months (2–96). Ninety-one percent of patients, 91% of FMs, and 84% of HCPs agreed that it was helpful having life expectancy explained as three scenarios. The majority (77%) of patients judged the information presented about their life expectancy to be the same or better than they had expected before the consultation. The survival estimates met a priori criteria for calibration, precision, and accuracy. Conclusions Patients, FMs, and HCPs found it helpful to receive personalized prognostic information formatted as three scenarios for survival. It was feasible, acceptable, and safe to use a web-based resource to do this.
doi_str_mv 10.1007/s00520-022-07167-3
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Methods Thirty-three oncologists estimated the “median survival of a group of similar patients” for patients seeking quantitative prognostic information. The web-based tool generated worst-case, most likely, and best-case scenarios for survival based on the oncologist’s estimate. Oncologists presented the scenarios to each patient and provided a printed summary to patients, FMs, and HCPs. Attitudes to the information were assessed by questionnaires. Observed survival for each patient was compared with the oncologist’s estimated survival and the three scenarios. Results Prognosis was discussed with 222 patients: median age 67 years; 61% male; most common primary sites pancreas 15%, non-small-cell lung 15%, and colorectal 12%. The median (range) for observed survival times was 9 months (0.5–43) and for oncologist’s estimated survival times was 12 months (2–96). Ninety-one percent of patients, 91% of FMs, and 84% of HCPs agreed that it was helpful having life expectancy explained as three scenarios. The majority (77%) of patients judged the information presented about their life expectancy to be the same or better than they had expected before the consultation. The survival estimates met a priori criteria for calibration, precision, and accuracy. Conclusions Patients, FMs, and HCPs found it helpful to receive personalized prognostic information formatted as three scenarios for survival. It was feasible, acceptable, and safe to use a web-based resource to do this.</description><identifier>ISSN: 0941-4355</identifier><identifier>EISSN: 1433-7339</identifier><identifier>DOI: 10.1007/s00520-022-07167-3</identifier><identifier>PMID: 35701634</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Aged ; Cancer ; Cancer patients ; Carcinoma, Non-Small-Cell Lung ; Communication ; Comparative analysis ; Delivery of Health Care ; Families &amp; family life ; Family ; Female ; Health aspects ; Humans ; Life Expectancy ; Lung cancer, Non-small cell ; Lung Neoplasms ; Male ; Medical personnel ; Medical prognosis ; Medicine ; Medicine &amp; Public Health ; Neoplasms - therapy ; Nursing ; Nursing Research ; Oncology ; Original ; Original Article ; Pain Medicine ; Palliative care ; Patient care planning ; Patients ; Physician patient relationships ; Prognosis ; Rehabilitation Medicine ; Surveys</subject><ispartof>Supportive care in cancer, 2022-09, Vol.30 (9), p.7763-7772</ispartof><rights>The Author(s) 2022. corrected publication 2024</rights><rights>2022. 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Methods Thirty-three oncologists estimated the “median survival of a group of similar patients” for patients seeking quantitative prognostic information. The web-based tool generated worst-case, most likely, and best-case scenarios for survival based on the oncologist’s estimate. Oncologists presented the scenarios to each patient and provided a printed summary to patients, FMs, and HCPs. Attitudes to the information were assessed by questionnaires. Observed survival for each patient was compared with the oncologist’s estimated survival and the three scenarios. Results Prognosis was discussed with 222 patients: median age 67 years; 61% male; most common primary sites pancreas 15%, non-small-cell lung 15%, and colorectal 12%. The median (range) for observed survival times was 9 months (0.5–43) and for oncologist’s estimated survival times was 12 months (2–96). Ninety-one percent of patients, 91% of FMs, and 84% of HCPs agreed that it was helpful having life expectancy explained as three scenarios. The majority (77%) of patients judged the information presented about their life expectancy to be the same or better than they had expected before the consultation. The survival estimates met a priori criteria for calibration, precision, and accuracy. Conclusions Patients, FMs, and HCPs found it helpful to receive personalized prognostic information formatted as three scenarios for survival. 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Methods Thirty-three oncologists estimated the “median survival of a group of similar patients” for patients seeking quantitative prognostic information. The web-based tool generated worst-case, most likely, and best-case scenarios for survival based on the oncologist’s estimate. Oncologists presented the scenarios to each patient and provided a printed summary to patients, FMs, and HCPs. Attitudes to the information were assessed by questionnaires. Observed survival for each patient was compared with the oncologist’s estimated survival and the three scenarios. Results Prognosis was discussed with 222 patients: median age 67 years; 61% male; most common primary sites pancreas 15%, non-small-cell lung 15%, and colorectal 12%. The median (range) for observed survival times was 9 months (0.5–43) and for oncologist’s estimated survival times was 12 months (2–96). Ninety-one percent of patients, 91% of FMs, and 84% of HCPs agreed that it was helpful having life expectancy explained as three scenarios. The majority (77%) of patients judged the information presented about their life expectancy to be the same or better than they had expected before the consultation. The survival estimates met a priori criteria for calibration, precision, and accuracy. Conclusions Patients, FMs, and HCPs found it helpful to receive personalized prognostic information formatted as three scenarios for survival. It was feasible, acceptable, and safe to use a web-based resource to do this.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>35701634</pmid><doi>10.1007/s00520-022-07167-3</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-1662-3523</orcidid><oa>free_for_read</oa></addata></record>
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subjects Aged
Cancer
Cancer patients
Carcinoma, Non-Small-Cell Lung
Communication
Comparative analysis
Delivery of Health Care
Families & family life
Family
Female
Health aspects
Humans
Life Expectancy
Lung cancer, Non-small cell
Lung Neoplasms
Male
Medical personnel
Medical prognosis
Medicine
Medicine & Public Health
Neoplasms - therapy
Nursing
Nursing Research
Oncology
Original
Original Article
Pain Medicine
Palliative care
Patient care planning
Patients
Physician patient relationships
Prognosis
Rehabilitation Medicine
Surveys
title Using three scenarios to explain life expectancy in advanced cancer: attitudes of patients, family members, and other healthcare professionals
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