INTRODUCTION: This study compares the relative prognostic power of clinical variables and quality-of-life (QoL) measures in a population of terminal cancer patients. METHODS: A prospective cohort study in 58 Italian Palliative Care Units. Of the 601 randomly selected terminal cancer patients, 574 were followed until death in order to compare clinical and QoL variables (using the Therapy Impact Questionnaire (TIQ) as predictors of survival, and assess whether their combined implementation makes prediction more accurate. RESULTS: The clinical variables most strongly associated with survival were dyspnoea, cachexia, Katz's ADL, oliguria, dysphagia, dehydration, liver and acute kidney failure and delirium (hazard ratios (HR) ranging from 2.10 to 3.01). Only the first four kept their strength once introduced in the Cox model (HRs ranging from 1.95 to 2.22). In the TIQ primary scale the strongest predictors were physical wellbeing, fatigue, functional status and cognitive status (HRs ranging from 1.42 to 1.71), but only fatigue showed an independent prognostic relevance (90% of selection). In the TIQ global scales, the Physical Symptom Index showed a stronger association with survival (HR 1.71) than the Therapy Impact Index (HR 1.47). The former marginally improved the prognostic power of the model when added to clinical variables. Internal validation confirmed that the results were not spurious. CONCLUSIONS: In terminal cancer patients, clinical variables are better predictors of survival than QoL. The large residual variability not accounted for by the model (approximately 70%) suggests that survival is also influenced by factors unlikely to be identified in a survey.
INTRODUCTION: This study compares the relative prognostic power of clinical variables and quality-of-life (QoL) measures in a population of terminal cancerpatients. METHODS: A prospective cohort study in 58 Italian Palliative Care Units. Of the 601 randomly selected terminal cancerpatients, 574 were followed until death in order to compare clinical and QoL variables (using the Therapy Impact Questionnaire (TIQ) as predictors of survival, and assess whether their combined implementation makes prediction more accurate. RESULTS: The clinical variables most strongly associated with survival were dyspnoea, cachexia, Katz's ADL, oliguria, dysphagia, dehydration, liver and acute kidney failure and delirium (hazard ratios (HR) ranging from 2.10 to 3.01). Only the first four kept their strength once introduced in the Cox model (HRs ranging from 1.95 to 2.22). In the TIQ primary scale the strongest predictors were physical wellbeing, fatigue, functional status and cognitive status (HRs ranging from 1.42 to 1.71), but only fatigue showed an independent prognostic relevance (90% of selection). In the TIQ global scales, the Physical Symptom Index showed a stronger association with survival (HR 1.71) than the Therapy Impact Index (HR 1.47). The former marginally improved the prognostic power of the model when added to clinical variables. Internal validation confirmed that the results were not spurious. CONCLUSIONS: In terminal cancerpatients, clinical variables are better predictors of survival than QoL. The large residual variability not accounted for by the model (approximately 70%) suggests that survival is also influenced by factors unlikely to be identified in a survey.
Authors: Niilo Färkkilä; Saku Torvinen; Risto P Roine; Harri Sintonen; Juha Hänninen; Kimmo Taari; Tiina Saarto Journal: Qual Life Res Date: 2013-11-01 Impact factor: 4.147
Authors: Maryam Dosani; Scott Tyldesley; Brendan Bakos; Jeremy Hamm; Tim Kong; Sarah Lucas; Jordan Wong; Mitchell Liu; Sarah Hamilton Journal: Support Care Cancer Date: 2018-02-01 Impact factor: 3.603
Authors: Franzisca Domeisen Benedetti; Christoph Ostgathe; Jean Clark; Massimo Costantini; Maria Laura Daud; Barbara Grossenbacher-Gschwend; Richard Latten; Olav Lindqvist; Andreja Peternelj; Stefanie Schuler; Kali Tal; Agnes van der Heide; Steffen Eychmüller Journal: Support Care Cancer Date: 2012-12-15 Impact factor: 3.603