TY - JOUR
T1 - HAprog
T2 - A New Prognostic Application to Assist Oncologists in Routine Care
AU - Preto, Daniel D.Almeida
AU - Paiva, Bianca Sakamoto Ribeiro
AU - Hui, David
AU - Bruera, Eduardo
AU - Paiva, Carlos Eduardo
N1 - Publisher Copyright:
© 2022 American Academy of Hospice and Palliative Medicine
PY - 2022/6
Y1 - 2022/6
N2 - Context: More patients are seeing palliative care (PC) earlier in the disease trajectory. The Barretos Prognostic Nomogram (BPN) was designed to fill the gap of survival prognostication for patients with advanced cancer and months of life expectancy. However, its routine use is limited by the common need for a ruler and calculator. Additionally, the BPN requires blood tests. Objectives: The aim is to refine the BPN and to create a prognostic application (App) for use on smartphones. Methods: This is a reanalysis of the two cohorts of advanced cancer patients (development, n=215 and validation, n=276). The variable ‘metastasis’ was revised (volume-site combinations) and ‘KPS’ replaced by ‘ECOG-PS’. Prognostic variables were selected for multivariable Cox and Log-logistic parametric regression analyses; the most accurate final models were identified by backward variable elimination. Calibration and discrimination properties were evaluated in the validation sample. Results: The ‘full version’ model is composed of 6 parameters: sex, locoregional disease, sites of metastasis, ECOG-PS, WBC and albumin. In the ‘clinical version’ model (5 variables), the variable ‘antineoplastic treatment’ was included and the laboratory variables were excluded. At validation, both models were well calibrated and presented adequate c-Index values (0.778 and 0.739). HAprog is a freely downloadable offline App that is used by clinicians to calculate prognosis in less than 1 minute. Conclusion: The new models that integrate HAprog are refined prognostic tools with adequate calibration and discrimination properties. It has potential practical impact for the oncologist dealing with outpatients with advanced cancer during the decision-making process.
AB - Context: More patients are seeing palliative care (PC) earlier in the disease trajectory. The Barretos Prognostic Nomogram (BPN) was designed to fill the gap of survival prognostication for patients with advanced cancer and months of life expectancy. However, its routine use is limited by the common need for a ruler and calculator. Additionally, the BPN requires blood tests. Objectives: The aim is to refine the BPN and to create a prognostic application (App) for use on smartphones. Methods: This is a reanalysis of the two cohorts of advanced cancer patients (development, n=215 and validation, n=276). The variable ‘metastasis’ was revised (volume-site combinations) and ‘KPS’ replaced by ‘ECOG-PS’. Prognostic variables were selected for multivariable Cox and Log-logistic parametric regression analyses; the most accurate final models were identified by backward variable elimination. Calibration and discrimination properties were evaluated in the validation sample. Results: The ‘full version’ model is composed of 6 parameters: sex, locoregional disease, sites of metastasis, ECOG-PS, WBC and albumin. In the ‘clinical version’ model (5 variables), the variable ‘antineoplastic treatment’ was included and the laboratory variables were excluded. At validation, both models were well calibrated and presented adequate c-Index values (0.778 and 0.739). HAprog is a freely downloadable offline App that is used by clinicians to calculate prognosis in less than 1 minute. Conclusion: The new models that integrate HAprog are refined prognostic tools with adequate calibration and discrimination properties. It has potential practical impact for the oncologist dealing with outpatients with advanced cancer during the decision-making process.
KW - application
KW - Cancer
KW - clinical prediction of survival
KW - palliative care
KW - prognostic markers
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U2 - 10.1016/j.jpainsymman.2022.02.004
DO - 10.1016/j.jpainsymman.2022.02.004
M3 - Article
C2 - 35157984
AN - SCOPUS:85127326407
SN - 0885-3924
VL - 63
SP - 1014-1021.e4
JO - Journal of pain and symptom management
JF - Journal of pain and symptom management
IS - 6
ER -