Literature DB >> 29392478

The TEACHH model to predict life expectancy in patients presenting for palliative spine radiotherapy: external validation and comparison with alternate models.

Maryam Dosani1,2, Scott Tyldesley1,2, Brendan Bakos3, Jeremy Hamm3, Tim Kong1,2, Sarah Lucas2,4, Jordan Wong1,2, Mitchell Liu1,2, Sarah Hamilton5,6.   

Abstract

INTRODUCTION: The TEACHH score was developed to identify patients with predicted short (< 3 months) and long (> 1 year) life expectancy. We aimed to validate this model in an independent group of patients presenting for palliative spine radiotherapy and to compare it to alternate prognostic models.
METHODS: We retrospectively reviewed charts of 195 consecutive patients referred for palliative spine radiotherapy. Patients were grouped according to the number of risk factors from the TEACHH model, Chow model, and Oswestry Risk Index.
RESULTS: One hundred and eighty patients with a median age of 65 years were included. Follow-up was 5.8 months in all patients and 31.8 months in living patients. For the TEACHH model, patients in groups 1, 2, and 3 had a median (95% CI) overall survival (OS) of 22.3 (15.7-36.1), 4.9 (3.8-6.6), and 1.5 (0.8-5.4) months, respectively. Wilcoxon pairwise comparisons showed statistically different survival between groups 1 and 2, and 1 and 3. In the Chow model, patients in groups 1, 2, and 3 had a median (95% CI) OS of 16.1 (10.0-22.3), 5.9 (3.8-9.2), and 1.9 (1.2-2.5) months, respectively. There was a significant difference between all groups. The Oswestry Risk Index identified five prognostic groups with median OS (95% CI) ranging from 22.2 (12.9-30.2) to 2.1 (0.8-4.0) months. Only group 1 was statistically different from the others. Although the effect of age was small, the TEACHH model performed best with the inclusion of all parameters.
CONCLUSIONS: The TEACHH model is useful to identify patients with spinal metastases with predicted short, intermediate, and long LE. Its prognostic ability is similar to the Chow model.

Entities:  

Keywords:  LE; Palliation; Prognosis; Radiotherapy; Spinal metastases

Mesh:

Year:  2018        PMID: 29392478     DOI: 10.1007/s00520-018-4064-x

Source DB:  PubMed          Journal:  Support Care Cancer        ISSN: 0941-4355            Impact factor:   3.603


  33 in total

1.  Statistical analysis of prognostic factors for survival in patients with spinal metastasis.

Authors:  Masaki Kataoka; Toshiyuki Kunisada; Masato Tanaka; Ken Takeda; Satoru Itani; Yoshihisa Sugimoto; Haruo Misawa; Masuo Senda; Shinnosuke Nakahara; Toshifumi Ozaki
Journal:  Acta Med Okayama       Date:  2012       Impact factor: 0.892

2.  A new palliative prognostic score: a first step for the staging of terminally ill cancer patients. Italian Multicenter and Study Group on Palliative Care.

Authors:  M Pirovano; M Maltoni; O Nanni; M Marinari; M Indelli; G Zaninetta; V Petrella; S Barni; E Zecca; E Scarpi; R Labianca; D Amadori; G Luporini
Journal:  J Pain Symptom Manage       Date:  1999-04       Impact factor: 3.612

3.  Randomized trial of short- versus long-course radiotherapy for palliation of painful bone metastases.

Authors:  William F Hartsell; Charles B Scott; Deborah Watkins Bruner; Charles W Scarantino; Robert A Ivker; Mack Roach; John H Suh; William F Demas; Benjamin Movsas; Ivy A Petersen; Andre A Konski; Charles S Cleeland; Nora A Janjan; Michelle DeSilvio
Journal:  J Natl Cancer Inst       Date:  2005-06-01       Impact factor: 13.506

4.  Regularization Paths for Generalized Linear Models via Coordinate Descent.

Authors:  Jerome Friedman; Trevor Hastie; Rob Tibshirani
Journal:  J Stat Softw       Date:  2010       Impact factor: 6.440

5.  A predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic.

Authors:  Edward Chow; KinWah Fung; Tony Panzarella; Andrea Bezjak; Cyril Danjoux; Ian Tannock
Journal:  Int J Radiat Oncol Biol Phys       Date:  2002-08-01       Impact factor: 7.038

6.  Validation of a predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic.

Authors:  Edward Chow; Mohamed Abdolell; Tony Panzarella; Kristin Harris; Andrea Bezjak; Padraig Warde; Ian Tannock
Journal:  Int J Radiat Oncol Biol Phys       Date:  2009-01-01       Impact factor: 7.038

7.  Survival prediction in terminally ill cancer patients by clinical estimates, laboratory tests, and self-rated anxiety and depression.

Authors:  Stephan Gripp; Sibylle Moeller; Edwin Bölke; Gerd Schmitt; Christiane Matuschek; Sonja Asgari; Farzin Asgharzadeh; Stephan Roth; Wilfried Budach; Matthias Franz; Reinhardt Willers
Journal:  J Clin Oncol       Date:  2007-08-01       Impact factor: 44.544

8.  Prognostic factors associated with survival in patients with symptomatic spinal bone metastases: a retrospective cohort study of 1,043 patients.

Authors:  Laurens Bollen; Yvette M van der Linden; Willem Pondaag; Marta Fiocco; Bas P M Pattynama; Corrie A M Marijnen; Rob G H H Nelissen; Wilco C Peul; P D Sander Dijkstra
Journal:  Neuro Oncol       Date:  2014-07       Impact factor: 12.300

9.  Prognostic factors in patients with advanced cancer: a comparison of clinicopathological factors and the development of an inflammation-based prognostic system.

Authors:  Barry J Laird; Stein Kaasa; Donald C McMillan; Marie T Fallon; Marianne J Hjermstad; Peter Fayers; Pal Klepstad
Journal:  Clin Cancer Res       Date:  2013-08-12       Impact factor: 12.531

10.  Clinical Predictors of Survival for Patients with Stage IV Cancer Referred to Radiation Oncology.

Authors:  Johnny Kao; Kenneth D Gold; Gina Zarrili; Emily Copel; Andrew J Silverman; Shanta S Ramsaran; Shanata S Ramsaran; David Yens; Samuel Ryu
Journal:  PLoS One       Date:  2015-04-20       Impact factor: 3.240

View more
  3 in total

1.  The LabBM score is an excellent survival prediction tool in patients undergoing palliative radiotherapy.

Authors:  Carsten Nieder; Astrid Dalhaug; Ellinor Haukland
Journal:  Rep Pract Oncol Radiother       Date:  2021-09-30

2.  External validation of life expectancy prognostic models in patients evaluated for palliative radiotherapy at the end-of-life.

Authors:  Adrianna E Mojica-Márquez; Joshua L Rodríguez-López; Ankur K Patel; Diane C Ling; Malolan S Rajagopalan; Sushil Beriwal
Journal:  Cancer Med       Date:  2020-06-26       Impact factor: 4.452

3.  Replacing performance status with a simple patient-reported outcome in palliative radiotherapy prognostic modelling.

Authors:  Daniel Howdon; Wilbert van den Hout; Yvette van der Linden; Katie Spencer
Journal:  Clin Transl Radiat Oncol       Date:  2022-10-03
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.