Literature DB >> 8680066

A computer based program to assist in adjuvant therapy decisions for individual breast cancer patients.

P M Ravdin1.   

Abstract

This paper describes a personal computer based tool to aid in decision making about whether a woman should receive adjuvant therapy for breast cancer. This tool can assist in engaging women with primary breast cancer in the discussion about: 1) her risk of breast cancer related mortality if she receives only local control measures, but no systemic adjuvant therapy, 2) how much receiving adjuvant therapy may reduce this risk, and 3) what the impact of receiving the adjuvant systemic therapy is in terms of survival. The tool utilizes life table analytical techniques to project outcomes after entry of patient age (used to calculate natural mortality rates), estimated risk of breast cancer related mortality (with a help tool allowing the physician to use estimates based on national database information), and estimate of the efficacy of adjuvant chemotherapy (with included tables of estimates based on the Early Breast Cancer Trialists' meta-analysis). Computer based tools can serve as valuable aids in patient and physician education, and the process of informed decision making.

Entities:  

Mesh:

Year:  1995        PMID: 8680066

Source DB:  PubMed          Journal:  Bull Cancer        ISSN: 0007-4551            Impact factor:   1.276


  10 in total

Review 1.  Computer-generated patient education materials: do they affect professional practice? A systematic review.

Authors:  Shaun P Treweek; Claire Glenton; Andrew D Oxman; Alister Penrose
Journal:  J Am Med Inform Assoc       Date:  2002 Jul-Aug       Impact factor: 4.497

2.  Nomogram Identifies Age as the Most Important Predictor of Overall Survival in Oral Cavity Squamous Cell Cancer After Primary Surgery.

Authors:  Supriya Gupta; Jennifer Waller; Jimmy Brown; Yolanda Elam; James V Rawson; Darko Pucar
Journal:  Indian J Otolaryngol Head Neck Surg       Date:  2019-08-16

3.  Nomogram for predicting the benefit of adjuvant chemoradiotherapy for resected gallbladder cancer.

Authors:  Samuel J Wang; Andrew Lemieux; Jayashree Kalpathy-Cramer; Celine B Ord; Gary V Walker; C David Fuller; Jong-Sung Kim; Charles R Thomas
Journal:  J Clin Oncol       Date:  2011-11-07       Impact factor: 44.544

4.  Modern Risk Assessment for Individualizing Treatment Concepts in Early-stage Breast Cancer.

Authors:  Alex Farr; Rachel Wuerstlein; Annika Heiduschka; Christian F Singer; Nadia Harbeck
Journal:  Rev Obstet Gynecol       Date:  2013

5.  An interactive tool for individualized estimation of conditional survival in rectal cancer.

Authors:  Samuel J Wang; Amanda R Wissel; Join Y Luh; C David Fuller; Jayashree Kalpathy-Cramer; Charles R Thomas
Journal:  Ann Surg Oncol       Date:  2011-01-05       Impact factor: 5.344

6.  Does use of the adjuvant! model influence use of adjuvant therapy through better risk communication?

Authors:  Jeffrey K Belkora; David W Hutton; Dan H Moore; Laura A Siminoff
Journal:  J Natl Compr Canc Netw       Date:  2011-07-01       Impact factor: 11.908

7.  External validation of Adjuvant! Online breast cancer prognosis tool. Prioritising recommendations for improvement.

Authors:  David Hajage; Yann de Rycke; Marc Bollet; Alexia Savignoni; Martial Caly; Jean-Yves Pierga; Hugo M Horlings; Marc J Van de Vijver; Anne Vincent-Salomon; Brigitte Sigal-Zafrani; Claire Senechal; Bernard Asselain; Xavier Sastre; Fabien Reyal
Journal:  PLoS One       Date:  2011-11-08       Impact factor: 3.240

8.  The impact of thyroid cancer and post-surgical radioactive iodine treatment on the lives of thyroid cancer survivors: a qualitative study.

Authors:  Anna M Sawka; David P Goldstein; James D Brierley; Richard W Tsang; Lorne Rotstein; Shereen Ezzat; Sharon Straus; Susan R George; Susan Abbey; Gary Rodin; Mary Ann O'Brien; Amiram Gafni; Lehana Thabane; Jeannette Goguen; Asima Naeem; Lilian Magalhaes
Journal:  PLoS One       Date:  2009-01-14       Impact factor: 3.240

9.  Oncologist use of the Adjuvant! model for risk communication: a pilot study examining patient knowledge of 10-year prognosis.

Authors:  Jeffrey K Belkora; Hope S Rugo; Dan H Moore; David W Hutton; Daniel F Chen; Laura J Esserman
Journal:  BMC Cancer       Date:  2009-04-28       Impact factor: 4.430

10.  Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis.

Authors:  Molly E Klein; David J Dabbs; Yongli Shuai; Adam M Brufsky; Rachel Jankowitz; Shannon L Puhalla; Rohit Bhargava
Journal:  Mod Pathol       Date:  2013-03-15       Impact factor: 7.842

  10 in total

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