PREDICT: Survival prediction in patients with breast cancer - Evidencio
PREDICT: Survival prediction in patients with breast cancer
Current version is to assess the integration possibilities using the URL
PREDICT is designed to calculate estimates of survival with and without adjuvant treatment to show the predicted benefit of providing specific treatment options. 
Autori della ricerca: Wishart GC, Azzato EM, Greenberg DC, Rashbass J, Kearins O, Lawrence G, Caldas C, Pharoah PD
Versione: 1.7
  • Pubblico
  • Oncologia
  • Algoritmo R-Script
  • Dettagli
  • Convalida del algoritmo
  • Salvare l'input
  • Ingresso di carico
  • Inglese Olandese

Age

0
100
Year

Menopausal

Tumor size

0
150
mm

Positive nodes

0
25
Lymph nodes

Tumour grade

Detected by

ER status

HER2 status

KI67 status

Chemotherapy

Result display

Predicted survival is: ... %

Impostare tutti i parametri per calcolare la previsione.

How this model can be applied: 
Online prognostic tools such as PREDICT are increasingly used by oncologists in clinical practice to inform patients and support treatment decisions regarding adjuvant, systemic therapy. Validation studies have shown that PREDICT generally provides reasonable to good estimates for overall 5- and 10-year mortality in patients with breast cancer.1-3

Limitations:
Prognostic tools such as PREDICT should be used with caution because of intrinsic variations in outcomes obtained and because the threshold to discuss adjuvant, systemic treatment is low. In a number of subgroups, PREDICT shows under- and overestimates, according to a study published in 2017 by Ellen G. Engelhardt (LUMC) and a group of colleagues from home and abroad.4 

Scientific Support: 
Several validation studies have been conducted internationally on the performance of PREDICT (see 'validations' tab at www.evidencio.com). In June 2017, a study on the prognostic accuracy of PREDICT was published by Ellen G. Engelhardt and colleagues.4 The researchers collected a consecutive series of 2,710 patients with breast cancer aged 50 years or younger diagnosed between 1990 and 2000. C-statistics were used to estimate calibration accuracy and discriminant accuracy for overall 10-year mortality and breast cancer-specific mortality. 

Overall, PREDICT's calibration proved good (predicted versus observed overall mortality). However, PREDICT does tend to underestimate overall mortality (regardless of cause of death) in subgroups with good prognosis (degree of underestimation: -2.9% to -4.8%) and overestimate it in subgroups with poor prognosis (degree of overestimation: 2.6% to 9.4%). In patients up to 35 years of age, PREDICT underestimated overall mortality by 6.6%. Breast cancer-specific mortality was overestimated by PREDICT by 3.2%. The researchers also observed an apparent overestimation of breast cancer-specific mortality in various subgroups (range 3.2% to 14.1%). 

References:

  1. Wishart GC, Azzato EM, Greenberg DC, et al. PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer. Breast Cancer Res. 2010;12(1):R1.
  2. Wishart GC, Bajdik CD, Dicks E, et al. PREDICT Plus: development and validation of a prognostic model for early breast cancer that includes HER2. Br. J. Cancer 2012;107(5):800-7.
  3. Wishart GC, Rakha E, Green A, et al. Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer. BMC Cancer. 2014;14:908.
  4. Engelhardt EG, van den Broek AJ, Linn SC, et al. Accuracy of the online prognostication tools PREDICT and Adjuvant! for early-stage breast cancer patients younger than 50 years. Eur J Cancer. 2017;78:37-44.

Questo algoritmo viene fornito a scopo educativo, formativo e informativo. Non deve essere utilizzato a supporto di decisioni mediche o per fornire servizi medici o diagnostici. Leggete il nostro sito completo disclaimer.

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