مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

311
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

130
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

CAN BIOMARKERS IMPROVE ABILITY OF NPI IN RISK PREDICTION? A DECISION TREE MODEL ANALYSIS

Pages

  62-74

Abstract

 Background: The Nottingham Prognostic Index (NPI) is widely-used in the UK for risk stratification of breast cancer patients. This paper aims to evaluate the ability of this index to detect patients with sufficiently low risk of recurrence that they could be spared harsh treatments, and to construct an enhanced prognostic rule that integrates biomarkers with clinical variables to achieve better risk stratification.Methods: We undertook review of published studies of outcomes in risk groups derived by applying NPI, and report estimated event-free rates extracted from papers found. Then we analysed biological and clinical variables for 401 ER+ patients, to develop a Tree-based Survival Model (TSM), for risk prediction, and estimated event-free rates by resulting risk-groups, Kaplan-Meier (K-M) curves corresponding to TSM and NPI were plotted. Results: We concluded that NPI does not distinguish low risk patients with a sufficiently high event-free rate to make it likely clinicians would decide treatments with potential harmful side effects can be avoided in that group. On the other hand, in the decision tree constructed, utilising 3 biomarkers, nodal status and tumour size, the 4 risk groups were clearly diverged in terms of event-free rates. Conclusion: There is considerable potential for improved prognostic modelling by incorporation of biological variables into risk prediction. Whilst low risk patients identified by our TSM model could potentially avoid systemic treatment, higher risk patients might require additional treatment, including chemotherapy or other adjuvant treatment options. However, the decision tree model needs to be validated in a larger clinical trial cohort.

Cites

  • No record.
  • References

  • No record.
  • Cite

    APA: Copy

    BANESHI, M.R., WARNER, P., ANDERSON, N., TOVEY, S., EDWARDS, J., & BARTLETT, J.M.S.. (2010). CAN BIOMARKERS IMPROVE ABILITY OF NPI IN RISK PREDICTION? A DECISION TREE MODEL ANALYSIS. INTERNATIONAL JOURNAL OF CANCER MANAGEMENT (IRANIAN JOURNAL OF CANCER PREVENTION), 3(2), 62-74. SID. https://sid.ir/paper/312474/en

    Vancouver: Copy

    BANESHI M.R., WARNER P., ANDERSON N., TOVEY S., EDWARDS J., BARTLETT J.M.S.. CAN BIOMARKERS IMPROVE ABILITY OF NPI IN RISK PREDICTION? A DECISION TREE MODEL ANALYSIS. INTERNATIONAL JOURNAL OF CANCER MANAGEMENT (IRANIAN JOURNAL OF CANCER PREVENTION)[Internet]. 2010;3(2):62-74. Available from: https://sid.ir/paper/312474/en

    IEEE: Copy

    M.R. BANESHI, P. WARNER, N. ANDERSON, S. TOVEY, J. EDWARDS, and J.M.S. BARTLETT, “CAN BIOMARKERS IMPROVE ABILITY OF NPI IN RISK PREDICTION? A DECISION TREE MODEL ANALYSIS,” INTERNATIONAL JOURNAL OF CANCER MANAGEMENT (IRANIAN JOURNAL OF CANCER PREVENTION), vol. 3, no. 2, pp. 62–74, 2010, [Online]. Available: https://sid.ir/paper/312474/en

    Related Journal Papers

  • No record.
  • Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    Move to top
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button