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Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

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Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
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Tumor Progression02:07

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Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
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Related Experiment Video

Updated: Jun 23, 2025

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

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Breast cancer symptom profile longitudinal changes: data mining study.

Mohammad Fathian1, Farzane Akbari2

  • 1Iran University of Science and Technology, Tehran, Iran fathian@iust.ac.ir.

BMJ Supportive & Palliative Care
|June 25, 2024
PubMed
Summary
This summary is machine-generated.

Breast cancer patients undergoing chemotherapy experience stable psychological and physiological symptoms, including depression and anxiety. Addressing these persistent symptoms is crucial for improving patient quality of life.

Keywords:
Breast

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Area of Science:

  • Oncology
  • Psychology
  • Symptom Science

Background:

  • Chemotherapy for breast cancer (BC) can cause significant psychological and physiological symptoms.
  • Identifying stable symptom clusters is key to effective symptom management and improving patient outcomes during treatment.

Purpose of the Study:

  • To examine the stability of co-occurring symptoms in Iranian breast cancer patients receiving chemotherapy.
  • To evaluate symptom cluster stability across three distinct time points during the chemotherapy treatment process.

Main Methods:

  • Data collected at three time points: chemotherapy initiation, 2.5 months, and 5 months postdiagnosis.
  • Employed exploratory factor analysis (EFA), hierarchical cluster analysis (HCA), and K-means clustering to identify symptom patterns.

Main Results:

  • EFA identified five consistent symptom clusters across all time points.
  • Key clusters included depression, anxiety, and irritability; sexual interest and pain; and diarrhea and vomiting.
  • Depression and anxiety symptoms remained notably stable over time, with some initial symptoms like vomiting and dry mouth decreasing in frequency.

Conclusions:

  • Psychological (depression, anxiety) and physiological symptoms in breast cancer patients are generally stable throughout treatment.
  • Palliative care interventions targeting persistent symptoms can enhance patient quality of life and the overall treatment experience.