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Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

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...
Cancer Prevention02:59

Cancer Prevention

Several factors can increase the risk of cancer in an individual. About 50% of cancer cases can be prevented by adopting a healthy lifestyle, regular exercise, eating healthy, and following a modest cancer prevention diet. Epidemiological studies have consistently shown that populations with vegetable and fruit-rich diets have reduced the incidence of cancer. On the other hand, populations who have a diet rich in animal fat, red meat, junk food, or high calories are predisposed to cancer.
Some...
Tumor Progression02:07

Tumor Progression

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.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...

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Related Experiment Video

Updated: May 11, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

[Prognostic factors for cervical cancer].

L Mouková1, R Nenutil, P Fabian

  • 1Oddeleni gynekologicke onkologie, Masarykuv onkologicky, Ustav, Brno.

Klinicka Onkologie : Casopis Ceske a Slovenske Onkologicke Spolecnosti
|May 31, 2013
PubMed
Summary

New biomolecular factors can improve cervical cancer treatment by predicting recurrence risk more accurately than traditional methods. This aids in personalizing therapies for better patient outcomes.

Related Experiment Videos

Last Updated: May 11, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

Area of Science:

  • Gynecological oncology
  • Cancer biomarkers
  • Molecular pathology

Context:

  • Current gynecological oncology guidelines rely on standard prognostic factors.
  • These factors are insufficient for predicting recurrence risk in patients undergoing conservative surgery for cervical cancer.

Purpose:

  • To evaluate new biomolecular prognostic factors for cervical cancer.
  • To assess the predictive power of proteins (p63, TAp63, p16, p21, p27, COX-2) and genes (hTERC, MYCC).

Summary:

  • Traditional prognostic factors in cervical cancer lack the precision to determine the safety of conservative procedures.
  • Biomolecular markers offer enhanced predictive capabilities for disease recurrence and extra-localization spread.
  • Comprehensive evaluation of these factors allows for individualized treatment strategies.

Impact:

  • Improved prediction of cervical cancer recurrence and spread.
  • Personalized surgical, radiotherapeutic, and chemotherapeutic treatment plans.
  • Enhanced patient management and potentially better therapeutic efficacy.