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Cancer Survival Analysis01:21

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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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The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
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Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...
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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
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Related Experiment Video

Updated: May 2, 2026

Preparation of Peripheral Blood Mononuclear Cell Pellets and Plasma from a Single Blood Draw at Clinical Trial Sites for Biomarker Analysis
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Actionable data analytics in oncology: are we there yet?

Ronald Barkley1, Rhonda Greenapple, John Whang

  • 1Cancer Center Business Development Group, Bedford, NH; Reimbursement Intelligence, Madison, NJ.

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|March 18, 2014
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Summary
This summary is machine-generated.

Most oncology providers lack the necessary analytic capabilities to report on outcomes and costs. However, a significant majority expect to develop these essential data analytics skills within two years.

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Area of Science:

  • Oncology
  • Health Services Research
  • Health Informatics

Background:

  • The shift to value-based care necessitates robust data analytics for oncology providers to measure outcomes and costs.
  • This study assesses the current state of analytic capabilities within oncology practices.
  • The 2013 Cancer Center Business Summit survey explored provider preparedness for value-based reporting.

Discussion:

  • Current analytic capabilities in oncology are limited, hindering the ability to aggregate and report clinical and economic data.
  • A significant gap exists between the demand for value-based data and the current capacity of oncology providers.
  • The survey highlights the challenges in data aggregation, analysis, and reporting for value proposition assessment.

Key Insights:

  • Only 7% of oncology providers currently possess the essential analytic tools for value-based reporting.
  • The majority of oncology providers (60%) anticipate developing these capabilities within the next two years.
  • Actionable data analytics are crucial for meeting internal and external demands in the evolving healthcare landscape.

Outlook:

  • Future investments in health informatics and data analytics are critical for oncology practices.
  • Oncology providers must prioritize developing capabilities for measuring and reporting clinical outcomes and associated costs.
  • The transition to value-based care will likely accelerate the adoption of advanced data analytic solutions in oncology.