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Related Concept Videos

Kaplan-Meier Approach01:24

Kaplan-Meier Approach

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The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
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Guidelines for Writing Outcome01:11

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When developing expected outcomes for a patient care plan, the nurse should adhere to the following recommendations:
Patient outcomes reflect the patient's response to the goal rather than what the nurse aims to achieve. Terminology should be observable and measurable to avoid the reader's interpretation. The desired outcome should be realistic and achievable in the designated care timeframe. Expected outcomes should align with adjunctive therapies. The outcome should enhance care...
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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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Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

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Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
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Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

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Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
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Nursing Evaluation01:15

Nursing Evaluation

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The evaluation stage signals the end of the nursing process. The nurse gathers evaluative data to assess whether or not the patient has attained the expected results. Whereas the nurse collects data in the nursing assessment to identify the patient's health concerns, the evaluation stage data determines if the indicated health issues are resolved. Evaluative data collection includes two sections: the data acquired to evaluate patient outcomes and the time criteria for data collection.
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Related Experiment Video

Updated: May 31, 2025

E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
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Survival Endpoints: Patient-Reported Experience Measures and Patient-Reported Outcome Measures as Quality Indicators

B Chacko1, N Jose2, C T Kainickal2

  • 1Government Medical College Trivandrum, Kerala, 695011, India.

Clinical Oncology (Royal College of Radiologists (Great Britain))
|January 22, 2025
PubMed
Summary
This summary is machine-generated.

Patient reported outcomes are crucial for personalized cancer care, offering valuable insights beyond traditional survival endpoints. Incorporating these measures ensures comprehensive, value-based oncology practices.

Keywords:
Patient-reported experience measures (PREMs)patient-reported outcome measures (PROMs)quality indicatorssurvival outcomes

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Area of Science:

  • Oncology
  • Healthcare Quality
  • Patient-Centered Care

Background:

  • Cancer treatment requires individualized approaches due to tumor heterogeneity.
  • Patient reported outcomes (PROs) are increasingly recognized as vital quality indicators in oncology.
  • PROs utilize validated instruments to capture patient health status and experiences.

Purpose of the Study:

  • To review the relevance of patient reported measures in current oncology.
  • To explore implementation challenges and barriers for PROs.
  • To advocate for the integration of PROs into cancer care guidelines.

Main Methods:

  • Literature review of patient reported outcomes in oncology.
  • Analysis of the role of PROs as surrogate markers.
  • Discussion of policy implications for PRO integration.

Main Results:

  • Patient reported outcomes offer a patient-centered perspective complementing survival endpoints.
  • Implementation of PROs faces practical barriers and challenges.
  • PROs are essential for delivering value-based, comprehensive cancer care.

Conclusions:

  • Patient reported outcomes should be integrated as surrogate markers alongside survival endpoints.
  • New policy guidelines are needed to incorporate PROs into future oncology practice.
  • Adoption of PROs enhances the quality and personalization of cancer care.