Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

805
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...
805
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

1.1K
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
1.1K
Prevalence and Incidence01:08

Prevalence and Incidence

2.1K
In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
2.1K
Actuarial Approach01:20

Actuarial Approach

339
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
339
Cancer Prevention02:59

Cancer Prevention

8.3K
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...
8.3K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

1.5K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
1.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The mortality impacts of implementing the 3-30-300 greenness rule and the WHO air quality guidelines in Bari, Southern Italy.

Scientific reports·2026
Same author

Prognostic models in populations with heart failure: a systematic review and meta-analysis.

Systematic reviews·2026
Same author

Prognostic Models for Disease Progression and Outcomes in Chronic Obstructive Pulmonary Disease: A Systematic Review and Meta-Analysis.

Journal of clinical medicine·2025
Same author

Incidence rates and trends of paediatric cancer in Italy, 2008-2017.

Cancer epidemiology·2025
Same author

[Climactions project. Environmental, socioeconomic, and territorial vulnerability in 5 Italian cities].

Epidemiologia e prevenzione·2025
Same author

When Real-World Outcomes Do Not Meet the Results of Clinical Trials: Transfemoral Transcatheter vs. Surgical Aortic Valve Replacement in an Intermediate-Age Population (The Outstanding Italy Study).

Journal of clinical medicine·2025

Related Experiment Video

Updated: Mar 1, 2026

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

7.3K

Cancer incidence estimation method: an Apulian experience.

Anna M Nannavecchia1, Ivan Rashid, Francesco Cuccaro

  • 1aCancer Registry of Apulia, Health Regional Agency of Apulia bCancer Registry of Apulia, Local Health Unit of Barletta-Andria-Trani, Bari, Italy.

European Journal of Cancer Prevention : the Official Journal of the European Cancer Prevention Organisation (ECP)
|June 3, 2017
PubMed
Summary

A new method estimates cancer incidence in Puglia, Italy, using available data to map regional variations. This approach helps plan health services even with incomplete cancer registry data.

More Related Videos

Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection
07:35

Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection

Published on: June 8, 2020

7.5K
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

956

Related Experiment Videos

Last Updated: Mar 1, 2026

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

7.3K
Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection
07:35

Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection

Published on: June 8, 2020

7.5K
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

956

Area of Science:

  • Oncology
  • Public Health
  • Biostatistics

Background:

  • The Cancer Registry of Puglia (RTP) was established in 2008, covering over 4 million inhabitants across six sections.
  • Currently, only four of the six RTP sections are accredited by AIRTUM, representing 53% of the regional population.
  • Accurate cancer incidence data is crucial for understanding regional geographic variability and planning health services.

Purpose of the Study:

  • To develop and validate an original estimation method for complete territorial coverage of cancer incidence in Puglia.
  • To address potential regional geographic disparities in cancer incidence.
  • To support health services planning by providing comprehensive cancer incidence data.

Main Methods:

  • Utilized incidence data from accredited RTP sections (2006-2008), regional hospitalization data (2001-2009), and mortality data (2006-2009).
  • Developed an estimation method combining accredited sections' rates with mortality and hospitalization ratios for non-accredited sections.
  • Validated the estimation method against real incidence data and applied it to calculate population-weighted regional cancer rates.

Main Results:

  • The developed estimation method demonstrated accuracy, with estimated rates closely matching real incidence data.
  • Identified the most frequent neoplasms in Apulia: breast, colon-rectum, and thyroid cancer in women; prostate, lung, and colon-rectum cancer in men.
  • The study successfully estimated regional cancer rates, accounting for geographic variability.

Conclusions:

  • The novel estimation method provides a reliable approach to assess cancer incidence when complete registration data is unavailable.
  • This method is valuable for health services planning and understanding cancer patterns in regions with partial data.
  • The findings highlight the importance of addressing data gaps for effective cancer control strategies.