Cancer Epidemiology

Overview – Cancer Epidemiology

Cancer epidemiology is the study of the distribution, patterns, causes, and control of cancer in populations. It is a cornerstone of public health and clinical medicine, especially due to cancer’s chronic nature, long latency period, and complex, multifactorial causality. Despite its relatively low overall population frequency (<5%), cancer remains a major global health burden. Understanding cancer epidemiology allows us to identify modifiable risk factors, measure incidence and mortality, evaluate screening tools, and improve patient outcomes through prevention and early detection strategies.

Definition

• Epidemiology: The study of health and disease in populations, focusing on the distribution and determinants of diseases.
• Cancer epidemiology is unique because:
  • Cancer is a chronic disease
  • Long latency periods (can remain asymptomatic for years)
  • Relatively rare in population terms (<5%), making incidence measures statistically challenging

Patterns of Disease

• Sporadic: Isolated or random cases of disease
• Endemic: The baseline, expected rate of disease in a given population
• Epidemic: A sudden increase in disease incidence above baseline
• Pandemic: When an epidemic spreads across countries or continents

Clinical Epidemiology

Purpose

Clinical epidemiology uses statistical methods, probability, and population-level data to guide evidence-based clinical decisions.

Key Terms

• Incidence:
  • General incidence: New cases per population over time
  • Incidence proportion (cumulative incidence): New cases among “at-risk” population during a time period
  • True incidence: Adjusted for changing populations;
    • Formula: New cases ÷ Average number at risk over the period
    • Average number at risk = (number at start + number at end) / 2
    • Units: Measured in person-years (e.g. 1 person for 1 year = 12 people for 1 month each)
• Prevalence:
  • Point prevalence: Total cases at a specific time
  • Period prevalence: Proportion of population who had the disease during a time window
  • Note: More useful in chronic diseases
• Mortality: Deaths due to specific disease ÷ total population
• Survival:
  • Commonly expressed as 5-year survival rate
  • I.e. % of patients surviving 5 years after diagnosis
• Lifetime Risk: Likelihood of developing the disease if one lives to 90

Study Types in Cancer Epidemiology

Observational Studies

• Cohort Study:
  • Begin with groups with and without exposure to a risk factor
  • Prospective: Follow over time to see who develops disease
• Case-Control Study:
  • Begin with groups with and without disease
  • Retrospective: Determine whether they were exposed to risk factors

Experimental Studies

• Animal models (not ethical to expose humans to suspected carcinogens)
• Natural experiments: Observe populations incidentally exposed (e.g. disasters, industrial accidents)

Causal Relationships in Cancer

Types of Causes

• Primary Causes:
  • Necessary for disease but not always sufficient
  • E.g. smoking, radiation, inherited mutations
• Secondary Causes:
  • Enabling or reinforcing risk factors
  • E.g. age, immune suppression

Types of Causal Relationships

• Direct: A → B
• Causal network: A + B + C → D
• Modified: A is influenced by C, resulting in B

Criteria for Causality

• Dose dependency
• Consistency
• Specificity
• Time sequence
• Coherence
• Analogy

Common Cancer Risk Factors

• Geography
• Environment
• Occupation
• Diet
• Gender
• Race
• Culture
• Genetics

Non-Causal Relationships

• Correlation (without causation)
• Confounding variables
• Random chance
• Selection bias
• Incidentals

Measuring Association Strength

Risks

• Risk: Incidence × duration
• Relative Risk (RR):
  • RR = Risk in exposed ÷ Risk in unexposed
  • E.g. RR = 5 means 5x increased risk
• Attributable Risk (AR):
  • AR = Risk in exposed − Risk in unexposed
  • Indicates the excess risk due to exposure
• Odds Ratio (OR):
  • OR = Odds of disease in exposed ÷ Odds in non-exposed
  • Most used in case-control studies

Probabilities

• Sensitivity: Probability that a test correctly detects disease (true positive rate)
• Specificity: Probability that a test correctly detects absence of disease (true negative rate)
• Positive Predictive Value (PPV):
  • Probability that a person has the disease given a positive test result
  • Example:
    • DRE: Sensitivity 69%, Specificity 97%, Prevalence 0.5%
    • PSA: Sensitivity 80%, Specificity 95%, Prior Probability = 10%
    • Combined DRE + PSA → PPV ≈ 64% → 64% chance the patient has prostate cancer

Specific Cancer Epidemiology

Lung Cancer

• Risk factors:
  • Smoking (30% lifetime risk)
  • TB
  • Asbestos
  • Radiation
  • Air pollution
• Incidence:
  • Higher in men, low SES, Indigenous Australians, rural areas
  • Peak age ≈70 years

Oesophageal Cancer

• Risk factors:
  • Smoking, alcohol, nitrosamines, precancerous lesions
• Incidence:
  • Peaks 70–80 years, 3:1 male:female

Lymphomas

• Hodgkin’s:
  • Possible link to EBV
  • Bimodal: young adults + elderly
• Non-Hodgkin’s:
  • Immunosuppression, comorbidities
  • Incidence increases with age

Bladder Cancer

• Risk factors:
  • Aniline dye exposure, smoking, chronic UTIs, schistosomiasis
• Incidence:
  • Males > females; peak at 60–70 years

Breast Cancer

• Risk factors:
  • Age, developed-country residency, personal/family history, early menarche, nulliparity, HRT
• Incidence:
  • Primarily in women; increases with age
• Early detection:
  • Reduces advanced disease
  • Improves treatment options & quality of life
  • May cause psychological harm without extending life expectancy

Prostate Cancer

• Risk factors:
  • Age, diet, occupational exposures, genetics
• Incidence:
  • Rising due to aging population
• Screening example:
  • Man aged 65, asymptomatic
  • Prevalence = 0.5%
  • DRE: Sensitivity 69%, Specificity 97%
  • PSA: Sensitivity 80%, Specificity 95%
  • Combined → PPV ≈ 64%

Colorectal Cancer

• Risk factors:
  • Environmental (diet, lifestyle, low fibre, high meat/fat intake)
  • Genetics (FAP, HNPCC, IBD)
• Incidence:
  • Rising in western countries; higher mortality in low SES
• Screening:
  • Faecal Occult Blood Test is most effective

Melanoma

• Risk factors:
  • UV exposure, fair skin, red hair, family history, moles
• Incidence:
  • Common in tropical regions; 11% lifetime risk

Non-Melanoma Skin Cancer

• Risk factors:
  • UV exposure, age, skin type
• Incidence:
  • BCC = 66%, SCC = 33%
  • Lifetime risk = 66%

Kidney Cancer

• Risk factors:
  • Smoking, high protein diet, obesity, hypertension, toxins
• Incidence:
  • RCC = 85% of cases
  • 2x more common in men

Stomach (Gastric) Cancer

• Risk factors:
  • Preserved/smoked foods, H. pylori, smoking, low fruit/veg
• Incidence:
  • Men >40 years; 2:1 male:female ratio

Brain Cancer

• Risk factors:
  • Age, genetics, immune disorders, radiation, vinyl chloride
• Incidence:
  • Highest in Australia
  • Bimodal (children <12, adults >55)

Cervical Cancer

• Risk factors:
  • HPV infection, smoking, immunosuppression, early sexual activity, contraceptives
• Incidence:
  • 5th most fatal female cancer

Uterine Cancer

• Risk factors:
  • Age, obesity, nulliparity, irregular menses, oestrogen therapy
• Incidence:
  • Peaks 60–70 years

Ovarian Cancer

• Risk factors:
  • Age, family history
  • Protective: contraception, multiple births
• Incidence:
  • 9th most common female cancer

Testicular Cancer

• Risk factors:
  • Undescended testes, family history, prior testicular cancer
• Incidence:
  • Most common in men aged 25–35
  • More prevalent in Caucasians

Summary – Cancer Epidemiology

Cancer epidemiology provides essential insight into how cancers arise, spread, and affect populations. From study design to causal inference and prevention, its scope spans clinical and public health domains. With rising global cancer incidence, especially in aging and westernized populations, an evidence-based understanding of cancer trends and risks is more important than ever. For a broader context, see our Genetics & Cancer Overview page.