This statistic shows the rate of registrations of newly diagnosed cases of lung cancer per 100,000 population in England in 2020, by region and gender. With a rate of 100.8 newly diagnosed males with lung cancer and 90.8 females per 100,000 population in 2020, the region most affected by lung cancer was the North East.

This dataset contains data about lung cancer Mortality. This database is a comprehensive collection of patient information, specifically focused on individuals diagnosed with cancer. It is designed to facilitate the analysis of various factors that may influence cancer prognosis and treatment outcomes. The database includes a range of demographic, medical, and treatment-related variables, capturing essential details about each patient's condition and history.

Key components of the database include:

Demographic Information: Basic details about the patients such as age, gender, and country of residence. This helps in understanding the distribution of cancer cases across different populations and regions.

Medical History: Information about each patient’s medical background, including family history of cancer, smoking status, Body Mass Index (BMI), cholesterol levels, and the presence of other health conditions such as hypertension, asthma, cirrhosis, and other cancers. This section is crucial for identifying potential risk factors and comorbidities.

Cancer Diagnosis: Detailed data about the cancer diagnosis itself, including the date of diagnosis and the stage of cancer at the time of diagnosis. This helps in tracking the progression and severity of the disease.

Treatment Details: Information regarding the type of treatment each patient received, the end date of the treatment, and the outcome (whether the patient survived or not). This is essential for evaluating the effectiveness of different treatment approaches.

The structure of the database allows for in-depth analysis and research, making it possible to identify patterns, correlations, and potential causal relationships between various factors and cancer outcomes. It is a valuable resource for medical researchers, epidemiologists, and healthcare providers aiming to improve cancer treatment and patient care.

id: A unique identifier for each patient in the dataset. age: The age of the patient at the time of diagnosis. gender: The gender of the patient (e.g., male, female). country: The country or region where the patient resides. diagnosis_date: The date on which the patient was diagnosed with lung cancer. cancer_stage: The stage of lung cancer at the time of diagnosis (e.g., Stage I, Stage II, Stage III, Stage IV). family_history: Indicates whether there is a family history of cancer (e.g., yes, no). smoking_status: The smoking status of the patient (e.g., current smoker, former smoker, never smoked, passive smoker). bmi: The Body Mass Index of the patient at the time of diagnosis. cholesterol_level: The cholesterol level of the patient (value). hypertension: Indicates whether the patient has hypertension (high blood pressure) (e.g., yes, no). asthma: Indicates whether the patient has asthma (e.g., yes, no). cirrhosis: Indicates whether the patient has cirrhosis of the liver (e.g., yes, no). other_cancer: Indicates whether the patient has had any other type of cancer in addition to the primary diagnosis (e.g., yes, no). treatment_type: The type of treatment the patient received (e.g., surgery, chemotherapy, radiation, combined). end_treatment_date: The date on which the patient completed their cancer treatment or died. survived: Indicates whether the patient survived (e.g., yes, no).

This dataset contains artificially generated data with as close a representation of reality as possible. This data is free to use without any licence required.

Good luck Gakusei!

In 2022, 83.2 males and 69.3 females per 100,000 population in England were registered as newly diagnosed with malignant neoplasm of bronchus and lung. Over the analyzed years, the rate of newly diagnosed cases for male individuals has seen a decrease trend. Conversely, the rate of newly diagnosed cases for females has seen a steady increase over the years. This statistic shows the rate of newly diagnosed cases of lung cancer per 100,000 population in England from 1995 to 2022, by gender.

Lung Cancer Deaths reports the number, crude rate, and age-adjusted mortality rate (AAMR) of deaths due to lung cancer.

As of 2020, the age-standardized incidence rate of lung cancer worldwide was 22.4 per 100,000 population. At this time, the incidence rate of lung cancer was highest in Polynesia. This statistic shows the age-standardized incidence rate of lung cancer worldwide as of 2020, by region.

About Dataset 📌 Overview This dataset has been carefully synthesized to support research in lung cancer survival prediction, enabling the development of models that estimate:

Whether a patient is likely to survive at least one year post-diagnosis (Binary Classification). The probability of survival based on clinical and lifestyle factors (Regression Analysis). The dataset is designed for machine learning and deep learning applications in medical AI, oncology research, and predictive healthcare.

📜 Dataset Generation Process The dataset was generated using a combination of real-world epidemiological insights, medical literature, and statistical modeling. The feature distributions and relationships have been carefully modeled to reflect real-world clinical scenarios, ensuring biomedical validity.

📖 Medical References & Sources The dataset structure is based on well-established lung cancer risk factors and survival indicators documented in leading medical research and clinical guidelines:

World Health Organization (WHO) Reports on lung cancer epidemiology. National Cancer Institute (NCI) & American Cancer Society (ACS) guidelines on lung cancer risk factors and treatment outcomes. The IASLC Lung Cancer Staging Project (8th Edition): Standard reference for lung cancer staging. Harrison’s Principles of Internal Medicine (20th Edition): Provides an in-depth review of lung cancer diagnosis and treatment. Lung Cancer: Principles and Practice (2022, Oxford University Press): Clinical insights into lung cancer detection, treatment, and survival factors. 🔬 Features of the Dataset Each record in the dataset represents an individual’s clinical condition, lifestyle risk factors, and survival outcome. The dataset includes the following features:

1️⃣ Patient Demographics Age → A key risk factor for lung cancer progression and survival. Gender → Male and female lung cancer survival rates can differ. Residence → Urban vs. Rural (impact of environmental factors). 2️⃣ Risk Factors & Lifestyle Indicators These factors have been linked to lung cancer risk in epidemiological studies:

Smoking Status → (Current Smoker, Former Smoker, Never Smoked). Air Pollution Exposure → (Low, Moderate, High). Biomass Fuel Use → (Yes/No) – Associated with household air pollution. Factory Exposure → (Yes/No) – Industrial exposure increases lung cancer risk. Family History → (Yes/No) – Genetic predisposition to lung cancer. Diet Habit → (Vegetarian, Non-Vegetarian, Mixed) – Nutritional impact on cancer progression. 3️⃣ Symptoms (Primary Predictors) These are key clinical indicators associated with lung cancer detection and severity:

Hemoptysis (Coughing Blood) Chest Pain Fatigue & Weakness Chronic Cough Unexplained Weight Loss 4️⃣ Tumor Characteristics & Clinical Features Tumor Size (mm) → The size of the detected tumor. Histology Type → (Adenocarcinoma, Squamous Cell Carcinoma, Small Cell Carcinoma). Cancer Stage → (Stage I to Stage IV). 5️⃣ Treatment & Healthcare Facility Treatment Received → (Surgery, Chemotherapy, Radiation, Targeted Therapy). Hospital Type → (Private, Government, Medical College). 6️⃣ Target Variables (Predicted Outcomes) Survival (Binary) → 1 (Yes) if the patient survives at least 1 year, 0 (No) otherwise. Survival Probability (%) (Can be derived) → Estimated probability of survival within one year. ⚡ Why This Dataset is Valuable? ✅ Balanced Data Distribution Designed to ensure a representative distribution of lung cancer survival cases. Prevents model bias and improves generalization in predictive models. ✅ Medically-Inspired Feature Engineering Features are derived from real-world lung cancer risk factors, validated through medical literature. Incorporates both lifestyle and clinical indicators to enhance predictive accuracy.(no real person data is used,just have made an biomedical environment) ✅ Diverse Risk Factors Considered Smoking, air pollution, and genetic history as primary lung cancer contributors. Symptom severity and tumor histology influence survival rates. ✅ Scalability & ML Suitability Ideal for classification and regression tasks in machine learning. Can be used with deep learning (TensorFlow, PyTorch), ML models (XGBoost, Random Forest, SVM), and explainable AI techniques like SHAP and LIME. 📂 Dataset Usage & Applications This dataset is highly useful for multiple healthcare AI applications, including:

🩺 Predictive Analytics → Early detection of high-risk lung cancer patients. 🤖 Healthcare Chatbots → AI-powered risk assessment tools.

BackgroundUnderstanding the effects of demographic drivers on lung cancer mortality trends is critical for lung cancer control. We have examined the drivers of lung cancer mortality at the global, regional, and national levels.MethodsData on lung cancer death and mortality were extracted from the Global Burden of Disease (GBD) 2019. Estimated annual percentage change (EAPC) in the age-standardized mortality rate (ASMR) for lung cancer and all-cause mortality were calculated to measure temporal trends in lung cancer from 1990 to 2019. Decomposition analysis was used to analyze the contributions of epidemiological and demographic drivers to lung cancer mortality.ResultsDespite a non-significant decrease in ASMR [EAPC = −0.31, 95% confidence interval (CI): −1.1 to 0.49], the number of deaths from lung cancer increased by 91.8% [95% uncertainty interval (UI): 74.5–109.0%] between 1990 and 2019. This increase was due to the changes in the number of deaths attributable to population aging (59.6%), population growth (56.7%), and non-GBD risks (3.49%) compared with 1990 data. Conversely, the number of lung cancer deaths due to GBD risks decreased by 19.8%, mainly due to tobacco (−12.66%), occupational risks (−3.52%), and air pollution (−3.47%). More lung cancer deaths (1.83%) were observed in most regions, which were due to high fasting plasma glucose levels. The temporal trend of lung cancer ASMR and the patterns of demographic drivers varied by region and gender. Significant associations were observed between the contributions of population growth, GBD risks and non-GBD risks (negative), population aging (positive), and ASMR in 1990, the sociodemographic index (SDI), and the human development index (HDI) in 2019.ConclusionPopulation aging and population growth increased global lung cancer deaths from 1990 to 2019, despite a decrease in age-specific lung cancer death rates due to GBD risks in most regions. A tailored strategy is needed to reduce the increasing burden of lung cancer due to outpacing demographic drivers of epidemiological change globally and in most regions, taking into account region- or gender-specific risk patterns.

Death rate has been age-adjusted by the 2000 U.S. standard population. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Lung cancer is a leading cause of cancer-related death in the US. People who smoke have the greatest risk of lung cancer, though lung cancer can also occur in people who have never smoked. Most cases are due to long-term tobacco smoking or exposure to secondhand tobacco smoke. Cities and communities can take an active role in curbing tobacco use and reducing lung cancer by adopting policies to regulate tobacco retail; reducing exposure to secondhand smoke in outdoor public spaces, such as parks, restaurants, or in multi-unit housing; and improving access to tobacco cessation programs and other preventive services.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

Deaths from lung cancer - Directly age-Standardised Rates (DSR) per 100,000 population Source: Office for National Statistics (ONS) Publisher: Information Centre (IC) - Clinical and Health Outcomes Knowledge Base Geographies: Local Authority District (LAD), Government Office Region (GOR), National, Primary Care Trust (PCT), Strategic Health Authority (SHA) Geographic coverage: England Time coverage: 2005-07, 2007 Type of data: Administrative data

Introduction: Approximately, 10–15% of lung cancer patients have never smoked. Previous epidemiological studies on non-tobacco associated lung cancer have been hampered by selected data from a small number of hospitals or limited numbers of patients. By use of data from large population-based registers with national coverage, this study aims to compare characteristics and survival of patients with non-small cell lung cancer (NSCLC) with different smoking histories. Methods: Swedish national population-based registers were used to retrieve data on patients diagnosed with primary NSCLC between 2002 and 2016. The Kaplan–Meier method and Cox proportional hazard models were used to estimate overall survival and lung cancer-specific survival by smoking history. Results: In total, 41,262 patients with NSCLC were included. Of those, 4624 (11%) had never smoked. Never-smokers were more often women and older compared to ever smokers (current and former). Adenocarcinoma was proportionally more common in never-smokers (77%) compared to current (52%) and former smokers (57%). Stage IV disease was more common in never-smokers (57%) than in current (48%) and former smokers (48%). Epidermal growth factor receptor mutation was observed more in never-smokers (37%) compared to current (5%) and former smokers (9%). Both lung cancer-specific and overall survival were higher for never-smokers compared to current smokers. Conclusions: The observed differences in characteristics between never-smokers and smokers, and the higher survival in never-smokers compared to smokers from this large population-based study provide further evidence that lung cancer in never-smokers is clinically different to tobacco-associated lung cancer. The findings from this study emphasise the need for an improved understanding of genetics, pathogenesis, mechanisms and progression of non-tobacco associated lung cancer that may help prevent lung cancer or identify individually targeted treatments.

Mortality from lung cancer (ICD-10 C33-C34 equivalent to ICD-9 162). To reduce deaths from lung cancer. Legacy unique identifier: P00516

Years of life lost due to mortality from lung cancer (ICD-10 C33-C34). Years of life lost (YLL) is a measure of premature mortality. Its primary purpose is to compare the relative importance of different causes of premature death within a particular population and it can therefore be used by health planners to define priorities for the prevention of such deaths. It can also be used to compare the premature mortality experience of different populations for a particular cause of death. The concept of years of life lost is to estimate the length of time a person would have lived had they not died prematurely. By inherently including the age at which the death occurs, rather than just the fact of its occurrence, the calculation is an attempt to better quantify the burden, or impact, on society from the specified cause of mortality. Legacy unique identifier: P00237

It is estimated that in 2025 there will be a total of 226,650 new cases of lung and bronchus cancer in the United States. The highest number of these cases are estimated to be in the state of Florida. This statistic presents the estimated number of new lung and bronchus cancer cases in the United States in 2025, by state.

Lung Cancer Diagnostics Market Outlook 2031:

The global lung cancer diagnostics market size was valued at USD 14.10 Billion in 2022 and is projected to reach USD 26.58 Billion by 2031, expanding at a CAGR of 7.3% during the forecast period 2023 - 2031. The growth of the market is attributed to the increasing prevalence of cancer as well as development of innovative diagnostic kits and treatment methods.

Lung cancer diagnosis refers to a screening procedure for detecting the cancer formation near and at the lungs, which is helpful for the treatment of the disease. Some of the key techniques for lung cancer treatment including imaging, cytology testing, biopsy, and tumor screening. Market expansion of lung cancer diagnostics is aided by rapid introduction of technological advancements in the field of tumor diagnosis.



The need for more effective diagnostic systems arises from the fact that only 15% of lung cancer cases are diagnosed, while the remaining undiscovered cases progress to more aggressive forms. This result to lowering the 5-year survival rate to only 4% in patients diagnosed with late-stage lung cancer.



The frequency of smoking has increased the chance of cancer dramatically in the developing world, which is predicted to have an impact on lung cancer incidence rates in the coming years. The need for early cancer screening and diagnosis is directly related to market growth as the prevalence of cancer rises.

Lung Cancer Diagnostics Market Trends, Drivers, Restraints, and Opportunities

• Increasing public awareness regarding the benefits regarding early diagnosis due to rising occurrence of cancer among a large number of population globally is expected to fuel the market growth in the coming years.


• Raising funding for R&D activities from private and government bodies to develop better tumour diagnostic tools is anticipated to propel the market growth during the forecast period.


• Introduction of inn

Years of Life Lost (YLL) as a result of death from lung cancer - Directly age-Standardised Rates (DSR) per 100,000 population Source: Office for National Statistics (ONS) Publisher: Information Centre (IC) - Clinical and Health Outcomes Knowledge Base Geographies: Local Authority District (LAD), Government Office Region (GOR), National, Primary Care Trust (PCT), Strategic Health Authority (SHA) Geographic coverage: England Time coverage: 2005-07, 2007 Type of data: Administrative data

Patient, tumor, and treatment characteristics in the Asian subgroups with lung or bronchial cancer.

The Global Lung Cancer Screening Software Market is estimated to reach USD 39.72 million by 2025, registering a healthy CAGR of 19.2% over the forecast period 2020-2026. Increasing prevalence of lung cancer, growing awareness about early stage diagnosis and growing number of screening programs across the globe are factors driving the market growth.
Lung cancer is widespread disease solely accounting for a high mortality rate alone in the U.S. Though the statistics may vary between countries, the cases of lung cancer can range from low to high. At present, aging in humans is found to be a major cause of lung cancer all across the world. Cigarette smoking is also found to be a major cause of concern in patients with lung cancers. Overall, a lung cancer screening enables detection of lung cancer before it proliferates in the body which later allows cancerous cells to attack healthy cells. Lung cancer screening thus enables the mode of treatment and diagnosis which can further help in controlling the cancer cells.

A screening software to determine the lung cancer in patients is a novel technique in medical science. It offers versatility in understanding the nature of patients dealing with lung cancers and also take them through simulation wherein the diagnosis tests are shared. Even though, the smoking and prevention programs have lessened the rates of lung cancer, a large population experiences lung disorders on a regular basis.
In the early stages of analysis, effective screening tests have proven unsuccessful and recent advances in multidetector computed tomography have enabled screening studies employing low-dose commuted topography (LDCT). CT screening for lung cancer is actively deployed in US and China on a significant scale. European countries are still awaiting trials before implementing CT scanning for lung cancers which will then conclude cancer screening to be a part of health insurance in EU. It is also obvious that a cancer screening program organized and structured will demand contemplation for costs and results generated by the scanning program.
Commercially, CT scan and solutions result in multiple benefits such as patent identification, data integration and analytics, patient communication and enrollment which have encouraged the adoption for scanning solutions in hospitals and radiological centers. Government initiatives are playing a crucial role in determining the market growth throughout.

Lung Cancer Screening Software Market Trends, Demands and Opportunities:

Lung Cancer Screening Software Market Segment Insights:

By Geography:

Competitive Landscape:

The global lung cancer treatment market is a significant and rapidly expanding sector, driven by rising incidence rates, an aging population, and advancements in therapeutic approaches. While precise figures for market size and CAGR are not provided, a reasonable estimate, considering the involvement of major pharmaceutical players like Roche, Novartis, and Pfizer, and the prevalence of lung cancer globally, would place the 2025 market size in the range of $100 billion to $150 billion USD. A CAGR of 5-7% for the forecast period (2025-2033) aligns with industry growth trends for targeted cancer therapies. Key drivers include the increasing adoption of targeted therapies, immunotherapy, and innovative treatment strategies like photodynamic and laser therapies, which offer improved efficacy and patient outcomes compared to traditional methods. The market segmentation reflects the diverse approaches to treatment, with surgery, chemotherapy, and radiotherapy remaining prevalent, while the growing segments of photodynamic and laser therapy indicate a shift towards less invasive and more targeted options. Regional variations exist, with North America and Europe currently holding substantial market shares, owing to higher healthcare expenditure and advanced infrastructure. However, Asia Pacific is expected to witness significant growth due to rising cancer incidence rates and increasing healthcare investments in the region. Restraints to market growth could include high treatment costs, the potential for adverse effects from certain therapies, and disparities in access to advanced treatment options across different geographical regions. Further growth in the lung cancer treatment market is anticipated to be fueled by ongoing research and development in novel therapies, including personalized medicine approaches tailored to individual patient genetic profiles. Increased awareness campaigns and early detection programs are also likely to play a significant role in shaping future market dynamics. The competitive landscape is characterized by the presence of numerous large pharmaceutical companies investing heavily in research and development, further contributing to innovation and expanding treatment options for lung cancer patients. The evolving regulatory environment and reimbursement policies in different countries will also influence market expansion and accessibility.

The global non-small cell lung cancer market garnered a market value of US$ 10 Billion in 2023 and is expected to accumulate a market value of US$ 20 Billion by registering a CAGR of 7.2% in the forecast period 2023 to 2033. This rapid expansion can be ascribed to an expanding patient population, the anticipated introduction of many medications, and increased expenditure by market players in NSCLC research and development.

Report Scope

From 2018 to 2022, the overall death rate for lung and bronchus cancer in the Kentucky was 61 per 100,000 for males and 43.2 per 100,000 for females. This statistic presents the death rates for lung and bronchus cancer in the United States from 2018 to 2022, by state and gender.