In 2023, Hawaii had the lowest death rate from cancer among all U.S. states, with around 119 deaths per 100,000 population. The states with the highest cancer death rates at that time were Kentucky, West Virginia, and Mississippi. This statistic shows cancer death rates in the United States in 2023, by state.

In 2022, Kentucky reported the highest cancer incidence rate in the United States, with around 512 new cases of cancer per 100,000 inhabitants. This statistic represents the U.S. states with the highest cancer incidence rates per 100,000 population in 2022.

In 2022, Utah had the lowest death rate from cancer among all U.S. states with around 116 deaths per 100,000 population. The states with the highest cancer death rates at that time were Mississippi, Kentucky and West Virginia. This statistic shows cancer death rates in the United States in 2022, by state.

In 2021, there were around *** new cases of breast cancer per 100,000 population in the state of Connecticut, making it the state with the highest breast cancer incidence rate that year. This statistic shows the incidence rate of breast cancer in the U.S. in 2021, by state.

In 2022, there were 157 cases of prostate cancer per 100,000 population in the state of Louisiana, making it the state with the highest prostate cancer incidence rate that year. This statistic shows the incidence rate of prostate cancer in the U.S. in 2022, by state.

In 2023, there were **** deaths from breast cancer per 100,000 population in the state of South Dakota, the lowest of any state that year. This statistic shows the death rate from breast cancer in the U.S. in 2023, by state.

What are Cancer Statistics in US States?

The circled group of good survivors has genetic indicators of poor survivors (i.e. low ESR1 levels, which is typically the prognostic indicator of poor outcomes in breast cancer) – understanding this group could be critical for helping improve mortality rates for this disease. Why this group survived was quickly analysed by using the Outcome Column (here Event Death - which is binary - 0,1) as a Data Lens (which we term Supervised vs Unsupervised analyses).

How to use this dataset

• A network was built using only gene expression with 272 breast cancer patients (as rows), and 1570 columns.

• Metadata includes patient info, treatment, and survival.

• Each node is a group of patients similar to each other. Flares (left) represent sub-populations that are distinct from the larger population. (One differentiating factor between the two flares is estrogen expression (low = top flare, high = bottom flare)).

• A bottom flare is a group of patients with 100% survival. The top flare shows a range of survival – very poor towards the tip (red), and very good near the base (circled).

Acknowledgments

When we use this dataset in our research, we credit the authors as :

• License : CC BY 4.0.

• This data set is taken from https://query.data.world/s/yi422lv7mkhnydnt4ixrfujmoaglpk .

The main idea for uploading this dataset is to practice data analysis with my students, as I am working in college and want my student to train our studying ideas in a big dataset, It may be not up to date and I mention the collecting years, but it is a good resource of data to practice

Cancer was responsible for around *** deaths per 100,000 population in the United States in 2023. The death rate for cancer has steadily decreased since the 1990’s, but cancer still remains the second leading cause of death in the United States. The deadliest type of cancer for both men and women is cancer of the lung and bronchus which will account for an estimated ****** deaths among men alone in 2025. Probability of surviving Survival rates for cancer vary significantly depending on the type of cancer. The cancers with the highest rates of survival include cancers of the thyroid, prostate, and testis, with five-year survival rates as high as ** percent for thyroid cancer. The cancers with the lowest five-year survival rates include cancers of the pancreas, liver, and esophagus. Risk factors It is difficult to determine why one person develops cancer while another does not, but certain risk factors have been shown to increase a person’s chance of developing cancer. For example, cigarette smoking has been proven to increase the risk of developing various cancers. In fact, around ** percent of cancers of the lung, bronchus and trachea among adults aged 30 years and older can be attributed to cigarette smoking. Other modifiable risk factors for cancer include being obese, drinking alcohol, and sun exposure.

Cervical cancer (CC) is a public health problem with a high disease burden and mortality in developing countries. In Brazil, areas with low human development index have the highest incidence rates of Brazil and upward temporal trend for this disease. The Northeast region has the second highest incidence of cervical cancer (20.47 new cases / 100,000 women). In this region, the mortality rates are similar to rates in countries that do not have a health system with a universal access screening program, as in Brazil. Thus, this study aimed to analyze the effects of age, period and birth cohorts on mortality from cervical cancer in the Northeast region of Brazil. Estimable functions predicted the effects of age, period and birth cohort. The average mortality rate was 10.35 deaths per 100,000 women during the period analyzed (1980–2014). The highest mortality rate per 100,000 women was observed in Maranhão (24.39 deaths), and the lowest mortality rate was observed in Bahia (11.24 deaths). According to the period effects, only the state of Rio Grande do Norte showed a reduction in mortality risk in the five years of the 2000s. There was a reduction in mortality risk for birth cohorts of women after the 1950s, except in Maranhão State, which showed an increasing trend in mortality risk for younger generations. We found that the high rates of cervical cancer mortality in the states of northeastern Brazil remain constant over time. Even after an increase in access to health services in the 2000s, associated with increased access to the cancer care network, which includes early detection (Pap Test), cervical cancer treatment and palliative care. However, it is important to note that the decreased risk of death and the mortality rates from CC among women born after the 1960s may be correlated with increased screening coverage, as well as increased access to health services for cancer treatment observed in younger women.

IntroductionLiver cancer is the fastest increasing cancer in the United States and is one of the leading causes of cancer-related death in New York City (NYC), with wide disparities among neighborhoods. The purpose of this cross-sectional study was to describe liver cancer incidence by neighborhood and examine its association with risk factors. This information can inform preventive and treatment interventions.Materials and methodsPublicly available data were collected on adult NYC residents (n = 6,407,022). Age-adjusted data on liver and intrahepatic bile duct cancer came from the New York State Cancer Registry (1) (2007–2011 average annual incidence); and the NYC Vital Statistics Bureau (2015, mortality). Data on liver cancer risk factors (2012–2015) were sourced from the New York City Department of Health and Mental Hygiene: (1) Community Health Survey, (2) A1C registry, and (3) NYC Health Department Hepatitis surveillance data. They included prevalence of obesity, diabetes, diabetic control, alcohol-related hospitalizations or emergency department visits, hepatitis B and C rates, hepatitis B vaccine coverage, and injecting drug use.ResultsLiver cancer incidence in NYC was strongly associated with neighborhood poverty after adjusting for race/ethnicity (β = 0.0217, p = 0.013); and with infection risk scores (β = 0.0389, 95% CI = 0.0088–0.069, p = 0.011), particularly in the poorest neighborhoods (β = 0.1207, 95% CI = 0.0147–0.2267, p = 0.026). Some neighborhoods with high hepatitis rates do not have a proportionate number of hepatitis prevention services.ConclusionHigh liver cancer incidence is strongly associated with infection risk factors in NYC. There are gaps in hepatitis prevention services like syringe exchange and vaccination that should be addressed. The role of alcohol and metabolic risk factors on liver cancer in NYC warrants further study.

In 2016 in India during the measured time period, Kerala had the highest crude incidence rate of cancer at ***** incidences for every 100,000 inhabitants. Mizoram in East India followed with almost *** incidences during the same time period.

MMWR Surveillance Summary 66 (No. SS-1):1-8 found that nonmetropolitan areas have significant numbers of potentially excess deaths from the five leading causes of death. These figures accompany this report by presenting information on potentially excess deaths in nonmetropolitan and metropolitan areas at the state level. They also add additional years of data and options for selecting different age ranges and benchmarks. Potentially excess deaths are defined in MMWR Surveillance Summary 66(No. SS-1):1-8 as deaths that exceed the numbers that would be expected if the death rates of states with the lowest rates (benchmarks) occurred across all states. They are calculated by subtracting expected deaths for specific benchmarks from observed deaths. Not all potentially excess deaths can be prevented; some areas might have characteristics that predispose them to higher rates of death. However, many potentially excess deaths might represent deaths that could be prevented through improved public health programs that support healthier behaviors and neighborhoods or better access to health care services. Mortality data for U.S. residents come from the National Vital Statistics System. Estimates based on fewer than 10 observed deaths are not shown and shaded yellow on the map. Underlying cause of death is based on the International Classification of Diseases, 10th Revision (ICD-10) Heart disease (I00-I09, I11, I13, and I20–I51) Cancer (C00–C97) Unintentional injury (V01–X59 and Y85–Y86) Chronic lower respiratory disease (J40–J47) Stroke (I60–I69) Locality (nonmetropolitan vs. metropolitan) is based on the Office of Management and Budget’s 2013 county-based classification scheme. Benchmarks are based on the three states with the lowest age and cause-specific mortality rates. Potentially excess deaths for each state are calculated by subtracting deaths at the benchmark rates (expected deaths) from observed deaths. Users can explore three benchmarks: “2010 Fixed” is a fixed benchmark based on the best performing States in 2010. “2005 Fixed” is a fixed benchmark based on the best performing States in 2005. “Floating” is based on the best performing States in each year so change from year to year. SOURCES CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES Moy E, Garcia MC, Bastian B, Rossen LM, Ingram DD, Faul M, Massetti GM, Thomas CC, Hong Y, Yoon PW, Iademarco MF. Leading Causes of Death in Nonmetropolitan and Metropolitan Areas – United States, 1999-2014. MMWR Surveillance Summary 2017; 66(No. SS-1):1-8. Garcia MC, Faul M, Massetti G, Thomas CC, Hong Y, Bauer UE, Iademarco MF. Reducing Potentially Excess Deaths from the Five Leading Causes of Death in the Rural United States. MMWR Surveillance Summary 2017; 66(No. SS-2):1–7.

One woman in nine can expect to develop breast cancer during her lifetime and one in 25 will die from the disease. Statistically low incidences of breast cancer are found in Newfoundland and Labrador, the territories, and northern areas of most provinces. Otherwise, each province has one or more pockets of significantly high breast cancer incidence. These are often located in more southerly areas, but they do not seem to be restricted to either urban or rural areas alone. Breast cancer rates are a health status indicator. They can be used to help assess health conditions. Health status refers to the state of health of a person or group, and measures causes of sickness and death. It can also include people’s assessment of their own health.

BackgroundForty percent of new cancer cases in the United States are attributed to modifiable risks, which can be influenced by the built environment. Recent cancer prevention guidelines include recommendations for making communities conducive to healthy living. Focused on the city of Philadelphia, the present study aims to 1) evaluate neighborhood-level adherence to cancer prevention guidelines by developing two novel indices and 2) identify factors driving low compliance in neighborhoods with high cancer mortality.MethodsPhiladelphia neighborhoods were compared to the city overall on ten cancer prevention recommendations. Comparison scores informed two indices: one focused on the American Cancer Society’s guidelines for Physical Activity, Nutrition, and Smoking, and the other focused on Healthy People 2030’s guidelines for Prevention Services. Indices were mapped by neighborhood and compared to cancer mortality. Where low adherence overlapped with high cancer mortality, the recommendations driving low compliance were identified.ResultsDistinct geospatial patterns were observed in adherence to guidelines, and while drivers of low adherence varied by neighborhood, general trends emerged in different areas of the city. Concerning Physical Activity, Nutrition, and Smoking Guideline adherence, some areas appeared to be more influenced by the built environment, while others were impacted by specific behavioral risk factors such as excessive alcohol consumption. Preventive Service recommendation adherence was driven in some parts by self-reported poor health and, in others, low cancer screening rates and a high physician-to-resident ratio. In neighborhoods where poor guideline adherence overlapped with high cancer mortality, the built environment emerged as a potentially important factor.DiscussionThis study considers the importance of the built environment in influencing adherence to cancer prevention guidelines. Policymakers and public health officials can use this information to prioritize interventions for neighborhoods with low guideline adherence and high cancer burden and tailor interventions to focus on indicators of low guideline adherence.

According to cognitive market research, the global lung cancer therapeutics market size was valued at USD xx billion in 2024 and is expected to reach USD xx billion at a CAGR of xx% during the forecast period.

The lungs are two spongy organs in the chest that control breathing. Lung cancer is the leading cause of cancer deaths worldwide. People who smoke have the greatest risk of lung cancer. The risk of lung cancer increases with the length of time and number of cigarettes smoked.
The market is anticipated to expand over the forecast period as a result of the high disease incidence rate and the rising number of drug approvals
The chemotherapy segment dominated the lung cancer therapeutics market revenue in 2024 and is projected to be the fastest-growing segment during the forecast period. Chemotherapy goes throughout the entire body for tumor cells, whereas radiation and surgery target a single region of the body.
Moreover, this market dominance is a result of consumers' growing propensity to buy pharmaceuticals from hospital pharmacies due to the availability of a large variety of medicines.
There are numerous products involved in the procedure of lung cancer therapeutics, which makes it costlier. Furthermore, the high maintenance cost of the instruments adds up to the total cost.

Market Dynamics of the Lung Cancer Therapeutics

Key Drivers of the Lung Cancer Therapeutics

The strong prevalence of lung cancer is notably driving market growth.

One of the most prevalent forms of cancer is lung cancer. Several reasons, including the aging population and lifestyle changes, have contributed to a notable increase in the number of new instances of cancer, particularly lung cancer, in recent years. In the United States, 6.2% of the population is at risk of developing lung cancer. Lung cancer still has a very high death rate, even with recent declines in the rate, which presents a market potential for suppliers. The market is anticipated to expand over the forecast period as a result of the high disease incidence rate and the rising number of drug approvals. • For instance, according to the 2022 report by the American Lung Association, while the disease remains the leading cause of cancer deaths among women and men, the survival rate over the past five years has increased from 21% nationally to 25% yet remains significantly lower among communities of color at 20%. Hence, the increasing prevalence of cancer and the need for effective treatment is likely to contribute to market growth. (Source:https://www.lung.org/research/state-of-lung-cancer/key-findings)

Rising pollution due to rapid industrialization increases the incidences of lung cancer

Air pollution (outdoor and indoor particulate matter and ozone) is closely linked to the rising prevalence of heart disease and strokes, lung cancer, lower respiratory infections, diabetes, and chronic obstructive pulmonary disease (COPD). The Global Burden of Disease Study Report (2019) ranks air pollution as the third leading cause of death worldwide. Globally, air pollution is responsible for 6.82 million deaths annually, of which 33% are caused by interior pollution and 66% by outdoor pollution. • For instance, According to the conference organized by the Associated Chambers of Commerce and Industry of India (ASSOCHAM), ‘Lung Cancer- Awareness, Prevention, Challenges & Treatment’, air pollution is the leading cause of the rise of lung cancer in the country. Around 63 out of the 100 most polluted places on earth belong to India. (Source:https://www.assocham.org/press-release-page.php?release-name=air-pollution-is-the-major-cause-of-lung-cancer-in-india-say-health-experts)

Restraints of the Lung Cancer Therapeutics

Regional disparities in treatment will hamper the market for lung cancer therapeutics

Lung cancer is the most prevalent cause of cancer-related deaths globally, and its impact is particularly felt in lower- and middle-income countries (LMICs), where access to early and effective diagnosis and treatment is often restricted. WHO data show that whereas 90% of cancer patients in high-income countries have access to therapy, only roughly 30% of cancer patients in low-income countries do. There are numerous products involved in the procedure of lung cancer therapeutics, which makes it costlier. Furthermore, the high maintenance cost of the i...

Cervical Cancer Risk Factors for Biopsy: This Dataset is Obtained from UCI Repository and kindly acknowledged!

This file contains a List of Risk Factors for Cervical Cancer leading to a Biopsy Examination!

About 11,000 new cases of invasive cervical cancer are diagnosed each year in the U.S. However, the number of new cervical cancer cases has been declining steadily over the past decades. Although it is the most preventable type of cancer, each year cervical cancer kills about 4,000 women in the U.S. and about 300,000 women worldwide. In the United States, cervical cancer mortality rates plunged by 74% from 1955 - 1992 thanks to increased screening and early detection with the Pap test. AGE Fifty percent of cervical cancer diagnoses occur in women ages 35 - 54, and about 20% occur in women over 65 years of age. The median age of diagnosis is 48 years. About 15% of women develop cervical cancer between the ages of 20 - 30. Cervical cancer is extremely rare in women younger than age 20. However, many young women become infected with multiple types of human papilloma virus, which then can increase their risk of getting cervical cancer in the future. Young women with early abnormal changes who do not have regular examinations are at high risk for localized cancer by the time they are age 40, and for invasive cancer by age 50. SOCIOECONOMIC AND ETHNIC FACTORS Although the rate of cervical cancer has declined among both Caucasian and African-American women over the past decades, it remains much more prevalent in African-Americans -- whose death rates are twice as high as Caucasian women. Hispanic American women have more than twice the risk of invasive cervical cancer as Caucasian women, also due to a lower rate of screening. These differences, however, are almost certainly due to social and economic differences. Numerous studies report that high poverty levels are linked with low screening rates. In addition, lack of health insurance, limited transportation, and language difficulties hinder a poor woman’s access to screening services. HIGH SEXUAL ACTIVITY Human papilloma virus (HPV) is the main risk factor for cervical cancer. In adults, the most important risk factor for HPV is sexual activity with an infected person. Women most at risk for cervical cancer are those with a history of multiple sexual partners, sexual intercourse at age 17 years or younger, or both. A woman who has never been sexually active has a very low risk for developing cervical cancer. Sexual activity with multiple partners increases the likelihood of many other sexually transmitted infections (chlamydia, gonorrhea, syphilis).Studies have found an association between chlamydia and cervical cancer risk, including the possibility that chlamydia may prolong HPV infection. FAMILY HISTORY Women have a higher risk of cervical cancer if they have a first-degree relative (mother, sister) who has had cervical cancer. USE OF ORAL CONTRACEPTIVES Studies have reported a strong association between cervical cancer and long-term use of oral contraception (OC). Women who take birth control pills for more than 5 - 10 years appear to have a much higher risk HPV infection (up to four times higher) than those who do not use OCs. (Women taking OCs for fewer than 5 years do not have a significantly higher risk.) The reasons for this risk from OC use are not entirely clear. Women who use OCs may be less likely to use a diaphragm, condoms, or other methods that offer some protection against sexual transmitted diseases, including HPV. Some research also suggests that the hormones in OCs might help the virus enter the genetic material of cervical cells. HAVING MANY CHILDREN Studies indicate that having many children increases the risk for developing cervical cancer, particularly in women infected with HPV. SMOKING Smoking is associated with a higher risk for precancerous changes (dysplasia) in the cervix and for progression to invasive cervical cancer, especially for women infected with HPV. IMMUNOSUPPRESSION Women with weak immune systems, (such as those with HIV / AIDS), are more susceptible to acquiring HPV. Immunocompromised patients are also at higher risk for having cervical precancer develop rapidly into invasive cancer. DIETHYLSTILBESTROL (DES) From 1938 - 1971, diethylstilbestrol (DES), an estrogen-related drug, was widely prescribed to pregnant women to help prevent miscarriages. The daughters of these women face a higher risk for cervical cancer. DES is no longer prsecribed.

This map uses age-standardized ratios to further aid in regional comparisons. A value of 1.0 would indicate that the region rate is identical to the overall Canadian rate; a value greater than 1.0 would indicate that the rate for that region is higher than the Canadian rate; and, in turn, a ratio value less than 1.0 would indicate that the rate for the specific region is lower than the Canadian rate. Statistically low incidences of breast cancer are found in Newfoundland and Labrador, the territories, and northern areas of most provinces. Otherwise, each province has one or more pockets of significantly high breast cancer incidence. Health status refers to the state of health of a person or group, and measures causes of sickness and death. It can also include people’s assessment of their own health.

One woman in nine can expect to develop breast cancer during her lifetime and one in 25 will die from the disease. Statistically low incidences of breast cancer are found in Newfoundland and Labrador, the territories, and northern areas of most provinces. Otherwise, each province has one or more pockets of significantly high breast cancer incidence. These are often located in more southerly areas, but they do not seem to be restricted to either urban or rural areas alone. Breast cancer rates are a health status indicator. They can be used to help assess health conditions. Health status refers to the state of health of a person or group, and measures causes of sickness and death. It can also include people’s assessment of their own health.

In the United States, medically underserved women carry a heavier burden of cancer incidence and mortality, yet are largely underrepresented in cancer prevention studies. My Body, My Test is a n observational cohort, multi-phase cervical cancer prevention study in North Carolina that recruited low-income women, aged 30–65 years and who had not undergone Pap testing in ≥ 4 years. Participants were offered home-based self-collection of cervico-vaginal samples for primary HPV testing. Here, we aimed to describe the recruitment strategies utilized by study staff, and the resulting recruitment and self-collection kit return rates for each specific recruitment strategy. Participants were recruited through different approaches: either direct (active, staff-effort intensive) or indirect (passive on the part of study staff). Of a total of 1,475 individuals screened for eligibility, 695 were eligible (47.1%) and 487 (70% of eligible) participants returned their self-collection kit. Small media recruitment resulted in the highest number of individuals found to be study eligible, with a relatively high self-collection kit return of 70%. In-clinic in-reach resulted in a lower number of study-eligible women, yet had the highest kit return rate (90%) among those sent kits. In contrast, 211 recruitment which resulted in the lowest kit return of 54%. Small media, word of mouth, and face-to-face outreach resulted in self-collection kit return rates ranging from 72 to 79%. The recruitment strategies undertaken by study staff support the continued study of reaching under-screened populations into cervical cancer prevention studies.

BackgroundLittle is known about the impact of comorbidity on cervical cancer survival in Australian women, including whether Indigenous women’s higher prevalence of comorbidity contributes to their lower survival compared to non-Indigenous women.MethodsData for cervical cancers diagnosed in 2003–2012 were extracted from six Australian state-based cancer registries and linked to hospital inpatient records to identify comorbidity diagnoses. Five-year cause-specific and all-cause survival probabilities were estimated using the Kaplan-Meier method. Flexible parametric models were used to estimate excess cause-specific mortality by Charlson comorbidity index score (0,1,2+), for Indigenous women compared to non-Indigenous women.ResultsOf 4,467 women, Indigenous women (4.4%) compared to non-Indigenous women had more comorbidity at diagnosis (score ≥1: 24.2% vs. 10.0%) and lower five-year cause-specific survival (60.2% vs. 76.6%). Comorbidity was associated with increased cervical cancer mortality for non-Indigenous women, but there was no evidence of such a relationship for Indigenous women. There was an 18% reduction in the Indigenous: non-Indigenous hazard ratio (excess mortality) when comorbidity was included in the model, yet this reduction was not statistically significant. The excess mortality for Indigenous women was only evident among those without comorbidity (Indigenous: non-Indigenous HR 2.5, 95%CI 1.9–3.4), indicating that factors other than those measured in this study are contributing to the differential. In a subgroup of New South Wales women, comorbidity was associated with advanced-stage cancer, which in turn was associated with elevated cervical cancer mortality.ConclusionsSurvival was lowest for women with comorbidity. However, there wasn’t a clear comorbidity-survival gradient for Indigenous women. Further investigation of potential drivers of the cervical cancer survival differentials is warranted.ImpactThe results highlight the need for cancer care guidelines and multidisciplinary care that can meet the needs of complex patients. Also, primary and acute care services may need to pay more attention to Indigenous Australian women who may not obviously need it (i.e. those without comorbidity).