Rate: Number of deaths due to prostate cancer per 100,000 male population.

Definition: Number of deaths per 100,000 males with malignant neoplasm (cancer) of the prostate as the underlying cause of death (ICD-10 code: C61).

Data Sources:

(1) Centers for Disease Control and Prevention, National Center for Health Statistics. Compressed Mortality File. CDC WONDER On-line Database accessed at http://wonder.cdc.gov/cmf-icd10.html

(2) Death Certificate Database, Office of Vital Statistics and Registry, New Jersey Department of Health

(3) Population Estimates, State Data Center, New Jersey Department of Labor and Workforce Development

This dataset contains Cancer Incidence data for Prostate Cancer(All Stages^) including: Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2016 to 2020.Data are for males segmented age (All Ages, Ages Under 50, Ages 50 & Over, Ages Under 65, and Ages 65 & Over), with field names and aliases describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.govData NotationsState Cancer Registries may provide more current or more local data.TrendRising when 95% confidence interval of average annual percent change is above 0.Stable when 95% confidence interval of average annual percent change includes 0.Falling when 95% confidence interval of average annual percent change is below 0.† Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84, 85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used for SEER and NPCR incidence rates.‡ Incidence Trend data come from different sources. Due to different years of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. Please refer to the source for each area for additional information.Rates and trends are computed using different standards for malignancy. For more information see malignant.^ All Stages refers to any stage in the Surveillance, Epidemiology, and End Results (SEER) summary stage.Data Source Field Key(1) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(5) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(6) Source: National Program of Cancer Registries SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention (based on the 2022 submission).(7) Source: SEER November 2022 submission.(8) Source: Incidence data provided by the SEER Program. AAPCs are calculated by the Joinpoint Regression Program and are based on APCs. Data are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84,85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used with SEER November 2022 data.Some data are not available, see Data Not Available for combinations of geography, cancer site, age, and race/ethnicity.Data for the United States does not include data from Nevada.Data for the United States does not include Puerto Rico.

RATIONALE: Zoledronate may prevent or decrease skeletal (bone)-related events (such as pain or fractures) caused by bone metastases and androgen deprivation therapy. It is not yet known whether treatment with zoledronate is effective in preventing bone-related events in patients who have prostate cancer and bone metastases. PURPOSE: This randomized phase III trial is studying how well zoledronate works in preventing bone-related events in patients who are receiving androgen deprivation therapy for prostate cancer and bone metastases.

Number and rate of new cancer cases diagnosed annually from 1992 to the most recent diagnosis year available. Included are all invasive cancers and in situ bladder cancer with cases defined using the Surveillance, Epidemiology and End Results (SEER) Groups for Primary Site based on the World Health Organization International Classification of Diseases for Oncology, Third Edition (ICD-O-3). Random rounding of case counts to the nearest multiple of 5 is used to prevent inappropriate disclosure of health-related information.

Eight-year age standardized incidence rates and crude incidence rates of prostate cancer (per 100 000 population) (2011–2018).

This publication reports on newly diagnosed cancers registered in England during 2022. It includes this summary report showing key findings, spreadsheet tables with more detailed estimates, and a methodology document. Cancer registration estimates are provided for: • Incidence of cancer using groupings that incorporate both the location and type of cancer by combinations of gender, age, deprivation, and stage at diagnosis (where appropriate) for England, former Government office regions, Cancer alliances and Integrated care boards • Incidence and mortality (using ICD-10 3-digit codes) by gender and age group for England, former Government office regions, Cancer alliances and Integrated care boards This publication will report on 2022 cancer registrations only, trends will not be reported as the required re-stated populations for 2012 to 2020 are not expected to be published by the Office of National Statistics (ONS) until Winter 2024.

Cancer diagnoses and age-standardised incidence rates for all types of cancer by age and sex including breast, prostate, lung and colorectal cancer.

🇬🇧 영국 English This summary brings together information on prostate cancer incidence, mortality and survival. Source agency: Office for National Statistics Designation: National Statistics Language: English Alternative title: Prostate cancer: the most common cancer in men in England

The purpose of this study is to compare the treatment effect of denosumab with placebo on prolonging bone metastasis-free survival in men with hormone refractory (androgen independent) prostate cancer who have no bone metastasis at baseline.

Dutasteride is used in the treatment of benign prostate enlargement (BPH).It inhibits conversion of testosterone (T) into the more potent dihydrotestosterone (DHT) to stop prostate (and possibly prostate cancer) growth. DHT regulates the expression of certain genes in the prostate. The pharmacodynamics of DHT reduction in the prostate were never investigated until now, as every measurement would require prostate tissue retrieval, which is medically and ethically unacceptable. A recently developed test is able to quantitatively measure gene expression in prostate-borne cells, in urine sediments after prostate massage. By measuring this gene expression in patients using dutasteride, it has become possible to assess the pharmacodynamics of gene expression reduction, which is representative for the pharmacodynamics of DHT reduction. Repeated prostate tissue sampling has therefore become unnecessary. This newly gained knowledge will lead to a better understanding of the action of dutasteride and will possibly help improve treatment of symptomatic BPH (Benign Prostatic Hyperplasia) and PrCa (Prostate Cancer)in the future.

This dataset comprises digitized benign prostate hematoxilyn and eosin (H&E) biopsies from men with raised prostate-specific antigen (PSA) values. The biopsies were systematically taken from different locations in the prostate and were not guided by magnetic resonance imaging (MRI). The dataset includes paired samples from patients with comparable age and PSA levels, all initially diagnosed as benign but with different outcomes upon subsequent follow-ups and re-biopsies. While some patients remained cancer-free during eight years of follow-up, others were diagnosed with prostate cancer within the subsequent 30 months of follow-up. The final processed dataset includes 213 patients from northern Sweden, resulting in a total of 587 H&E prostate needle biopsies. Among these, 125 control patients with 333 biopsies exhibited no cancer development in eight years following the initial diagnosis. Conversely, 88 case patients with 254 biopsies were diagnosed with prostate cancer of various ISUP grades within the 30 months following the initial diagnosis. Each case patient is accompanied by one to three control patients, paired for similar age, PSA value and year of diagnosis. Patients were anonymized by assigning random case IDs and MRXS image files were anonymized by using the module in https://github.com/bgilbert/anonymize-slide.

This dataset presents the footprint of male cancer mortality statistics in Australia for all cancers combined and the 11 top cancer groupings (bladder, colorectal, head and neck, kidney, leukaemia, lung, lymphoma, melanoma of the skin, pancreas, prostate and stomach) and their respective ICD-10 codes. The data spans the years 2009-2013 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS). Mortality …Show full descriptionThis dataset presents the footprint of male cancer mortality statistics in Australia for all cancers combined and the 11 top cancer groupings (bladder, colorectal, head and neck, kidney, leukaemia, lung, lymphoma, melanoma of the skin, pancreas, prostate and stomach) and their respective ICD-10 codes. The data spans the years 2009-2013 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS). Mortality data refer to the number of deaths due to cancer in a given time period. Cancer deaths data are sourced from the Australian Institute of Health and Welfare (AIHW) 2013 National Mortality Database (NMD). For further information about this dataset, please visit: Australian Institute of Health and Welfare - Cancer Incidence and Mortality Across Regions (CIMAR) books. Australian Institute of Health and Welfare - 2013 National Mortality Database. Please note: AURIN has spatially enabled the original data using the Department of Health - PHN Areas. Due to changes in geographic classifications over time, long-term trends are not available. Values assigned to "n.p." in the original data have been removed from the data. The Australian and jurisdictional totals include people who could not be assigned a PHN. The number of people who could not be assigned a PHN is less than 1% of the total. The Australian total also includes residents of Other Territories (Cocos (Keeling) Islands, Christmas Island and Jervis Bay Territory). Cause of Death Unit Record File data are provided to the AIHW by the Registries of Births, Deaths and Marriages and the National Coronial Information System (managed by the Victorian Department of Justice) and include cause of death coded by the Australian Bureau of Statistics (ABS). The data are maintained by the AIHW in the NMD. Year refers to year of occurrence of death for years up to and including 2012, and year of registration of death for 2013. Deaths registered in 2011 and earlier are based on the final version of cause of death data; deaths registered in 2012 and 2013 are based on revised and preliminary versions, respectively and are subject to further revision by the ABS. Cause of death information are based on underlying cause of death and are classified according to the International Classification of Diseases and Related Health Problems (ICD). Deaths registered in 1997 onwards are classified according to the 10th revision (ICD-10). Colorectal deaths presented are underestimates. For further information, refer to "Complexities in the measurement of bowel cancer in Australia" in Causes of Death, Australia (ABS cat. no. 3303.0). Copyright attribution: Government of the Commonwealth of Australia - Australian Institute of Health and Welfare, (2016): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 3.0 Australia (CC BY 3.0 AU)

Prostate cancer is the second most common cancer in men and affects 1 in 9 men in the United States. Early screening for prostate cancer often involves monitoring levels of prostate-specific antigen (PSA) and performing digital rectal exams. However, a prostate biopsy is always required for definitive cancer diagnosis. The Early Detection Research Network (EDRN) is a consortium within the National Cancer Institute aimed at improving screening approaches and early detection of cancers. As part of this effort, the Weill Cornell EDRN Prostate Cancer has collected and biobanked specimens from men undergoing a prostate biopsy between 2008 and 2017. In this report, we describe blood metabolomics measurements for a subset of this population. The dataset includes detailed clinical and prospective records for 580 patients who underwent prostate biopsy, 287 of which were subsequentially diagnosed with prostate cancer, combined with profiling of 1,482 metabolites from plasma samples collected at the time of biopsy. We expect this dataset to provide a valuable resource for scientists investigating prostate cancer metabolism.

Number and rate of new cancer cases by stage at diagnosis from 2011 to the most recent diagnosis year available. Included are colorectal, lung, breast, cervical and prostate cancer with cases defined using the Surveillance, Epidemiology and End Results (SEER) Groups for Primary Site based on the World Health Organization International Classification of Diseases for Oncology, Third Edition (ICD-O-3). Random rounding of case counts to the nearest multiple of 5 is used to prevent inappropriate disclosure of health-related information.

This record contains raw data related to article 68Ga-PSMA Positron Emission Tomography/Computerized Tomography for Primary Diagnosis of Prostate Cancer in Men with Contraindications to or Negative Multiparametric Magnetic Resonance Imaging: A Prospective Observational Study

PURPOSE:

68Ga labeled prostate specific membrane antigen positron emission tomography/computerized tomography may represent the most promising imaging modality to identify and risk stratify prostate cancer in patients with contraindications to or negative multiparametric magnetic resonance imaging.

MATERIALS AND METHODS:

In this prospective observational study we analyzed 68Ga labeled prostate specific membrane antigen positron emission tomography/computerized tomography in a select group of patients with persistently elevated prostate specific antigen and/or Prostate Health Index suspicious for prostate cancer, negative digital rectal examination and at least 1 negative biopsy. The cohort comprised men with equivocal multiparametric magnetic resonance imaging (Prostate Imaging-Reporting and Data System, version 2 score of 2 or less), or an absolute or relative contraindication to multiparametric magnetic resonance imaging. Sensitivity, specificity and CIs were calculated compared to histopathology findings. ROC analysis was applied to determine the optimal cutoff values of 68Ga labeled prostate specific membrane antigen uptake to identify clinically significant prostate cancer (Gleason score 7 or greater).

RESULTS:

A total of 45 patients with a median age of 64 years were referred for 68Ga labeled prostate specific membrane antigen positron emission tomography/computerized tomography between January and August 2017. The 25 patients (55.5%) considered to have positive positron emission tomography results underwent software assisted fusion biopsy. We determined the uptake values of regions of interest, including a median maximum standardized uptake value of 5.34 (range 2.25 to 30.41) and a maximum-to-background standardized uptake value ratio of 1.99 (range 1.06 to 14.42). Mean and median uptake values on 68Ga labeled prostate specific membrane antigen positron emission tomography/computerized tomography (ie the maximum standardized uptake value or the maximum-to-background standardized uptake value ratio) were significantly higher for Gleason score 7 lesions than for Gleason score 6 or benign lesions (p <0.001). On ROC analysis a maximum standardized uptake value of 5.4 and a maximum-to-background standardized uptake value ratio of 2 discriminated clinically relevant prostate cancer with 100% overall sensitivity in each case, and 76% and 88% specificity, respectively.

CONCLUSIONS:

Our findings support the use of 68Ga labeled prostate specific membrane antigen positron emission tomography/computerized tomography for primary detection of prostate cancer in a specific subset of men.

Non-steroidal anti-inflammatory drugs (NSAIDs), especially aspirin, have been associated with lowered cancer incidence and mortality. We examined overall cancer mortality and mortality from specific cancer sites among the 80,144 men in the Finnish Prostate Cancer Screening Trial. Information on prescription drug use was acquired from the national drug reimbursement database. Over-the-counter use information was gathered by a questionnaire. Hazard ratios (HR) and 95% confidence intervals (CI) by prescription and over-the-counter NSAID use for overall and specific cancer deaths were calculated using Cox regression. During the median follow-up time of 15 years, 7,008 men died from cancer. Men with prescription NSAID use had elevated cancer mortality (HR 2.02 95% CI 1.91–2.15) compared to non-users. The mortality risk was increased for lung, colorectal and pancreas cancer mortality (HR 2.68, 95%CI 2.40–2.99, HR 1.91, 95% CI 1.57–2.32 and HR 1.93, 95% CI 1.58–2.37, respectively). The increased risk remained in competing risks regression (HR 1.11, 95% CI 1.05–1.18). When the usage during the last three years of follow-up was excluded, the effect was reversed (HR 0.69, 95% CI 0.65–0.73). Cancer mortality was not decreased for prescription or over-the-counter aspirin use. However, in the competing risk regression analysis combined prescription and over-the-counter aspirin use was associated with decreased overall cancer mortality (HR 0.76, 95% CI 0.70–0.82). Cancer mortality was increased for NSAID users. However, the risk disappeared when the last 3 years were excluded.

This table contains 600 series, with data for years 1997 - 1997 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (15 items: Canada; Prince Edward Island; Newfoundland and Labrador; Nova Scotia ...), Sex (3 items: Both sexes; Females; Males ...), Selected sites of cancer (ICD-9) (4 items: Colorectal cancer; Prostate cancer; Lung cancer; Female breast cancer ...), Characteristics (5 items: Relative survival rate for cancer; High 95% confidence interval; relative survival rate for cancer; Number of cases; Low 95% confidence interval; relative survival rate for cancer ...).

This dataset presents the footprint of cancer mortality data in Australia for all cancers combined, and six selected cancers (female breast cancer, colorectal cancer, cervical cancer, lung cancer, melanoma of the skin, and prostate cancer) with their respective ICD-10 codes. The data spans the years 2011 to 2015 and is aggregated to 2015 PHN boundaries based on the 2011 Australian Statistical Geography Standard (ASGS). The source of the mortality data is the Australia Cancer Database, the National Mortality Database and the National Death Index. Cause of Death Unit Record File data are provided to the AIHW by the Registries of Births, Deaths and Marriages and the National Coronial Information System (managed by the Victorian Department of Justice) and include cause of death coded by the Australian Bureau of Statistics (ABS). The data are maintained by AIHW in the National Mortality Database. For more information, please visit the data source: AIHW - Cancer incidence and mortality in Australia by small geographic areas. Please note: AURIN has spatially enabled the original data using the Department of Health - PHN Areas. Colorectal deaths presented are underestimates. For further information on complexities in the measurement of bowel cancer in Australia, refer to the Australian Bureau of Statistics.

Population based cancer incidence rates were abstracted from National Cancer Institute, State Cancer Profiles for all available counties in the United States for which data were available. This is a national county-level database of cancer data that are collected by state public health surveillance systems. All-site cancer is defined as any type of cancer that is captured in the state registry data, though non-melanoma skin cancer is not included. All-site age-adjusted cancer incidence rates were abstracted separately for males and females. County-level annual age-adjusted all-site cancer incidence rates for years 2006–2010 were available for 2687 of 3142 (85.5%) counties in the U.S. Counties for which there are fewer than 16 reported cases in a specific area-sex-race category are suppressed to ensure confidentiality and stability of rate estimates; this accounted for 14 counties in our study. Two states, Kansas and Virginia, do not provide data because of state legislation and regulations which prohibit the release of county level data to outside entities. Data from Michigan does not include cases diagnosed in other states because data exchange agreements prohibit the release of data to third parties. Finally, state data is not available for three states, Minnesota, Ohio, and Washington. The age-adjusted average annual incidence rate for all counties was 453.7 per 100,000 persons. We selected 2006–2010 as it is subsequent in time to the EQI exposure data which was constructed to represent the years 2000–2005. We also gathered data for the three leading causes of cancer for males (lung, prostate, and colorectal) and females (lung, breast, and colorectal). The EQI was used as an exposure metric as an indicator of cumulative environmental exposures at the county-level representing the period 2000 to 2005. A complete description of the datasets used in the EQI are provided in Lobdell et al. and methods used for index construction are described by Messer et al. The EQI was developed for the period 2000– 2005 because it was the time period for which the most recent data were available when index construction was initiated. The EQI includes variables representing each of the environmental domains. The air domain includes 87 variables representing criteria and hazardous air pollutants. The water domain includes 80 variables representing overall water quality, general water contamination, recreational water quality, drinking water quality, atmospheric deposition, drought, and chemical contamination. The land domain includes 26 variables representing agriculture, pesticides, contaminants, facilities, and radon. The built domain includes 14 variables representing roads, highway/road safety, public transit behavior, business environment, and subsidized housing environment. The sociodemographic environment includes 12 variables representing socioeconomics and crime. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. This dataset is associated with the following publication: Jagai, J., L. Messer, K. Rappazzo , C. Gray, S. Grabich , and D. Lobdell. County-level environmental quality and associations with cancer incidence#. Cancer. John Wiley & Sons Incorporated, New York, NY, USA, 123(15): 2901-2908, (2017).

BackgroundMany individuals undergoing cancer treatment experience substantial financial hardship, often referred to as financial toxicity (FT). Those undergoing prostate cancer treatment may experience FT and its impact can exacerbate disparate health outcomes. Localized prostate cancer treatment options include: radiation, surgery, and/or active surveillance. Quality of life tradeoffs and costs differ between treatment options. In this project, our aim was to quantify direct healthcare costs to support patients and clinicians as they discuss prostate cancer treatment options. We provide the transparent steps to estimate healthcare costs associated with treatment for localized prostate cancer among the privately insured population using a large claims dataset.MethodsTo quantify the costs associated with their prostate cancer treatment, we used data from the Truven Health Analytics MarketScan Commercial Claims and Encounters, including MarketScan Medicaid, and peer reviewed literature. Strategies to estimate costs included: (1) identifying the problem, (2) engaging a multidisciplinary team, (3) reviewing the literature and identifying the database, (4) identifying outcomes, (5) defining the cohort, and (6) designing the analytic plan. The costs consist of patient, clinician, and system/facility costs, at 1-year, 3-years, and 5-years following diagnosis.ResultsWe outline our specific strategies to estimate costs, including: defining complex research questions, defining the study population, defining initial prostate cancer treatment, linking facility and provider level related costs, and developing a shared understanding of definitions on our research team.Discussion and next stepsAnalyses are underway. We plan to include these costs in a prostate cancer patient decision aid alongside other clinical tradeoffs.