Incidence, prevalence, and survival of breast cancer in the United Kingdom from 2000-2021: a population-based cohort study

Background Breast cancer is the most frequently diagnosed cancer in females globally. However, we know relatively little about trends in males. This study describes UK secular trends in breast cancer from 2000-2021 for both sexes. Methods Population-based cohort study using UK primary care Clinical Practice Research Datalink (CPRD) GOLD database and validated in Aurum. There were 5848436 eligible females and 5539681 males aged 18+ years, with ≥one year of prior data availability in the study period. We estimated breast cancer incidence rates (IR), period prevalence (PP) and survival at one-, five- and 10-years after diagnosis using the Kaplan-Meier method. Analyses were further stratified by age. Results IR of breast cancer from 2000-2021 was 194.4 per 100000 person-years for females and 1.16 for males. PP in 2021 was 2.1% for females and 0.009% for males. Both sexes have seen around a 2.5-fold increase in PP across time. Incidence increased with age for both sexes, peaking in females aged 60-69 years and males 90+. There was a drop in incidence for females aged 70-79 years. From 2003-2019, incidence increased >2-fold in younger females (aged 18-29: IR 2.12 in 2003 vs. 4.58 in 2018); decreased in females aged 50-69 years; and further declined from 2015 onwards in females aged 70-89 years. Survival for females after one-, five-, and ten-years after diagnosis was 95.1%, 80.2%, and 68.4%, and for males 92.9%, 69.0%, and 51.3%. Survival at one-year increased by 2.08% points, and survival at five years increased by 5.39% from 2000-2004 to 2015-2019 for females, particularly those aged 50-70 years. For males, there were no clear time-trends for short-term and long-term survival. Conclusion Changes in incidence of breast cancer in females largely reflect the success of screening programmes, as rates rise and fall in synchronicity with ages of eligibility for such programmes. Overall survival from breast cancer for females has improved from 2000 to 2021, again reflecting the success of screening programmes, early diagnosis, and improvements in treatments. Male breast cancer patients have worse survival outcomes compared to females, highlighting the need to develop male-specific diagnosis and treatment strategies to improve long-term survival in line with females

Incidence, Prevalence, and Survival of Prostate Cancer in the UK

Importance: Incidence, prevalence, and survival are pertinent measures to inform the management and provision of prostate cancer care. Objective: To calculate the incidence, prevalence, and survival rates for prostate cancer in the UK from 2000 to 2021. Design, Setting, and Participants: This population-based cohort study uses routinely collected primary care data from the UK. Male patients aged 18 years or older with at least 1 year of history registered in Clinical Practice Research Datalink (CPRD) GOLD or Aurum were included. Data were analyzed from January 2023 to March 2024. Main Outcomes and Measures: Prostate cancer incidence rates (IR), period prevalence (PP), and 1-, 5-, and 10-year survival after diagnosis between 2000 and 2021, stratified by age and calendar years. Results: This study included 64 925 and 133 200 patients with prostate cancer in CPRD GOLD and Aurum, respectively, with a median age of 72 (65-78) years. The overall IR of prostate cancer was 151.7 (95% CI, 150.6 to 152.9) per 100 000 person-years in GOLD to 153.1 (95% CI, 152.3 to 153.9) per 100 000 person-years for Aurum and increased with age. The incidence of prostate cancer increased from 109 per 100 000 person-years in 2000 to 159 per 100 000 person-years in 2021. Peaks of incidence occurred in 2004 and 2018, before a decline in 2020. PP increased 3.5 times over the study period for both databases, from 0.4% in 2000 to 1.4% in 2021. IR and PP were highest in those aged 80 to 89 years. Median (95% CI) survival was similar in both databases (GOLD: 10.9 [95% CI, 10.7-11.1] years and Aurum: 11.1 [95% CI, 11.0-11.2] years). Survival at 1, 5, and 10 years after diagnosis were 93.4% (95% CI, 93.2%-93.6%), 71.8% (95% CI, 71.4%-72.2%), 53.2% (95% CI, 52.6%-53.7%) in GOLD and 93.9% (95% CI, 93.7%-94.0%), 72.7% (95% CI, 72.5%-73.0%), 53.7% (95% CI, 53.3%-54.1%) in AURUM, respectively. Survival increased over time: 1-year survival was 94.8% (95% CI, 94.5%-95.2%) in those diagnosed between 2015 to 2019 compared with 90.8% (95% CI, 90.2%-91.3%) from 2000 to 2004; 5-year survival improved from 65.3% (95% CI, 64.4%-66.3%) from 2000 to 2004 to 75.3% (95% CI, 74.4%-76.3%) in 2015 to 2019. Conclusions and Relevance:In this population-based cohort study, incidence and prevalence increased with older age, with high survival rates reflecting a high burden of disease, particularly in the management of cancer survivorship in an aging population. Health care systems should consider this when managing the increasing numbers of people with prevalent prostate cancer.</p

Trends in incidence, prevalence, and survival of breast cancer in the United Kingdom from 2000 to 2021

Breast cancer is the most frequently diagnosed cancer in females globally. However, we know relatively little about trends in males. This study describes United Kingdom (UK) secular trends in breast cancer from 2000 to 2021 for both sexes. We describe a population-based cohort study using UK primary care Clinical Practice Research Datalink (CPRD) GOLD and Aurum databases. There were 5,848,436 eligible females and 5,539,681 males aged 18+ years, with ≥ one year of prior data availability in the study period. We estimated crude breast cancer incidence rates (IR), prevalence and survival probability at one-, five- and 10-years after diagnosis using the Kaplan–Meier method. Analyses were further stratified by age. Crude IR of breast cancer from 2000 to 2021 was 194.4 per 100,000 person-years for females and 1.16 for males. Crude prevalence in 2021 was 2.1% for females and 0.009% for males. Both sexes have seen around a 2.5-fold increase in prevalence across time. Incidence increased with age for both sexes, peaking in females aged 60–69 years and males 90+ . There was a drop in incidence for females aged 70–79 years. From 2003–2019, incidence increased > twofold in younger females (aged 18–29: IR 2.12 in 2003 vs. 4.58 in 2018); decreased in females aged 50–69 years; and further declined from 2015 onwards in females aged 70–89 years. Survival probability for females after one-, five-, and ten-years after diagnosis was 95.1%, 80.2%, and 68.4%, and for males 92.9%, 69.0%, and 51.3%. Survival probability at one-year increased by 2.08% points, and survival at five years increased by 5.39% from 2000–2004 to 2015–2019 for females, particularly those aged 50–70 years. For males, there were no clear time-trends for short-term and long-term survival probability. Changes in incidence of breast cancer in females largely reflect the success of screening programmes, as rates rise and fall in synchronicity with ages of eligibility for such programmes. Overall survival from breast cancer for females has improved from 2000 to 2021, again reflecting the success of screening programmes, early diagnosis, and improvements in treatments. Male breast cancer patients have worse survival outcomes compared to females, highlighting the need to develop male-specific diagnosis and treatment strategies to improve long-term survival in line with females

Diabetes Mellitus and Its Correlates in an Iranian Adult Population

The rising epidemic of diabetes imposes a substantial economic burden on the Middle East. Using baseline data from a population based cohort study, we aimed to identify the correlates of diabetes mellitus (DM) in a mainly rural population from Iran. Between 2004 and 2007, 50044 adults between 30 and 87 years old from Golestan Province located in Northeast Iran were enrolled in the Golestan Cohort Study. Demographic and health-related information was collected using questionnaires. Individuals' body sizes at ages 15 and 30 were assessed by validated pictograms ranging from 1 (very lean) to 7 in men and 9 in women. DM diagnosis was based on the self-report of a physician's diagnosis. The accuracy of self-reported DM was evaluated in a subcohort of 3811 individuals using fasting plasma glucose level and medical records. Poisson regression with robust variance estimator was used to estimate prevalence ratios (PR's). The prevalence of self-reported DM standardized to the national and world population was 5.7% and 6.2%, respectively. Self-reported DM had 61.5% sensitivity and 97.6% specificity. Socioeconomic status was inversely associated with DM prevalence. Green tea and opium consumption increased the prevalence of DM. Obesity at all ages and extreme leanness in childhood increased diabetes prevalence. Being obese throughout life doubled DM prevalence in women (PR: 2.1; 95% CI: 1.8, 2.4). These findings emphasize the importance of improving DM awareness, improving general living conditions, and early lifestyle modifications in diabetes prevention

Identification of functional genetic variation in exome sequence analysis

Recent technological advances have allowed us to study individual genomes at a base-pair resolution and have demonstrated that the average exome harbors more than 15,000 genetic variants. However, our ability to understand the biological significance of the identified variants and to connect these observed variants with phenotypes is limited. The first step in this process is to identify genetic variation that is likely to result in changes to protein structure and function, because detailed studies, either population based or functional, for each of the identified variants are not practicable. Therefore algorithms that yield valid predictions of a variant’s functional significance are needed. Over the past decade, several programs have been developed to predict the probability that an observed sequence variant will have a deleterious effect on protein function. These algorithms range from empirical programs that classify using known biochemical properties to statistical algorithms trained using a variety of data sources, including sequence conservation data, biochemical properties, and functional data. Using data from the pilot3 study of the 1000 Genomes Project available through Genetic Analysis Workshop 17, we compared the results of four programs (SIFT, PolyPhen, MAPP, and VarioWatch) used to predict the functional relevance of variants in 101 genes. Analysis was conducted without knowledge of the simulation model. Agreement between programs was modest ranging from 59.4% to 71.4% and only 3.5% of variants were classified as deleterious and 10.9% as tolerated across all four programs

Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer:A Systematic Review

Background and objective: The treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients’ response to treatment. Methods: We critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria. Key findings and limitations: The search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance. Conclusions and clinical implications: Most of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa. Patient summary: In this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals.</p

Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer:A Systematic Review

Background and objective: The treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients’ response to treatment. Methods: We critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria. Key findings and limitations: The search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance. Conclusions and clinical implications: Most of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa. Patient summary: In this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals.</p

Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer : A Systematic Review

Peer reviewe

Research protocol to identify progression and death amongst patients with metastatic hormone-sensitive prostate cancer treated with available treatments: PIONEER IMI's "big data for better outcomes" program

Androgen deprivation therapy-based with or without first-generation anti-androgens, was the standard of care for patients with metastatic hormone-sensitive prostate cancer (mHSPC) for decades. However, the development of docetaxel chemotherapy and new androgen receptor-targeted agents, abiraterone acetate and prednisolone, apalutamide , enzalutamide and darolutamide (in combination with docetaxel chemotherapy) has proven that combination of treatments is more effective. Recently, intensification therapy, so-called "triplets", have emerged in the armamentarium of mHSPC treatment. Metastatic disease is a clinical state that remains poorly understood. The optimal diagnostic and management of patients with mHSPC are changing thanks to the development of new imaging techniques and therapies. The primary objective of this study is to develop and validate a predictive model for the occurrence of symptomatic progression, initiation of new treatments and death amongst patients with mHSPC treated with one of the approved treatment plans, on characteristics present at admission

Similar Risk of Kidney Failure among Patients with Blinding Diseases Who Receive Ranibizumab, Aflibercept, and Bevacizumab:An Observational Health Data Sciences and Informatics Network Study

Purpose: To characterize the incidence of kidney failure associated with intravitreal anti-VEGF exposure; and compare the risk of kidney failure in patients treated with ranibizumab, aflibercept, or bevacizumab. Design: Retrospective cohort study across 12 databases in the Observational Health Data Sciences and Informatics (OHDSI) network. Subjects: Subjects aged ≥ 18 years with ≥ 3 monthly intravitreal anti-VEGF medications for a blinding disease (diabetic retinopathy, diabetic macular edema, exudative age-related macular degeneration, or retinal vein occlusion). Methods: The standardized incidence proportions and rates of kidney failure while on treatment with anti-VEGF were calculated. For each comparison (e.g., aflibercept versus ranibizumab), patients from each group were matched 1:1 using propensity scores. Cox proportional hazards models were used to estimate the risk of kidney failure while on treatment. A random effects meta-analysis was performed to combine each database's hazard ratio (HR) estimate into a single network-wide estimate. Main Outcome Measures: Incidence of kidney failure while on anti-VEGF treatment, and time from cohort entry to kidney failure. Results: Of the 6.1 million patients with blinding diseases, 37 189 who received ranibizumab, 39 447 aflibercept, and 163 611 bevacizumab were included; the total treatment exposure time was 161 724 person-years. The average standardized incidence proportion of kidney failure was 678 per 100 000 persons (range, 0–2389), and incidence rate 742 per 100 000 person-years (range, 0–2661). The meta-analysis HR of kidney failure comparing aflibercept with ranibizumab was 1.01 (95% confidence interval [CI], 0.70–1.47; P = 0.45), ranibizumab with bevacizumab 0.95 (95% CI, 0.68–1.32; P = 0.62), and aflibercept with bevacizumab 0.95 (95% CI, 0.65–1.39; P = 0.60). Conclusions: There was no substantially different relative risk of kidney failure between those who received ranibizumab, bevacizumab, or aflibercept. Practicing ophthalmologists and nephrologists should be aware of the risk of kidney failure among patients receiving intravitreal anti-VEGF medications and that there is little empirical evidence to preferentially choose among the specific intravitreal anti-VEGF agents. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.</p