The National Institutes of Health (NIH) has conducted a comprehensive analysis of cancer statistics for different age groups in the United States. The study reveals that between 2010 and 2019, the incidence rates of 14 cancer types increased among people under the age of 50. These cancer types include breast cancer, colorectal cancer, kidney cancer, uterine cancer, and others.

Lead investigator Meredith Shiels, Ph.D., notes that this study provides a starting point for understanding which cancers are increasing among individuals under 50. The causes of these increases are likely to be specific to each type of cancer, including changes in cancer risk factors, screening or detection methods, and clinical diagnosis or coding.

The researchers analyzed incidence and mortality trends for 33 cancer types using data from the Centers for Disease Control and Prevention’s United States Cancer Statistics database and national death certificate data. They examined six age groups: three early-onset (15-29 years, 20-39 years, and 40-49 years) and three older-onset (50-59 years, 60-69 years, and 70-79 years).

The study found that the incidence of nine cancer types increased in at least one of the younger age groups, including female breast, colorectal, kidney, testicular, uterine, pancreatic, and three types of lymphoma. Although death rates did not increase in early-onset age groups for most of these cancers, researchers observed concerning increases in rates of colorectal and uterine cancer deaths at younger ages.

Only five cancer types increased in incidence among one of the younger age groups but not among any of the older age groups: melanoma, cervical cancer, stomach cancer, myeloma, and cancers of the bones and joints.

To better understand the magnitude of these increases, researchers estimated how many additional people were diagnosed with early-onset cancers in 2019 compared to expected diagnoses based on rates in 2010. The largest absolute increases were seen for female breast cancer (4,800 additional cases), followed by colorectal (2,100), kidney (1,800), uterine (1,200), and pancreatic cancers (500).

The researchers speculate that risk factors such as increasing obesity may have contributed to some of the increases in early-onset cancer incidence. Changes in cancer screening guidelines, advances in imaging technologies, and increased surveillance of high-risk individuals may also have led to earlier cancer diagnoses, potentially contributing to rising rates among younger age groups.

To more fully understand and address these increasing rates, future studies should examine trends in early-onset cancers across demographics and geography in the U.S. and internationally. Additional research is also needed to better understand the risk factors that are particularly relevant to younger people.

Early Cancer Detection: New Algorithms Revolutionize Primary Care

Two groundbreaking predictive algorithms have been developed to help General Practitioners (GPs) identify patients who may have undiagnosed cancer, including hard-to-detect liver and oral cancers. These advanced models use information about a patient’s health conditions and simple blood tests to accurately predict their chances of having an undiagnosed cancer.

The National Health Service (NHS) currently uses algorithms like the QCancer scores to combine relevant patient data and identify individuals at high risk of having undiagnosed cancer, allowing GPs and specialists to call them in for further testing. Researchers from Queen Mary University of London and the University of Oxford have created two new algorithms using anonymized electronic health records from over 7.4 million adults in England.

The new models are significantly more sensitive than existing ones, potentially leading to better clinical decision-making and earlier cancer diagnosis. Crucially, these algorithms incorporate the results of seven routine blood tests as biomarkers to improve early cancer detection. This approach makes it easier for patients to receive treatment at much earlier stages, increasing their chances of survival.

Compared to the QCancer algorithms, the new models identified four additional medical conditions associated with an increased risk of 15 different cancers, including liver, kidney, and pancreatic cancers. The researchers also found two additional associations between family history and lung cancer and blood cancer, as well as seven new symptoms of concern (itching, bruising, back pain, hoarseness, flatulence, abdominal mass, dark urine) associated with multiple cancer types.

The study’s lead author, Professor Julia Hippisley-Cox, said: “These algorithms are designed to be embedded into clinical systems and used during routine GP consultations. They offer a substantial improvement over current models, with higher accuracy in identifying cancers – especially at early, more treatable stages.”

Dr Carol Coupland, senior researcher and co-author, added: “These new algorithms for assessing individuals’ risks of having currently undiagnosed cancer show improved capability of identifying people most at risk of having one of 15 types of cancer based on their symptoms, blood test results, lifestyle factors, and other information recorded in their medical records.”

The article highlights a substantial decrease in breast cancer deaths among young women between 2010 and 2020. Analyzing data from the Surveillance, Epidemiology, and End Results (SEER) registry, researchers found that incidence-based mortality declined from 9.70 per 100,000 women in 2010 to 1.47/100,000 in 2020 across all subtypes and racial/ethnic groups.

Luminal A had the most pronounced decline among the four subtypes, with a notable drop in 2017 (-32.88% annual percent change). Triple-negative breast cancer also showed a similar trend, with its largest decline in 2018 (-32.82% APC).

The analysis revealed that the declines became more pronounced after 2016, likely reflecting advancements in treatment options and greater access to care and screening. The study’s findings suggest that there are opportunities for further improvement, particularly in reducing disparities.

However, the research also identified some unexpected trends. Among women aged 20-39, luminal A had lower 10-year survival rates than luminal B, which was unexpected as luminal A is generally considered the least aggressive subtype with the most favorable prognosis.

The study’s limitations include a follow-up time limited to 10 years and a relatively smaller number of breast cancer deaths in some racial/ethnic groups. Despite these limitations, the research provides valuable insights into recent trends in mortality rates among young women and highlights the need for further investigation into understanding tumor biology and molecular mechanisms driving carcinogenesis and treatment response in younger women.

The article concludes by emphasizing the importance of continued research to ensure further reduction in breast cancer mortality, including research into population-based screening in women aged 40-49 and targeted screening in younger high-risk women. Additionally, it advocates for access to high-quality treatment and care for all women.