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Take a look at a selection of our recent media coverage:
6th May 2022
Globally, cancer of the colon and rectum (colorectal cancer) was diagnosed in 1.93 million people in 2020 and responsible for 916,000 deaths. Moreover, screening colonoscopy has been shown to be associated with a substantial decreased mortality risk. CT colonography (CTC) is a minimally invasive test that uses CT scans to check the colon and rectum. In a 2008 study, the authors concluded that CTC screening identified 90% of subjects with adenomas or cancers measuring 10 mm or more in diameter and that the results augmented published data on the role of CTC in screening patients with an average risk of colorectal cancer. However, to date, there is limited information on the sociodemographic factors that might influence uptake of CTC.
For the present investigation, the researchers turned to the National Health Interview Survey (NHIS), which is a nationally representative cross-sectional survey and used data collected in 2019. Included participants were aged 50 to 75 years of age and with no recorded history of colorectal cancer. In the NHIS survey, individuals were asked about whether or not they ever had a CTC and if they responded positively, when the scan had been performed. The researchers collected additional information on age, gender, ethnicity and employment status. They employed multiple variable logistic regression to evaluate predictors of CTC use.
Predictors of CTC utilisation
A total of 13,709 individuals with a mean age of 61.4 years (52.7% female) were included in the analysis, of whom, 70.3% were White, 10.4% Black and 12.1% Hispanic.
In total, only 1.4% of participants reported having previously undergone CTC and, of these, 39.9% had the procedure within the last 12 months.
When analysing the association between CTC use and ethnicity, Hispanic individuals were more than twice as likely to undergo CTC compared with White participants (OR = 2.67, 95% CI 1.66 – 4.29, p < 0.001). There was also a similarly higher use among Black individuals (OR = 2.47, 95% CI 1.60 – 3.82, p < 0.001) than White participants.
Among the other sociodemographic factors examined, only participants who reported that they worked in the last week were significantly less likely to have a CTC (OR = 0.61, 95% CI 0.40 – 0.94, p = 0.024).
One limitation recognised by the authors was how the study data were collected in 2019 prior to the COVID-19 pandemic and therefore they were unable to assess any potential impact on CTC uptake. They concluded that strategies improving access to CTC services could mitigate the observed racial disparities.
O’Connor B et al. Predictors of CT Colonography Use: Results From the 2019 National Health Interview Cross-Sectional Survey J Am Coll Radiol 2022
17th March 2022
The use of a faecal microbiota signature can be used for the screening and early detection of patients with pancreatic adenocarcinoma. This was the finding of a study by researchers from the Structural and Computational Biology Unit, Baden, Germany.
Pancreatic ductal adenocarcinoma accounts for more than 90% of pancreatic cancer cases and is a highly aggressive and lethal cancer due to both the lack of early detection and limited response to treatments. Furthermore, the majority of patients with pancreatic cancer are asymptomatic until the disease reaches an advanced stage and there is no standard programme for screening high-risk patients. Currently, the only biomarker approved for pancreatic ductal adenocarcinoma is serum carbohydrate antigen (CA19-9) although it’s use is limited by low sensitivity and specificity.
Some evidence suggests that there is a relationship between the duodenal microbiota in pancreatic head cancer patients that could be useful in future trials investigating the role of faecal microbiota in pancreatic cancer. Nevertheless, translation of the potential changes in gut microbiota and its relationship to pancreatic cancer has been largely unexplored.
For the present study, the German researchers took faecal samples from normal and cancerous pancreatic tissue and assessed the microbial composition using whole-genomic sequencing. They recruited three groups of patients: newly diagnosed adults with pancreatic cancer but before they had started treatment; individuals for which pancreatic cancer was suspected and finally a cohort with chronic pancreatitis. The results from these patients were used in the discovery phase of the study whereas a second patient group was used for validation purposes. The sensitivity and specificity were determined using the area under the receiver operating characteristic curve.
Faecal microbiota and pancreatic ductal adenocarcinoma
A total of 57 newly diagnosed treatment naive and 29 with confirmed pancreatic cancer were included in the analysis.
The faecal microbiota composition was found to be significantly different in patients with pancreatic adenocarcinoma compared to both controls (p < 0.0001) and from patients with chronic pancreatitis.
A faecal metagenomic classifier identified a pancreatic ductal adenoma with an area under the curve (AUC) of 0.84 based on the presence of 27 bacterial species. However, with addition of CA19-9 levels, this increased the AUC to 0.94. Using a separate sample of patients to validate the classifier, it was found that the AUC was 0.83.
In a discussion of their findings, the authors suggested that the metagenomic classifier was able to robustly and accurately predict pancreatic ductal adenocarcinoma based on the composition of faecal microbiota species and that addition of CA19-9 data (which is already an approved biomarker) further enhanced the accuracy of the model. They concluded that the microbial panel they had identified could provide future entry points for disease prevention and therapeutic interventions.
Kartal E et al. A faecal microbiota signature with high specificity for pancreatic cancer Gut 2022
10th February 2022
Breast cancer scans for women with no recognisable risk factors for the disease has identified that around 40% of these women have a tumour, emphasising the need to continue scanning eligible women. This was the conclusion of a study by researchers from the Sydney School of Public Health, University of Sydney, Australia.
A 2015 systematic review of the benefits and harms of breast cancer screening concluded that for women of all ages and at average risk, screening was associated with a reduction in breast cancer mortality of approximately 20%. However, risk-stratification of breast cancer screening might improve the cost-effectiveness of the whole scanning process and at the same time, potentially reduce any associated risks. In fact, a 2018 study found that not offering breast cancer screening to women at lower risk could improve the cost-effectiveness of the screening programme, through reducing over diagnosis and at the same time, maintaining the benefits of screening. Nevertheless, little is known about the screening outcomes for women without any known breast cancer risk factors and who are therefore assumed to be at a lower risk.
For the present study, the Australian team examined the breast cancer scan outcomes for women deemed to be at the lower end of the risk spectrum. They undertook a retrospective analysis of clinical data routinely collected in the BreastScreen Western Australia (BSWA) program and included women aged 40 years and older. Although the program does stratify women in terms of their risk, i.e., those with > 2 affected first-degree relatives etc), women age 40 and over can volunteer to participate, despite not being in the target group. The researchers collected variables such as age, need for repeat scans together with information such as a previous history of breast or ovarian cancer, use of hormone replacement therapy etc. The scans were then categorised as having none of these factors verses at least one factor and age bands of 40 -49, 50 -59, 60 – 69 and > 70 years were created. The outcomes of interest were cancer detection rates at screening (CDR) per 10,000 screens and the interval cancer rates (ICR) per 10,000 women-years.
Breast cancer scans and detection of tumours
A total of 1,026,137 screens were performed including 323,082 in women aged > 40 years, who had a mean age of 58.5 years. Among the total scans, 44.7% of women had at least one risk factor although for 55.3% of screens, the women had none of the recorded risk factors.
In the screens without any risk factors, the CDR was 50 (95% CI 48 – 52) per 10,000 screens and the ICR was 7.9 (95% CI 7.4 – 8.4). Overall, in all of the scans in which cancer was detected, for 40.9% of cases, there were no recognised risk factors present.
The authors concluded that given how many of the scans identified cancers in women without risk factors, their finding did not justify less frequent screening of women without recognised risks.
Noguchi N et al. Evidence from a BreastScreen cohort does not support a longer inter-screen interval in women who have no conventional risk factors for breast cancer Breast 2022
16th December 2021
The screening of older black patients or those with a first-degree relative who has a haematological cancer led to the detection of monoclonal gammopathy of undetermined significance (MGUS), which is a precursor to multiple myeloma (MM). This was the conclusion of a study by a researchers from the Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, US, presented at ASH 2021.
MGUS a benign condition which is usually diagnosed incidentally when tests are performed to investigate other problems although MGUS is a precursor to multiple myeloma in around 1% of cases. However, the prevalence of MGUS has not been described in a population at high risk of developing MM, in particular, Black/African American (AA) individuals or first-degree relatives of patients with haematologic malignancies (HM).
In 2019, the US researchers launched the first nationwide US (PROMISE) screening older black patients study for individuals at high risk of MM to help better identify what population would benefit most from screening and early intervention for precursor MM stages. The overarching aim of the study is to assess the prevalence of MGUS in a high risk population and to characterise the clinical variables of individuals who screen positive. For the present study, the researchers reported on screening data available for the first 2960 participants.
The researcher team recruited individuals aged 40 or older with an additional MM risk factor which included Black/AAs and those with a first-degree relative diagnosed with a haematologic malignancy or a precursor condition to MM. Blood from all participants was analysed to measure the serum free light chains (sFLC), IgG, IgA and IgM. In addition and for comparative purposes, the team also identified and screened additional individuals from the Mass General Brigham (MGB) Biobank who met the PROMISE enrolment criteria. The researchers measured Heavy-Chain MGUS (HC-MGUS) as a marker for MGUS.
Screening older black patients occurred with 2960 individuals participants (1092 from PROMISE). The overall prevalence of HC-MGUS was 9.6% (95% CI 8.6 – 11%) and 10% (95% CI 8.3-12%) in PROMISE and 9.4% (95% CI 8.1 – 11%) in the MGB cohort.
The prevalence of HC-MGUS increased with age in high-risk individuals from 4.9% (CI 3.3 – 6.9%) for participants aged 40-49 to 13% (95% CI 10 – 17%) in the 70-79 range (P < 0.005 ). Among monoclonal HC-MGUS, they detected 65% IgG, 18% IgM, and 18% IgA. M-spike was quantified in 97% of samples.
The authors concluded that screening older black patients or those who have a first-degree relative with an HM have a high prevalence MGUS and may therefore benefit from precision screening approaches to allow for early detection and clinical intervention.
El-Khoury H et al. High Prevalence of Monoclonal Gammopathy in a Population at Risk: The First Results of the Promise Study. ASH Conference 2021
23rd September 2021
Globally, in 2020, there were an estimated 2.3 million women diagnosed with breast cancer leading to 685,000 deaths. Fortunately, improvements in survival over recent decades have been attributed to population-based breast cancer screening with mammography. In fact, a recent UK study suggested that screening reduces cancer mortality by 38% among women screened at least once.
The use of artificial intelligence (AI) systems for image recognition in breast cancer screening could lead to improvements in the detection of cases, either as a standalone system or as an aid to radiologists. Indeed, there is some evidence to support the value of AI with one retrospective analysis of an AI screening algorithm concluding that it showed better diagnostic performance than a radiologist. Nevertheless, in a 2019 review, it was concluded that while AI systems have good accuracy for breast cancer detection, methodological concerns and evidence gaps exist that limit translation into clinical breast cancer screening settings.
In light of these concerns, a team from the Division of Health Sciences, University of Warwick, UK, were commissioned by the UK National Screening Committee to undertake a systematic review to determine whether there was sufficient evidence to support the introduction of AI for mammographic image analysis in breast screening. They conducted literature searches up to May 2021 and included studies that reported the test accuracy of AI algorithms either alone or in combination with radiologists, to detect breast cancer in digital mammograms in screening practice or in test sets. The team included cancer confirmed by histological analysis of biopsy samples in cases where women were referred for further tests after screening as the reference standard or from symptomatic presentation during follow-up.
The review identified a total of 12 studies including 131,822 women undergoing breast cancer screening. In studies with a standalone AI system, the algorithm calculated a cancer risk score, categorising women at either high (recall) or low (no recall) risk. When used to assist the radiologist, the AI system simply provided a level of suspicion. In two large retrospective studies including 76,813 women, that compared the AI system with the clinical decisions of a radiologist, 96% of systems were less accurate than a single radiologist and all were less accurate than a double read.
Overall, the authors reported considerably heterogeneity in study methodology, some of which resulted in high concerns over the risk of bias and applicability. In their study, they commented that “evidence is insufficient on the accuracy or clinical effect of introducing AI to examine mammograms anywhere on the screening pathway”.
In the conclusion, the authors noted how AI systems for breast cancer screening are a long way from having the quality and quantity required for implementation into clinical practice.
Freeman K et al. Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy. BMJ 2021