Interval Cancers Research Articles

Rethinking screening mammography in Japan: next-generation breast cancer screening through breast awareness and supplemental ultrasonography.

Breast cancer mortality has not been reduced in Japan despite more than 20years of population-based screening mammography. Screening mammography might not be suitable for Japanese women who often have dense breasts, thus decreasing mammography sensitivity because of masking. The J-START study showed that breast ultrasonography increases the sensitivity and the detection rate for early invasive cancers and lowers the rate of interval cancers for Japanese women in their 40s. Breast awareness and breast cancer survival are directly correlated; however, breast awareness is not widely known in Japan. Next-generation breast cancer screening in Japan should consist of breast awareness campaigns for improving breast cancer literacy and supplemental breast ultrasonography to address the problem of false-negative mammograms attributable to dense breasts.

Cervical cancer in Region Skåne, Sweden 2017-2020 after the implementation of primary HPV screening: A quality assurance audit.

Primary human papilloma virus (HPV) screening to detect cervical cancer and dysplastic lesions was implemented in Region Skåne 2017 for women aged 30-70. The aim of this study was to characterize the screening history of women diagnosed with cervical cancer to evaluate the performance of the screening program, as well as to assess the cancer treatments given and shortcomings in the follow-up of women with cervical dysplasia. We performed a quality assurance audit. The data was collected from the National Cervical Cancer Prevention Registry, Region Skåne Labmedicin database and the Melior Journal system in 2017-2020. We identified 247 women diagnosed with invasive cervical cancer in Region Skåne in 2017-2020. Of these, 35 (14.2%) had a screening history over at least two screening rounds before diagnosis. There were 25 (10.1%) women diagnosed with cervical cancer in between screening intervals, i.e., interval cancer. The most common screening history in women with cervical cancer was irregular screening (143, 57.9%), followed by women being above screening age (44, 17.8%). HPV was detected in 96% of the cases, either in cervical cytology or in the tumor tissue. The screening program detected the disease in 96 (38.9%) of the patients, 149 (60.3%) were diagnosed through symptoms and two (0.80%) as a result of incidental findings. The most powerful tool in the prevention of cervical cancer is screening program attendance. Prolongation with HPV screening among elderly women will also reduce the incidence of cervical cancer. Today, such cancers are usually discovered when symptoms appear.

AI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosis.

Background Few studies have evaluated the role of artificial intelligence (AI) in prior screening mammography. Purpose To examine AI risk scores assigned to screening mammography in women who were later diagnosed with breast cancer. Materials and Methods Image data and screening information of examinations performed from January 2004 to December 2019 as part of BreastScreen Norway were used in this retrospective study. Prior screening examinations from women who were later diagnosed with cancer were assigned an AI risk score by a commercially available AI system (scores of 1-7, low risk of malignancy; 8-9, intermediate risk; and 10, high risk of malignancy). Mammographic features of the cancers based on the AI score were also assessed. The association between AI score and mammographic features was tested with a bivariate test. Results A total of 2787 prior screening examinations from 1602 women (mean age, 59 years ± 5.1 [SD]) with screen-detected (n = 1016) or interval (n = 586) cancers showed an AI risk score of 10 for 389 (38.3%) and 231 (39.4%) cancers, respectively, on the mammograms in the screening round prior to diagnosis. Among the screen-detected cancers with AI scores available two screening rounds (4 years) before diagnosis, 23.0% (122 of 531) had a score of 10. Mammographic features were associated with AI score for invasive screen-detected cancers (P < .001). Density with calcifications was registered for 13.6% (43 of 317) of screen-detected cases with a score of 10 and 4.6% (15 of 322) for those with a score of 1-7. Conclusion More than one in three cases of screen-detected and interval cancers had the highest AI risk score at prior screening, suggesting that the use of AI in mammography screening may lead to earlier detection of breast cancers. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Mehta in this issue.

Prolonged screening interval due to the COVID-19 pandemic and its association with tumor characteristics and treatment; a register-based study from BreastScreen Norway

ObjectiveDuring the COVID-19 pandemic Norway had to suspend its national breast cancer screening program. We aimed to investigate the effect of the pandemic-induced suspension on the screening interval, and its subsequent association with the tumor characteristics and treatment of screen-detected (SDC) and interval breast cancer (IC). MethodsInformation about women aged 50–69, participating in BreastScreen Norway, and diagnosed with a SDC (N = 3799) or IC (N = 1806) between 2018 and 2021 was extracted from the Cancer Registry of Norway. Logistic regression was used to investigate the association between COVID-19 induced prolonged screening intervals and tumor characteristics and treatment. ResultsWomen with a SDC and their last screening exam before the pandemic had a median screening interval of 24.0 months (interquartile range: 23.8–24.5), compared to 27.0 months (interquartile range: 25.8–28.5) for those with their last screening during the pandemic. The tumor characteristics and treatment of women with a SDC, last screening during the pandemic, and a screening interval of 29–31 months, did not differ from those of women with a SDC, last screening before the pandemic, and a screening interval of 23–25 months. ICs detected 24–31 months after screening, were more likely to be histological grade 3 compared to ICs detected 0–23 months after screening (odds ratio: 1.40, 95% confidence interval: 1.06–1.84). ConclusionsPandemic-induced prolonged screening intervals were not associated with the tumor characteristics and treatment of SDCs, but did increase the risk of a histopathological grade 3 IC. This study provides insights into the possible effects of extending the screening interval.

Lynch Syndrome: Approach from the Gastroenterologist’s Point of View

"Colorectal cancer is one of the main causes of death by cancer in the European Union and in Romania. Lynch Syndrome is an autosomal dominant inherited disease that affects around 3% of all colorectal cancer patients, defined by mutations in the mismatch repair genes (MLH1, MSH2, MSH6, PMS2). Aside from the high risk for colorectal cancer (CRC), they exhibit a high risk for endometrial cancer, ovarian cancer, gastric cancer, pancreatic cancer, brain cancer, small bowel cancer, and sebaceous gland cancer. Diagnosis is often made by the gastroenterologist, usually when he meets a young patient with symptoms suggesting the presence of a colonic tumor and a family history of CRC. The role of the gastroenterologist is to investigate the best practices in order to have an early diagnosis and to prevent interval cancers according to the newest guidelines or other gastrointestinal tract tumors associated with Lynch Syndrome. Registries play an important role in the optimal surveillance of these particular categories of patients and should be put into place in every country. They will allow clinicians to have a better understanding of the disease and a more standardized quality of care for them."

Robust cross-vendor mammographic texture models using augmentation-based domain adaptation for long-term breast cancer risk.

Risk-stratified breast cancer screening might improve early detection and efficiency without comprising quality. However, modern mammography-based risk models do not ensure adaptation across vendor-domains and rely on cancer precursors, associated with short-term risk, which might limit long-term risk assessment. We report a cross-vendor mammographic texture model for long-term risk. The texture model was robustly trained using two systematically designed case-control datasets. Textural features, indicative of future breast cancer, were learned by excluding samples with diagnosed/potential malignancies from training. An augmentation-based domain adaption technique, based on flavorization of mammographic views, ensured generalization across vendor-domains. The model was validated in 66,607 consecutively screened Danish women with flavorized Siemens views and 25,706 Dutch women with Hologic-processed views. Performances were evaluated for interval cancers (IC) within 2 years from screening and long-term cancers (LTC) from 2 years after screening. The texture model was combined with established risk factors to flag 10% of women with the highest risk. In Danish women, the texture model achieved an area under the receiver operating characteristic curve (AUC) of 0.71 and 0.65 for ICs and LTCs, respectively. In Dutch women with Hologic-processed views, the AUCs were not different from AUCs in Danish women with flavorized views. The AUC for texture combined with established risk factors increased to 0.68 for LTCs. The 10% of women flagged as high-risk accounted for 25.5% of ICs and 24.8% of LTCs. The texture model robustly estimated long-term breast cancer risk while adapting to an unseen processed vendor-domain and identified a clinically relevant high-risk subgroup.

Supplemental magnetic resonance imaging plus mammography compared with magnetic resonance imaging or mammography by extent of breast density.

Examining screening outcomes by breast density for breast magnetic resonance imaging (MRI) with or without mammography could inform discussions about supplemental MRI in women with dense breasts. We evaluated 52 237 women aged 40-79 years who underwent 2611 screening MRIs alone and 6518 supplemental MRI plus mammography pairs propensity score-matched to 65 810 screening mammograms. Rates per 1000 examinations of interval, advanced, and screen-detected early stage invasive cancers and false-positive recall and biopsy recommendation were estimated by breast density (nondense = almost entirely fatty or scattered fibroglandular densities; dense = heterogeneously/extremely dense) adjusting for registry, examination year, age, race and ethnicity, family history of breast cancer, and prior breast biopsy. Screen-detected early stage cancer rates were statistically higher for MRI plus mammography vs mammography for nondense (9.3 vs 2.9; difference = 6.4, 95% confidence interval [CI] = 2.5 to 10.3) and dense (7.5 vs 3.5; difference = 4.0, 95% CI = 1.4 to 6.7) breasts and for MRI vs MRI plus mammography for dense breasts (19.2 vs 7.5; difference = 11.7, 95% CI = 4.6 to 18.8). Interval rates were not statistically different for MRI plus mammography vs mammography for nondense (0.8 vs 0.5; difference = 0.4, 95% CI = -0.8 to 1.6) or dense breasts (1.5 vs 1.4; difference = 0.0, 95% CI = -1.2 to 1.3), nor were advanced cancer rates. Interval rates were not statistically different for MRI vs MRI plus mammography for nondense (2.6 vs 0.8; difference = 1.8 (95% CI = -2.0 to 5.5) or dense breasts (0.6 vs 1.5; difference = -0.9, 95% CI = -2.5 to 0.7), nor were advanced cancer rates. False-positive recall and biopsy recommendation rates were statistically higher for MRI groups than mammography alone. MRI screening with or without mammography increased rates of screen-detected early stage cancer and false-positives for women with dense breasts without a concomitant decrease in advanced or interval cancers.

Diagnostic performance of two versions of an artificial intelligence system in interval breast cancer detection.

Various versions of artificial intelligence (AI) have been used as a diagnostic tool aid in the diagnosis of breast cancer. One of the most important problems in breast screening progmrams is interval breast cancer (IBC). To compare the diagnostic performance of Transpara v1.6 and v1.7 in the detection of IBC. Reports of screening mammograms of a total 2,248,665 of women were evaluated retrospectively. Of 2,129,486 mammograms reported as Breast Imaging Reporting and Data System (BIRADS) 1 and 2, the IBC group consisted of 323 cases who were diagnosed as having cancer on mammography and were correlated with pathology in second mammogram taken >30 days after first mammogram. Four hundred and forty-one were defined as the control group because they did not change over 2 years. Cancer risk scores of both groups were determined from 1 to 10 with Tranpara v1.6 and v1.7. Diagnostic performances of both versions were evaluated by the receiver operating characteristic curve. Cancer risk scores 1 and 10 in v1.7 increased compared to v1.6 (P < 0.001). In all cases, sensitivity for v1.6 was 56.6%, specificity was 90%, and, for v1.7, sensitivity was 65.9% and specificity was 90%, respectively. In all cases, area under the curve values were 0.812 for v1.6 and 0.856 for v1.7, which was higher in v1.7 (P < 0.001). Diagnostic performance of v1.7 was higher than v1.6 at the 7-12-month period (P < 0.001). The present study showed that Tranpara v1.7 has a higher specificity, sensitivity and diagnostic performance in IBC determination than v1.6. AI systems can be used in breast screening as a secondary or third reader in screening programs.

Early performance measures following regular versus irregular screening attendance in the population-based screening program for breast cancer in Norway.

Irregular attendance in breast cancer screening has been associated with higher breast cancer mortality compared to regular attendance. Early performance measures of a screening program following regular versus irregular screening attendance have been less studied. We aimed to investigate early performance measures following regular versus irregular screening attendance. We used information from 3,302,396 screening examinations from the Cancer Registry of Norway. Examinations were classified as regular or irregular. Regular was defined as an examination 2 years ± 6 months after the prior examination, and irregular examination >2 years and 6 months after prior examination. Performance measures included recall, biopsy, screen-detected and interval cancer, positive predictive values, and histopathological tumor characteristics. Recall rate was 2.4% (72,429/3,070,068) for regular and 3.5% (8217/232,328) for irregular examinations. The biopsy rate was 1.0% (29,197/3,070,068) for regular and 1.7% (3825/232,328) for irregular examinations, while the rate of screen-detected cancers 0.51% (15,664/3,070,068) versus 0.86% (2003/232,328), respectively. The adjusted odds ratio was 1.53 (95% CI: 1.49-1.56) for recall, 1.73 (95% CI: 1.68-1.80) for biopsy, and 1.68 (95% CI: 1.60-1.76) for screen-detected cancer after irregular examinations compared to regular examinations. The proportion of lymph node-positive tumors was 20.1% (2553/12,719) for regular and 25.6% (426/1662) for irregular examinations. Irregular attendance was linked to higher rates of recall, needle biopsies, and cancer detection. Cancers detected after irregular examinations had less favorable histopathological tumor characteristics compared to cancers detected after regular examinations. Women should be encouraged to attend screening when invited to avoid delays in diagnosis.

German mammography screening program: program sensitivity between 2010 and 2016 estimated based on German health claims data

BackgroundProgram sensitivity is a key quality indicator for mammography screening programs (MSP). Estimating program sensitivity usually requires a linkage of screening and cancer registry data. For the German MSP, such data linkage-based estimates have only been reported for two out of 16 federal states. We aimed to explore the potential of estimating program sensitivity for the German MSP based on information available in health claims data.MethodsWe used data from the second-largest statutory health insurance fund in Germany, BARMER (~ 9 million members all over Germany). We included women aged 50 to 69 years with a non-initial screening mammography between 2010 and 2016 and followed them up for two years. We estimated the rate of screen-detected and interval cancers as well as program sensitivity.ResultsPer year, we included 212,400 to 303,667 women (mean age: 60–61 years). Overall, 1,992,287 non-initial MSP screening examinations conducted in these women between 2010 and 2016 were considered for the analyses. Age-standardized program sensitivity ranged between 69.9% [95% CI: 67.3–72.0%] and 71.7% [95% CI: 69.5-73.9%] during the study period. Per 1,000 non-initial screening examinations, the rate of screen-detected breast cancer ranged between 4.6 and 5.3, and the rate of interval breast cancer rates ranged between 0.6 and 0.8 for the first and between 1.3 and 1.4 for the second year after screening.ConclusionsOur results were plausible and consistent with quality indicators estimated for the German MSP based on data linkage and thus support the value of German health claims data in this regard. The quality indicators estimated in our study are in line with levels expected according to European Guidelines.

Are mammography image acquisition factors, compression pressure and paddle tilt, associated with breast cancer detection in screening?

To assess the associations between objectively measured mammographic compression pressure and paddle tilt and breast cancer (BC) detected at the same ("contemporaneous") screen, subsequent screens, or in-between screens (interval cancers). Automated pressure and paddle tilt estimates were derived for 80,495 mammographic examinations in a UK population-based screening programme. Adjusted logistic regression models were fitted to estimate the associations of compression parameters with BC detected at contemporaneous screen (777 cases).Nested case-control designs were used to estimate associations of pressure and tilt with: (a) interval cancer (148 cases/625 age-matched controls) and (b) subsequent screen-detected cancer (344/1436), via conditional logistic regression. Compression pressure was negatively associated with odds of BC at contemporaneous screen (odds ratio (OR) for top versus bottom third of the pressure distribution: 0.74; 95% CI 0.60, 0.92; P-for-linear-trend (Pt) = 0.007). There was weak evidence that moderate pressure at screening was associated with lower odds of interval cancer (OR for middle versus bottom third: 0.63; 95% CI 0.38, 1.05; p = 0.079), but no association was found between pressure and the odds of BC at subsequent screen. There was no evidence that paddle tilt was associated with the odds of contemporaneous, subsequent screen or interval cancer detection. Findings are consistent with compression pressure, but not paddle tilt, affecting the performance of mammographic screening by interfering with its ability to detect cancers. Inadequate or excessive compression pressure at screening may contribute to a reduced ability to detect cancers, resulting in a greater number of interval cancer cases.

Early screening outcomes before, during, and after a randomized controlled trial with digital breast tomosynthesis

PurposeTo describe and compare early screening outcomes before, during and after a randomized controlled trial with digital breast tomosynthesis (DBT) including synthetic 2D mammography versus standard digital mammography (DM) (To-Be 1) and a follow-up cohort study using DBT (To-Be 2). MethodsRetrospective results of 125,020 screening examinations from four consecutive screening rounds performed in 2014–2021 were described and compared for pre-To-Be 1 (DM), To-Be 1 (DM or DBT), To-Be 2 (DBT), and post-To-Be 2 (DM) cohorts. Descriptive analyses of rates of recall, biopsy, screen-detected and interval cancer, distribution of histopathologic tumor characteristics and time spent on image interpretation and consensus were presented for the four rounds including five cohorts, one cohort in each screening round except for the To-Be 1 trail, which included a DBT and a DM cohort. Odds ratios (OR) with 95% CIs was calculated for recall and cancer detection rates. ResultsRate of screen-detected cancer was 0.90% for women screened with DBT in To-Be 2 and 0.64% for DM in pre-To-Be 1. The rates did not differ for the To-Be 1 DM (0.61%), To-Be 1 DBT (0.66%) and post-To-Be 2 DM (0.67%) cohorts. The interval cancer rates ranged between 0.13% and 0.20%. The distribution of histopathologic tumor characteristics did not differ between the cohorts. ConclusionsScreening all women with DBT following a randomized controlled trial in an organized, population-based screening program showed a temporary increase in the rate of screen-detected cancer.

Population-based breast cancer screening in Pavia (northern Italy) in 2016-2018: Key performance indicators and sensitivity estimate.

This study aims to assess the quality of the population-based breast cancer screening programme in Pavia, northern Italy computing its key performance indicators and estimating its sensitivity for the years 2016-2018. Invitation and examination coverage, participation rate, recall rate, detection rate and positive predictive values were computed on the basis of data provided yearly to the Italian Ministry of Health. Sensitivity was estimated identifying interval cancers in the local Cancer Registry and computed with the proportional incidence method. In 2016-2018 the adjusted invitation coverage was 90%, and the adjusted participation rate was 62%. Recall rate was 8.4% for first screenings and 3.9% for subsequent ones. The number of screen-detected cases was 268, corresponding to a detection rate of 6.6‰ for first screenings and 4.6‰ for subsequent screenings. The number of interval cancers observed was 110 over the study period; the proportional incidence was 22% for the first interval year and 50% for the second interval. The overall sensitivity of the screening program was 64%. The analysis of performance indicators and sensitivity estimates for the Pavia programme indicates that the programme performance is in line with the quality standards set by the European Union and the Italian reference scientific society (GISMa).

654 Inflammatory Bowel Disease and Risk of Interval Colorectal Carcinoma: What’s Missing in Surveillance Endoscopy?

Abstract Colorectal carcinomas in ulcerative colitis patients are more commonly missed endoscopically compared to those in other symptomatic patients. They may present as flat lesions on a background of colitis, making them harder to visualise. Those presenting after negative colonoscopies are termed interval cancers, and account for up to 50% of colorectal cancers in patients with inflammatory bowel disease (IBD). Professional bodies recommend the use of chromoendoscopy for IBD surveillance to improve diagnostic yield by allowing targeted biopsies of non-polypoid lesions. We present an asymptomatic missed cancer in a patient with UC following a complete white light surveillance colonoscopy. After the sole endoscopic finding of a small, raised rectal lesion, found to be dysplastic, a CT scan incidentally demonstrated a missed ascending colon tumour. Had chromoendoscopy been used, this cancer may have been detected initially. This case report demonstrates that missed tumours remain a problem during surveillance endoscopy for IBD.

Use of novel artificial intelligence computer-assisted detection (AI-CAD) for screening mammography: an analysis of 17,884 consecutive two-view full-field digital mammography screening exams.

Novel artificial intelligence computer-assisted detection (AI-CAD) systems based on deep learning (DL) promise to support screen reading. To test a DL-AI-CAD system compared to human reading on consecutive screening mammograms. In this retrospective study, 17,884 consecutive anonymized screening mammograms, double-read from January to November 2018, were processed by the DL-AI-CAD system. AI-CAD reading was considered positive if the AI-CAD case scores exceeded 30 (range = 1-100) and the lesion was correctly marked. Likewise, human reading (R1 or R2, respectively) was considered positive if the lesion was correctly identified and called. Receiver operating characteristic (ROC) analysis was performed and accuracy data were calculated. Ground truth for benign lesions: absence of malignancy after cancer registry matching (2022); for malignancy: histopathologic proof; evaluation was patient-based. In total, 114 screen-detected and 17 interval cancers (ICA) occurred. ROC analysis of screen-detected cancers yielded an AUC of 89% for AI-CAD. Sensitivity/specificity was 81.7%/80.2% for AI-CAD; 77.1%/91.7% for R1; 78.6/91.6% for R2. Combining each human reading with AI-CAD was as sensitive as human double-reading (all approximately 88%), but less specific (approximately 75%) compared to human double-reading (approximately 87%). These AI-CAD combinations required consensus readings for twice as many cases as the human combination. Four of 17 ICA exceeded a case score of 30; two of four CAD correctly marked the quadrant of the subsequent ICA. Including ICA cases, this AI-CAD achieved comparable sensitivity to human reading at lower specificity. Combining human reading and AI-CAD allows increasing sensitivity compared to single-reading.

Breast MRI – The champion in the millimeter league: MIO breast MRI – The method of choice in women with dense breasts

We perform MRI of the breast as a first pass technique. We successfully established 10-minute-protocols (including T2 images) with a fixed dosage of 5 ml 1 M CM. A high spatial resolution of 526 × 526, better 672 × 672 or maximum (1.024 × 1.024, MIO MRI) is vital to achieve best results. We use fixation tools to avoid motion artifacts. Motion correction algorithms can, however, often eliminate such artifacts when they are present. In initial breast MRI exams, morphologic features are the most important criteria for lesion evaluation. If previous exams are available for comparison, the main criteria indicating a suspicious lesion are an increase in lesion size or the depiction of new lesions.High quality HR MRI of the breast is the method of choice in women with dense or extremely dense breasts in all cases (screening, assessment, follow up). In density type A or B, MRI can be helpful in defined constellations, e.g. when MX and US are limited or contraindicated.According to our experience, 95% or more of all carcinomas of the breast are detectable on MRI. The remaining 5% of MRI-occult lesions are intraductal tumors or very small invasive carcinomas depicted with mammography due to associated microcalcifications. MRI is, however, superior to all other imaging modalities in the detection of the clinically relevant DCIS (high risk DCIS, intermediate type).Consecutive MRI examinations in intervals of 12 to 24 months allow a reliable detection of invasive breast cancer with an average size of 7–8 mm. This corresponds to a rate of metastasis-free locoregional lymph nodes in >95% of cases. The rate of interval cancers is <2%. In conclusion, this strategy may increase the overall-lifetime survival of breast cancer patients to more than 95%. Inversely, mortality may be reduced to <5%.Taking these improvements in early breast cancer detection and survival that can be achieved through the implementation of QA HR MRI of the breast into account, it should be discussed to modify oncologic guidelines for the treatment of breast cancer.MRI is the best diagnostic tool we have and according to our experience, a first pass, quality-assured high-resolution breast MRI protocol provides best diagnostic results at minimal procedural effort.

Causes and consequences of delayed diagnosis in breast cancer screening with a focus on mammographic features and tumour characteristics

PurposeTo study the prevalence, causes and consequences of delayed breast cancer diagnosis in the screening population. MethodsThis retrospective study was performed in women who underwent biennial screening mammography between January 1, 2009 and June 30, 2019. Patients were divided into 3 groups; screen-detectedbreast cancer (SDC) without a diagnostic delay, a primary diagnostic delay(i.e. missed cancer at previous screening round)and a delay in diagnostic work-up after recall. Women with a true interval cancer (IC; i.e. not visible on prior examinations) were excluded. Outcome parameters included mammographic and tumour characteristics, lymph node status and surgical treatment. ResultsIn our sample of 4491 women with breast cancer (4292 SDC and 199 ‘missed’ IC), respectively, a total of 1112 women experienced a diagnostic delay of ≥ 4 months. Compared to women without a diagnostic delay (n = 2720), the 176 women with a delay in diagnostic work-up showed overall similar mammographic abnormalities (P = 0.052). These groups show similar distributions in invasive tumours, tumour stage and lymph node status (P = 0.25, P = 0.95 and P = 0.93, respectively). Women with a primary diagnostic delay (n = 936) showed less calcifications (P < 0.001), and more masses with calcifications and architectural distortions on mammography (P = 0.01 and P = 0.04, respectively). Moreover, this group comprised larger tumours (P < 0.001) and lymph node metastases (P < 0.001), and more often underwent mastectomy (P < 0.001). ConclusionsA primary diagnostic delay in breast cancer diagnosis results in less favourable tumour characteristics and relatively more mastectomies compared to no delay in breast cancer diagnosis and a delay in diagnostic work-up after recall.

Update and latest advances in mechanisms and management of colitis-associated colorectal cancer.

Colitis-associated colorectal cancer (CAC) is defined as a specific cluster of colorectal cancers that develop as a result of prolonged colitis in patients with inflammatory bowel disease (IBD). Patients with IBD, including ulcerative colitis and Crohn's disease, are known to have an increased risk of developing CAC. Although the incidence of CAC has significantly decreased over the past few decades, individuals with CAC have increased mortality compared to individuals with sporadic colorectal cancer, and the incidence of CAC increases with duration. Chronic inflammation is generally recognized as a major contributor to the pathogenesis of CAC. CAC has been shown to progress from colitis to dysplasia and finally to carcinoma. Accumulating evidence suggests that multiple immune-mediated pathways, DNA damage pathways, and pathogens are involved in the pathogenesis of CAC. Over the past decade, there has been an increasing effort to develop clinical approaches that could help improve outcomes for CAC patients. Colonoscopic surveillance plays an important role in reducing the risk of advanced and interval cancers. It is generally recommended that CAC patients undergo endoscopic removal or colectomy. This review summarizes the current understanding of CAC, particularly its epidemiology, mechanisms, and management. It focuses on the mechanisms that contribute to the development of CAC, covering advances in genomics, immunology, and the microbiome; presents evidence for management strategies, including endoscopy and colectomy; and discusses new strategies to interfere with the process and development of CAC. These scientific findings will pave the way for the management of CAC in the near future.

Persistence of patient-detected breast cancer over time: 1990-2019.

The continued presentation of patient-detected breast cancer (BC) and associated characteristics over time is understudied. In a large institutional cohort of first primary stage 0-IV patients with BC in 1990-2019 (n=15,827), diagnostic method (patient-detected [PtDBC] [n=5844]; mammography-detected [MamDBC] [nondiagnostic] [n=9248]; and physician-detected [PhysDBC] [n=736]) and patient and tumor characteristics including age, race, TNM stage, and hormone-receptor status were reviewed. Pearson χ2 tests for bivariate comparisons and logistic regression for patient detection-associated factors were used. In a cohort from 1990 to 2019, the proportion aged 50-74 years (55%-63%; p<.001) and non-White race (9%-37%; p<.001) increased over time. Percentage PtDBC decreased over time but case numbers increased (1990-1999: 44% [n=1399]; 2010-2019: 34% [n=2349]; p<.001). Excluding stage 0, PtDBC declined from 47% to 41% over time (p<.001). In 2010-2019, 21% of cases were stage 0, 91% of which were mammography detected (n=1439). Seventy percent of patient-detected cases were stage II-IV (stage II, 44%; stage III, 20%; stage IV, 6%; p<.001). In adjusted logistic regression, the odds of PtDBC decreased over time (2000-2009: odds ratio [OR],.65 [95% CI, .58-.72]; 2010-2019: OR,.54 [95% CI, .49-.60]), with age <40 years OR,15.81, and Black and non-White other at 50% increased risk. The relative proportion of PtDBC decreased to a constant 34%-40% of total cases after 1990-1999. PtDBC case numbers increased in subsequent years (2000-2019), and were consistently higher stage. Interval cancers, mammography-screening uptake, breast health awareness of age groups outside screening guidelines, and underserved socioeconomic groups may be related to the continued significant PtDBC incidence. After decades of mammography-screening availability, symptomatic patient-detected breast cancer declined over time from 44% to a persistent rate of 34% in our institutional cohort. The persistence of patient-detected breast cancer over time presents a difficult situation for patients and care givers without clear diagnosis pathways for younger and older women outside recommended screening guidelines, who often present with higher stage and more lethal characteristics. More timely diagnosis and treatment including breast health awareness, prompt presentation of breast problems, outreach to younger age and minority groups, and provision of specialized training and care delivery for symptomatic patient-detected breast cancer are needed.

Assessing Breast Cancer Risk by Combining AI for Lesion Detection and Mammographic Texture.

Background Recent mammography-based risk models can estimate short-term or long-term breast cancer risk, but whether risk assessment may improve by combining these models has not been evaluated. Purpose To determine whether breast cancer risk assessment improves when combining a diagnostic artificial intelligence (AI) system for lesion detection and a mammographic texture model. Materials and Methods This retrospective study included Danish women consecutively screened for breast cancer at mammography from November 2012 to December 2015 who had at least 5 years of follow-up data. Examinations were evaluated for short-term risk using a commercially available diagnostic AI system for lesion detection, which produced a score to indicate the probability of cancer. A mammographic texture model, trained on a separate data set, assessed textures associated with long-term cancer risk. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate both the individual and combined performance of the AI and texture models for the prediction of future cancers in women with a negative screening mammogram, including those with interval cancers diagnosed within 2 years of screening and long-term cancers diagnosed 2 years or more after screening. AUCs were compared using the DeLong test. Results The Danish screening cohort included 119 650 women (median age, 59 years [IQR, 53-64 years]), of whom 320 developed interval cancers and 1401 developed long-term cancers. The combination model achieved a higher AUC for interval and long-term cancers grouped together than either the diagnostic AI (AUC, 0.73 vs 0.70; P < .001) or the texture risk (AUC, 0.73 vs 0.66; P < .001) models. The 10% of women with the highest combined risk identified by the combination model accounted for 44.1% (141 of 320) of interval cancers and 33.7% (472 of 1401) of long-term cancers. Conclusion Combining a diagnostic AI system and mammographic texture model resulted in improved risk assessment for interval cancers and long-term cancers and enabled identification of women at high risk. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Poynton and Slanetz in this issue.