Imaging biomarkers are underutilised but highly predictive prognostic factors for the more fatal breast cancer subtypes.

PURPOSE: The development and refinement of breast imaging modalities offer a wealth of diagnostic information such as imaging biomarkers, which are primarily the mammographic appearance of the various breast cancer subtypes. These are readily available preoperatively at the time of diagnosis and can enhance the prognostic value of currently used molecular biomarkers. In this study, we investigated the relative utility of the molecular and imaging biomarkers, both jointly and independently, when predicting long-term patient outcome according to the site of tumour origin. METHODS: We evaluated the association of imaging biomarkers and conventional molecular biomarkers, (ER, PR, HER-2, Ki67), separately and combined, with long-term patient outcome in all breast cancer cases having complete data on both imaging and molecular biomarkers (n = 2236) diagnosed in our Institute during the period 2008-2019. Large format histopathology technique was used to document intra- and intertumoural heterogeneity and select the appropriate foci for evaluating molecular biomarkers. RESULTS: The breast cancer imaging biomarkers were strongly predictive of long-term patient outcome. The molecular biomarkers were predictive of outcome only for unifocal acinar adenocarcinoma of the breast (AAB), but less reliable in the multifocal AAB cases due to variability of molecular biomarkers in the individual tumour foci. In breast cancer of mesenchymal origin (BCMO), conventionally termed classic invasive lobular carcinoma, and in cancers originating from the major lactiferous ducts (ductal adenocarcinoma of the breast, DAB), the molecular biomarkers misleadingly indicated favourable prognosis, whereas the imaging biomarkers in BCMO and DAB reliably indicated the high risk of breast cancer death. Among the 2236 breast cancer cases, BCMO and DAB comprised 21% of the breast cancer cases, but accounted for 45% of the breast cancer deaths. CONCLUSIONS: Integration of imaging biomarkers into the diagnostic workup of breast cancer yields a more precise, comprehensive and prognostically accurate diagnostic report. This is particularly necessary in multifocal AAB cases having intertumoural heterogeneity, in diffuse carcinomas (DAB and BCMO), and in cases with combined DAB and AAB. In such cases, the imaging biomarkers should be prioritised over molecular biomarkers in planning treatment because the latter fail to predict the severity of the disease. In combination with the use of the large section histopathology technique, imaging biomarkers help alleviate some of the current problems in breast cancer management, such as over- and under-assessment of disease extent, which carry the risk of overtreatment and undertreatment.

Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools.

BACKGROUND: We sought to develop a proteomics-based risk model for lung cancer and evaluate its risk-discriminatory performance in comparison with a smoking-based risk model (PLCOm2012) and a commercially available autoantibody biomarker test. METHODS: We designed a case-control study nested in 6 prospective cohorts, including 624 lung cancer participants who donated blood samples at most 3 years prior to lung cancer diagnosis and 624 smoking-matched cancer free participants who were assayed for 302 proteins. We used 470 case-control pairs from 4 cohorts to select proteins and train a protein-based risk model. We subsequently used 154 case-control pairs from 2 cohorts to compare the risk-discriminatory performance of the protein-based model with that of the Early Cancer Detection Test (EarlyCDT)-Lung and the PLCOm2012 model using receiver operating characteristics analysis and by estimating models' sensitivity. All tests were 2-sided. RESULTS: The area under the curve for the protein-based risk model in the validation sample was 0.75 (95% confidence interval [CI] = 0.70 to 0.81) compared with 0.64 (95% CI = 0.57 to 0.70) for the PLCOm2012 model (Pdifference = .001). The EarlyCDT-Lung had a sensitivity of 14% (95% CI = 8.2% to 19%) and a specificity of 86% (95% CI = 81% to 92%) for incident lung cancer. At the same specificity of 86%, the sensitivity for the protein-based risk model was estimated at 49% (95% CI = 41% to 57%) and 30% (95% CI = 23% to 37%) for the PLCOm2012 model. CONCLUSION: Circulating proteins showed promise in predicting incident lung cancer and outperformed a standard risk prediction model and the commercialized EarlyCDT-Lung.

Multifocal and diffusely infiltrating breast cancers are highly fatal subgroups needing further improvement in diagnostic and therapeutic strategies.

Physicians treating breast cancer patients often wonder why this dreaded disease is still fatal in some women despite our best diagnostic and therapeutic efforts. Our own studies on prospectively documented cases spanning several decades have given us new insights for approaching this problem. By using imaging biomarkers to classify breast cancer subtypes according to their apparent site of origin, we found that a majority of breast cancer deaths (71%) occur in a minority of breast cancers (45%). Breast cancer deaths are significantly more likely to occur in women with multifocal acinar adenocarcinoma of the breast, AAB (13.1%), diffusely invasive breast cancers of ductal origin, DAB (24 %) and breast malignancies of mesenchymal hybrid cell origin, BCMO (33.7%) compared with women having unifocal invasive breast cancers (6.1%). Preventing more of these fatal events will require a re-evaluation of the current imperfect histopathologic terminology of breast cancer with special attention to the diffuse breast cancer subtypes, intensification of multimodality imaging and multidisciplinary management, as well as application of image guided large format histopathology.

Low-grade glioma risk SNP rs11706832 is associated with type I interferon response pathway genes in cell lines.

Genome-wide association studies (GWAS) have contributed to our understanding of glioma susceptibility. To date, 25 risk loci for development of any of the glioma subtypes are known. However, GWAS studies reveal little about the molecular processes that lead to increased risk, especially for non-coding single nucleotide polymorphisms (SNP). A particular SNP in intron 2 of LRIG1, rs11706832, has been shown to increase the susceptibility for IDH1 mutated low-grade gliomas (LGG). Leucine-rich repeats and immunoglobulin-like domains protein 1 (LRIG1) is important in cancer development as it negatively regulates the epidermal growth factor receptor (EGFR); however, the mechanism responsible for this particular risk SNP and its potential effect on LRIG1 are not known. Using CRISPR-CAS9, we edited rs11706832 in HEK293T cells. Four HEK293T clones with the risk allele were compared to four clones with the non-risk allele for LRIG1 and SLC25A26 gene expression using RT-qPCR, for global gene expression using RNA-seq, and for metabolites using gas chromatography-mass spectrometry (GC-MS). The experiment did not reveal any significant effect of the SNP on the expression levels or splicing patterns of LRIG1 or SLC25A26. The global gene expression analysis revealed that the risk allele C was associated with upregulation of several mitochondrial genes. Gene enrichment analysis of 74 differentially expressed genes in the genome revealed a significant enrichment of type I interferon response genes, where many genes were downregulated for the risk allele C. Gene expression data of IDH1 mutated LGGs from the cancer genome atlas (TCGA) revealed a similar under expression of type I interferon genes associated with the risk allele. This study found the expression levels and splicing patterns of LRIG1 and SLC25A26 were not affected by the SNP in HEK293T cells. However, the risk allele was associated with a downregulation of genes involved in the innate immune response both in the HEK293T cells and in the LGG data from TCGA.

Assessment of the EarlyCDT-Lung test as an early biomarker of lung cancer in ever-smokers: A retrospective nested case-control study in two prospective cohorts.

The EarlyCDT-Lung test is a blood-based autoantibody assay intended to identify high-risk individuals for low-dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT-Lung test in ever-smokers. We conducted a nested case-control study within two prospective cohorts to evaluate the risk-discriminatory performance of the EarlyCDT-Lung test using prediagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a prediagnostic blood sample <3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT-Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT-Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI: 0.34-2.30) for a moderate risk EarlyCDT-Lung test result and 1.09 (95% CI: 0.48-2.47) for a high-risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI: 4.6-14) and overall specificity was 92% (95% CI: 87-96) when considering a high-risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI: 7.2-32.1) in subjects with blood drawn up to 1 year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT-Lung test in identifying the high-risk subjects in ever-smokers for lung cancer screening in the EPIC and NSHDS cohorts.

Prediagnostic biomarkers for early detection of glioma-using case-control studies from cohorts as study approach.

Background: Understanding the trajectory and development of disease is important and the knowledge can be used to find novel targets for therapy and new diagnostic tools for early diagnosis. Methods: Large cohorts from different parts of the world are unique assets for research as they have systematically collected plasma and DNA over long-time periods in healthy individuals, sometimes even with repeated samples. Over time, the population in the cohort are diagnosed with many different diseases, including brain tumors. Results: Recent studies have detected genetic variants that are associated with increased risk of glioblastoma and lower grade gliomas specifically. The impact for genetic markers to predict disease in a healthy population has been deemed low, and a relevant question is if the genetic variants for glioma are associated with risk of disease or partly consist of genes associated to survival. Both metabolite and protein spectra are currently being explored for early detection of cancer. Conclusions: We here present a focused review of studies of genetic variants, metabolomics, and proteomics studied in prediagnostic glioma samples and discuss their potential in early diagnostics.

Progression patterns in monoclonal gammopathy of undetermined significance and multiple myeloma outcome: a cohort study in 42 patients.

Follow-up of low-risk monoclonal gammopathy of undetermined significance (MGUS) is debated as multiple myeloma (MM) progression risk is low. Worse MM outcome was reported for patients followed for low-risk MGUS, possibly due to less optimal follow-up. However, it is unknown whether progressing low-risk MGUS is associated with aggressive tumor behavior. Understanding these patterns is crucial for MGUS management. Here, we investigated whether progression from low-risk MGUS is associated with worse MM outcome in patients who had no MGUS follow-up before myeloma diagnosis. We retrospectively determined the MGUS status in repeated pre-diagnostic blood samples prospectively collected from 42 myeloma patients in median 11.6 years (first sample) and 3.3 years (repeated sample) before myeloma diagnosis. At first pre-diagnostic blood draw, 12 had low-risk (defined by an immunoglobulin [Ig] G monoclonal [M] spike < 15 g/L and a normal free light-chain ratio) and 30 had MGUS of other risk. MM bone disease was more common in patients with low-risk MGUS at first blood draw (67% vs. 30%, P = 0.041). Median survival since myeloma diagnosis was worse in low-risk than other MGUS at first blood draw (2.3 vs. 7.5 years, P = 0.004). Modest progression was observed between first and repeated blood draw for the majority of low-risk MGUS as 67% remained as low- or low-intermediate-risk MGUS at repeated blood draw. Our study, albeit limited by its small size, indicates that progression from low-risk MGUS is associated with worse MM outcome regardless of MGUS follow-up. Although further investigation is needed, progressing low-risk MGUS could belong to a group of aggressive tumors with progression that is difficult to predict.

Pre-diagnostic levels of sVEGFR2, sTNFR2, sIL-2Rα and sIL-6R are associated with glioma risk: A nested case-control study of repeated samples.

No strong aetiological factors have been established for glioma aside from genetic mutations and variants, ionising radiation and an inverse relationship with asthmas and allergies. Our aim was to investigate the association between pre-diagnostic immune protein levels and glioma risk. We conducted a case-control study nested in the Northern Sweden Health and Disease Study cohort. We analysed 133 glioma cases and 133 control subjects matched by age, sex and date of blood donation. ELISA or Luminex bead-based multiplex assays were used to measure plasma levels of 19 proteins. Conditional logistic regression models were used to estimate the odds ratios and 95% CIs. To further model the protein trajectories over time, the linear mixed-effects models were conducted. We found that the levels of sVEGFR2, sTNFR2, sIL-2Rα and sIL-6R were associated with glioma risk. After adjusting for the time between blood sample collection and glioma diagnosis, the odds ratios were 1.72 (95% CI = 1.01-2.93), 1.48 (95% CI = 1.01-2.16) and 1.90 (95% CI = 1.14-3.17) for sTNFR2, sIL-2Rα and sIL-6R, respectively. The trajectory of sVEGFR2 concentrations over time was different between cases and controls (p-value = 0.031), increasing for cases (0.8% per year) and constant for controls. Our findings suggest these proteins play important roles in gliomagenesis.

Intraindividual Long-term Immune Marker Stability in Plasma Samples Collected in Median 9.4 Years Apart in 304 Adult Cancer-free Individuals.

BACKGROUND: Changes in immune marker levels in the blood could be used to improve the early detection of tumor-associated inflammatory processes. To increase predictiveness and utility in cancer detection, intraindividual long-term stability in cancer-free individuals is critical for biomarker candidates as to facilitate the detection of deviation from the norm. METHODS: We assessed intraindividual long-term stability for 19 immune markers (IL10, IL13, TNFα, CXCL13, MCP-3, MIP-1α, MIP-1ß, fractalkine, VEGF, FGF-2, TGFα, sIL2Rα, sIL6R, sVEGF-R2, sTNF-R1, sTNF-R2, sCD23, sCD27, and sCD30) in 304 cancer-free individuals. Repeated blood samples were collected up to 20 years apart. Intraindividual reproducibility was assessed by calculating intraclass correlation coefficients (ICC) using a linear mixed model. RESULTS: ICCs indicated fair to good reproducibility (ICCs ≥ 0.40 and < 0.75) for 17 of 19 investigated immune markers, including IL10, IL13, TNFα, CXCL13, MCP-3, MIP-1α, MIP-1ß, fractalkine, VEGF, FGF-2, TGFα, sIL2Rα, sIL6R, sTNF-R1, sTNF-R2, sCD27, and sCD30. Reproducibility was strong (ICC ≥ 0.75) for sCD23, while reproducibility was poor (ICC < 0.40) for sVEGF-R2. Using a more stringent criterion for reproducibility (ICC ≥ 0.55), we observed either acceptable or better reproducibility for IL10, IL13, CXCL13, MCP-3, MIP-1α, MIP-1ß, VEGF, FGF-2, sTNF-R1, sCD23, sCD27, and sCD30. CONCLUSIONS: IL10, IL13, CXCL13, MCP-3, MIP-1α, MIP-1ß, VEGF, FGF-2, sTNF-R1, sCD23, sCD27, and sCD30 displayed ICCs consistent with intraindividual long-term stability in cancer-free individuals. IMPACT: Our data support using these markers in prospective longitudinal studies seeking early cancer detection biomarkers.

Breast cancer screening and overdiagnosis.

Overdiagnosis is a harmful consequence of screening which is particularly challenging to estimate. An unbiased setting to measure overdiagnosis in breast cancer screening requires comparative data from a screened and an unscreened cohort for at least 30 years. Such randomised data will not become available, leaving us with observational data over shorter time periods and outcomes of modelling. This collaborative effort of the International Cancer Screening Network quantified the variation in estimated breast cancer overdiagnosis in organised programmes with evaluation of both observed and simulated data, and presented examples of how modelling can provide additional insights. Reliable observational data, analysed with study design accounting for methodological pitfalls, and modelling studies with different approaches, indicate that overdiagnosis accounts for less than 10% of invasive breast cancer cases in a screening target population of women aged 50 to 69. Estimates above this level are likely to derive from inaccuracies in study design. The widely discrepant estimates of overdiagnosis reported from observational data could substantially be reduced by use of a cohort study design with at least 10 years of follow-up after screening stops. In contexts where concomitant opportunistic screening or gradual implementation of screening occurs, and data on valid comparison groups are not readily available, modelling of screening intervention becomes an advantageous option to obtain reliable estimates of breast cancer overdiagnosis.

Early detection of breast cancer rectifies inequality of breast cancer outcomes.

OBJECTIVES: To explain apparent differences among mammography screening services in Sweden using individual data on participation in screening and with breast cancer-specific survival as an outcome. METHODS: We analysed breast cancer survival data from the Swedish Cancer Register on breast cancer cases from nine Swedish counties diagnosed in women eligible for screening. Data were available on 38,278 breast cancers diagnosed and 4312 breast cancer deaths. Survival to death from breast cancer was estimated using the Kaplan-Meier estimate, for all cases in each county, and separately for cases of women participating and not participating in their last invitation to screening. Formal statistical comparisons of survival were made using proportional hazards regression. RESULTS: All counties showed a reduction in the hazard of breast cancer death with participation in screening, but the reductions for individual counties varied substantially, ranging from 51% (95% confidence interval 46-55%) to 81% (95% confidence interval 74-85%). Survival rates in nonparticipating women ranged from 53% (95% confidence interval 40-65%) to 74% (95% confidence interval 72-77%), while the corresponding survival in women participating in screening varied from 80% (95% confidence interval 77-84%) to 86% (95% confidence interval 83-88%), a considerably narrower range. CONCLUSIONS: Differences among counties in the effect of screening on breast cancer outcomes were mainly due to variation in survival in women not participating in screening. Screening conferred similarly high survival rates in all counties. This indicates that the performance of screening services was similar across counties and that detection and treatment of breast cancer in early-stage reduces inequalities in breast cancer outcome.

Precision Science on Incidence and Progression of Early-Detected Small Breast Invasive Cancers by Mammographic Features.

The aim was to evaluate how the inter-screening interval affected the performance of screening by mammographic appearances. This was a Swedish retrospective screening cohort study with information on screening history and mammography features in two periods (1977-1985 and 1996-2010). The pre-clinical incidence and the mean sojourn time (MST) for small breast cancer allowing for sensitivity by mammographic appearances were estimated. The percentage of interval cancer against background incidence (I/E ratio) was used to assess the performance of mammography screening by different inter-screening intervals. The sensitivity-adjusted MSTs (in years) were heterogeneous with mammographic features, being longer for powdery and crushed stone-like calcifications (4.26, (95% CI, 3.50-5.26)) and stellate masses (3.76, (95% CI, 3.15-4.53)) but shorter for circular masses (2.65, (95% CI, 2.06-3.55)) in 1996-2010. The similar trends, albeit longer MSTs, were also noted in 1977-1985. The I/E ratios for the stellate type were 23% and 32% for biennial and triennial screening, respectively. The corresponding figures were 32% and 43% for the circular type and 21% and 29% for powdery and crushed stone-like calcifications, respectively. Mammography-featured progressions of small invasive breast cancer provides a new insight into personalized quality assurance, surveillance, treatment and therapy of early-detected breast cancer.

Mammography screening reduces rates of advanced and fatal breast cancers: Results in 549,091 women.

BACKGROUND: It is of paramount importance to evaluate the impact of participation in organized mammography service screening independently from changes in breast cancer treatment. This can be done by measuring the incidence of fatal breast cancer, which is based on the date of diagnosis and not on the date of death. METHODS: Among 549,091 women, covering approximately 30% of the Swedish screening-eligible population, the authors calculated the incidence rates of 2473 breast cancers that were fatal within 10 years after diagnosis and the incidence rates of 9737 advanced breast cancers. Data regarding each breast cancer diagnosis and the cause and date of death of each breast cancer case were gathered from national Swedish registries. Tumor characteristics were collected from regional cancer centers. Aggregated data concerning invitation and participation were provided by Sectra Medical Systems AB. Incidence rates were analyzed using Poisson regression. RESULTS: Women who participated in mammography screening had a statistically significant 41% reduction in their risk of dying of breast cancer within 10 years (relative risk, 0.59; 95% CI, 0.51-0.68 [P < .001]) and a 25% reduction in the rate of advanced breast cancers (relative risk, 0.75; 95% CI, 0.66-0.84 [P < .001]). CONCLUSIONS: Substantial reductions in the incidence rate of breast cancers that were fatal within 10 years after diagnosis and in the advanced breast cancer rate were found in this contemporaneous comparison of women participating versus those not participating in screening. These benefits appeared to be independent of recent changes in treatment regimens.

The Genetic Architecture of Gliomagenesis-Genetic Risk Variants Linked to Specific Molecular Subtypes.

Genome-wide association studies have identified 25 germline genetic loci that increase the risk of glioma. The somatic tumor molecular alterations, including IDH-mutation status and 1p/19q co-deletion, have been included into the WHO 2016 classification system for glioma. To investigate how the germline genetic risk variants correlate with the somatic molecular subtypes put forward by WHO, we performed a meta-analysis that combined findings from 330 Swedish cases and 876 controls with two other recent studies. In total, 5,103 cases and 10,915 controls were included. Three categories of associations were found. First, variants in TERT and TP53 were associated with increased risk of all glioma subtypes. Second, variants in CDKN2B-AS1, EGFR, and RTEL1 were associated with IDH-wildtype glioma. Third, variants in CCDC26 (the 8q24 locus), C2orf80 (close to IDH), LRIG1, PHLDB1, ETFA, MAML2 and ZBTB16 were associated with IDH-mutant glioma. We therefore propose three etiopathological pathways in gliomagenesis based on germline variants for future guidance of diagnosis and potential functional targets for therapies. Future prospective clinical trials of patients with suspicion of glioma diagnoses, using the genetic variants as biomarkers, are necessary to disentangle how strongly they can predict glioma diagnosis.

Role of monoamine-oxidase-A-gene variation in the development of glioblastoma in males: a case control study.

BACKGROUND: The Mono-amine oxidase-A (MAO-A) enzyme is involved in the degradation and regulation of catecholamines such as serotonin, dopamine, epinephrine and nor-epinephrine. Preclinical studies suggest that this enzyme may contribute to an environment favorable for growth of malignant glioma. The MAO-A gene is located on the X-chromosome and has at least one functional genetic polymorphism. The aim of the present study was to explore possible effects of MAO-A genotype on development of glioblastoma in males. METHODS: Genotypes for 437 glioma cases and 876 population-based controls from the Swedish Glioma International Case-Control study (GICC) were compared. We analyzed the germline DNA using the Illumina Oncoarray. We selected seven single nucleotide polymorphisms (SNPs) located in the MAO-A gene, and imputed genotypes based on data from the 1000 genomes project. We used 1579 male glioblastoma cases and 1875 controls comprising the whole GICC cohort for subsequent validation of findings. RESULTS: The rs144551722 SNP was a significant predictor of development of glioblastoma in males (p-value = 0.0056) but not in females even after correction for multiple testing. We conducted haplotype analysis to confirm an association between MAO-A gene and risk of glioblastoma (p-value = 0.016). We found similar results in the validation sample. CONCLUSIONS: These results suggest the possibility of a role for the MAO-A enzyme and the MAO-A gene in the development of glioblastoma in males.

Imaging Biomarkers as Predictors for Breast Cancer Death.

BACKGROUND: To differentiate the risk of breast cancer death in a longitudinal cohort using imaging biomarkers of tumor extent and biology, specifically, the mammographic appearance, basal phenotype, histologic tumor distribution, and conventional tumor attributes. METHODS: Using a prospective cohort study design, 498 invasive breast cancer patients diagnosed between 1996 and 1998 were used as the test cohort to assess the independent effects of the imaging biomarkers and other predictors on the risk of breast cancer death. External validation was performed with a cohort of 848 patients diagnosed between 2006 and 2010. RESULTS: Mammographic tumor appearance was an independent predictor of risk of breast cancer death (P=0.0003) when conventional tumor attributes and treatment modalities were controlled. The casting type calcifications and architectural distortion were associated with 3.13-fold and 3.19-fold risks of breast cancer death, respectively. The basal phenotype independently conferred a 2.68-fold risk compared with nonbasal phenotype. The observed deaths did not differ significantly from expected deaths in the validation cohort. The application of imaging biomarkers together with other predictors classified twelve categories of risk for breast cancer death. CONCLUSION: Combining imaging biomarkers such as the mammographic appearance of the tumor with the histopathologic distribution and basal phenotype, accurately predicted long-term risk of breast cancer death. The information may be relevant for determining the need for molecular testing, planning treatment, and determining the most appropriate clinical surveillance schedule for breast cancer patients.

The incidence of fatal breast cancer measures the increased effectiveness of therapy in women participating in mammography screening.

BACKGROUND: Women and their health care providers need a reliable answer to this important question: If a woman chooses to participate in regular mammography screening, then how much will this choice improve her chances of avoiding a death from breast cancer compared with women who choose not to participate? METHODS: To answer this question, we used comprehensive registries for population, screening history, breast cancer incidence, and disease-specific death data in a defined population in Dalarna County, Sweden. The annual incidence of breast cancer was calculated along with the annual incidence of breast cancers that were fatal within 10 and within 11 to 20 years of diagnosis among women aged 40 to 69 years who either did or did not participate in mammography screening during a 39-year period (1977-2015). For an additional comparison, corresponding data are presented from 19 years of the prescreening period (1958-1976). All patients received stage-specific therapy according to the latest national guidelines, irrespective of the mode of detection. RESULTS: The benefit for women who chose to participate in an organized breast cancer screening program was a 60% lower risk of dying from breast cancer within 10 years after diagnosis (relative risk, 0.40; 95% confidence interval, 0.34-0.48) and a 47% lower risk of dying from breast cancer within 20 years after diagnosis (relative risk, 0.53; 95% confidence interval, 0.44-0.63) compared with the corresponding risks for nonparticipants. CONCLUSIONS: Although all patients with breast cancer stand to benefit from advances in breast cancer therapy, the current results demonstrate that women who have participated in mammography screening obtain a significantly greater benefit from the therapy available at the time of diagnosis than do those who have not participated.

Overdiagnosis in the population-based organized breast cancer screening program estimated by a non-homogeneous multi-state model: a cohort study using individual data with long-term follow-up.

BACKGROUND: Overdiagnosis, defined as the detection of a cancer that would not become clinically apparent in a woman's lifetime without screening, has become a growing concern. Similar underlying risk of breast cancer in the screened and control groups is a prerequisite for unbiased estimates of overdiagnosis, but a contemporary control group is usually not available in organized screening programs. METHODS: We estimated the frequency of overdiagnosis of breast cancer due to screening in women 50-69 years old by using individual screening data from the population-based organized screening program in Stockholm County 1989-2014. A hidden Markov model with four latent states and three observed states was constructed to estimate the natural progression of breast cancer and the test sensitivity. Piecewise transition rates were used to consider the time-varying transition rates. The expected number of detected non-progressive breast cancer cases was calculated. RESULTS: During the study period, 2,333,153 invitations were sent out; on average, the participation rate in the screening program was 72.7% and the average recall rate was 2.48%. In total, 14,648 invasive breast cancer cases were diagnosed; among the 8305 screen-detected cases, the expected number of non-progressive breast cancer cases was 35.9, which is equivalent to 0.43% (95% confidence interval (CI) 0.10%-2.2%) overdiagnosis. The corresponding estimates for the prevalent and subsequent rounds were 15.6 (0.87%, 95% CI 0.20%-4.3%) and 20.3 (0.31%, 95% CI 0.07%-1.6%), respectively. The likelihood ratio test showed that the non-homogeneous model fitted the data better than an age-homogeneous model (P <0.001). CONCLUSIONS: Our findings suggest that overdiagnosis in the organized biennial mammographic screening for women 50-69 in Stockholm County is a minor phenomenon. The frequency of overdiagnosis in the prevalent screening round was higher than that in subsequent rounds. The non-homogeneous model performed better than the simpler, traditional homogeneous model.

Effect of Mammography Screening on Mortality by Histological Grade.

Background: It has been asserted that mammography screening preferentially benefits those with less aggressive cancers, with lesser or no impact on more rapidly progressing and therefore more life-threatening tumors.Methods: We utilized data from the Swedish Two-County Trial, which randomized 77,080 women ages 40 to 74 to invitation to screening and 55,985 for usual care. We tabulated cancers by histologic grade and then compared mortality from cancers specific to histologic grade between the invited and control group using Poisson regression, with specific interest in the effect on mortality from grade 3 cancers. We used incidence-based mortality from tumors diagnosed within the screening phase of the trial. Finally, we cross-tabulated grade with tumor size and node status, to assess downstaging within tumor grades.Results: There was a major reduction in mortality from grade 3 tumors (RR = 0.65; 95% CI, 0.53-0.80; P < 0.001), and more deaths prevented from grade 3 tumors (n = 95) than grade 1 and 2 tumors combined (n = 48) in the invited group. The proportions of tumors ≥15 mm or larger and node-positive tumors were substantially reduced in the grade 3 tumors in the invited group.Conclusions: The combination of prevention of tumors progressing to grade 3 and detection at smaller sizes and lesser rates of lymph node metastases within grade 3 tumors results in a substantial number of deaths from grade 3 cancers being prevented by invitation to mammographic screening.Impact: Mammography screening prevents deaths from aggressive cancers. Cancer Epidemiol Biomarkers Prev; 27(2); 154-7. ©2017 AACR.

Initiators and promoters for the occurrence of screen-detected breast cancer and the progression to clinically-detected interval breast cancer.

BACKGROUND: The risk factors responsible for breast cancer have been well documented, but the roles of risk factors as initiators, causing the occurrence of screen-detected breast cancer, or promoters, responsible for the progression of the screen-detected to the clinically-detected breast cancer, have been scarcely evaluated. METHODS: We used data from women in a cohort in Kopparberg (Dalarna), Sweden between 1977 and 2010. Conventional risk factors, breast density, and tumor-specific biomarkers are superimposed to the temporal course of the natural history of the disease. RESULTS: The results show that older age at first full-term pregnancy, dense breast, and a family history of breast cancer increased the risk of entering the preclinical screen-detectable phase of breast cancer by 23%, 41%, and 89%, respectively. Overweight/obesity (body mass index ≥25 kg/m2) was a significant initiator (adjusted relative risk [aRR] 1.15; 95% confidence interval [CI], 0.99-1.33), but was inversely associated with the role of promoter (aRR 0.65; 95% CI, 0.51-0.82). Dense breast (aRR 1.46; 95% CI, 1.12-1.91), triple-negative (aRR 2.07; 95% CI, 1.37-3.15), and Ki-67 positivity (aRR 1.66; 95% CI, 1.19-2.30) were statistically significant promoters. When the molecular biomarkers were considered collectively as one classification, the basal-like subtype was the most influential subtype on promoters (aRR 4.24; 95% CI, 2.56-7.02) compared with the Luminal A subtype. DISCUSSION: We ascertained state-dependent covariates of initiators and promoters to classify the risk of the two-step progression of breast cancer. The results of the current study are useful for individually-tailored screening and personalized clinical surveillance of patients with breast cancer that was detected at an early stage.