123 research outputs found
Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials
Background: Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal carcinoma In Situ is safe (E. S. Hwang et al., BMJ Open, 9: e026797, 2019, A. Francis et al., Eur J Cancer. 51: 2296–2303, 2015, Chizuko Kanbayashi et al. The international collaboration of active surveillance trials for low-risk DCIS (LORIS, LORD, COMET, LORETTA), L. E. Elshof et al., Eur J Cancer, 51, 1497–510, 2015). Low-risk is defined as grade I or II DCIS. Because DCIS grade is a major eligibility criteria in these trials, it would be very helpful to assess DCIS grade on mammography, informed by grade assessed on DCIS histopathology in pre-surgery biopsies, since surgery will not be performed on a significant number of patients participating in these trials. Objective: To assess the performance and clinical utility of a convolutional neural network (CNN) in discriminating high-risk (grade III) DCIS and/or Invasive Breast Cancer (IBC) from low-risk (grade I/II) DCIS based on mammographic features. We explored whether the CNN could be used as a decision support tool, from excluding high-risk patients for active surveillance. Methods: In this single centre retrospective study, 464 patients diagnosed with DCIS based on pre-surgery biopsy between 2000 and 2014 were included. The collection of mammography images was partitioned on a patient-level into two subsets, one for training containing 80% of cases (371 cases, 681 images) and 20% (93 cases, 173 images) for testing. A deep learning model based on the U-Net CNN was trained and validated on 681 two-dimensional mammograms. Classification performance was assessed with the Area Under the Curve (AUC) receiver operating characteristic and predictive values on the test set for predicting high risk DCIS-and high-risk DCIS and/ or IBC from low-risk DCIS. Results: When classifying DCIS as high-risk, the deep learning network achieved a Positive Predictive Value (PPV) of 0.40, Negative Predictive Value (NPV) of 0.91 and an AUC of 0.72 on the test dataset. For distinguishing high-risk and/or upstaged DCIS (occult invasive breast cancer) from low-risk DCIS a PPV of 0.80, a NPV of 0.84 and an AUC of 0.76 were achieved. Conclusion: For both scenarios (DCIS grade I/II vs. III, DCIS grade I/II vs. III and/or IBC) AUCs were high, 0.72 and 0.76, respectively, concluding that our convolutional neural network can discriminate low-grade from high-grade DCIS.</p
Genomic patterns resembling BRCA1- and BRCA2-mutated breast cancers predict benefit of intensified carboplatin-based chemotherapy
Introduction: BRCA-mutated breast cancer cells lack the DNA-repair mechanism homologous recombination that is required for error-free DNA double-strand break (DSB) repair. Homologous recombination deficiency (HRD) may cause hypersensitivity to DNA DSB-inducing agents, such as bifunctional alkylating agents and platinum salts. HRD can be caused by BRCA mutations, and by other mechanisms. To identify HRD, studies have focused on triple-negative (TN) breast cancers as these resemble BRCA1-mutated breast cancer closely and might also share this hypersensitivity. However, ways to identify HRD in non-BRCA-mutated, estrogen receptor (ER)-positive breast cancers have remained elusive. The current study provides evidence that genomic patterns resembling BRCA1- or BRCA2- mutated breast cancers can identify breast cancer patients with TN as well as ER-positive, HER2-negative tumors that are sensitive to intensified, DSB-inducing chemotherapy. Methods: Array comparative genomic hybridization (aCGH) was used to classify breast cancers. Patients with tumors with similar aCGH patterns as BRCA1- and/or BRCA2-mutated breast cancers were defined as having a BRCA-like(CGH) status, others as non-BCRA-like(CGH). Stage-III patients (n = 249) had participated in a randomized controlled trial of adjuvant high-dose (HD) cyclophosphamide-thiotepa-carboplatin (CTC) versus 5-fluorouracil-epirubicin-cyclophosphamide (FE90C) chemotherapy. Results: Among patients with BRCA-like(CGH) tumors (81/249, 32%), a significant benefit of HD-CTC compared to FE90C was observed regarding overall survival (adjusted hazard ratio 0.19, 95% CI: 0.08 to 0.48) that was not seen for patients with non-BRCA-like(CGH) tumors (adjusted hazard ratio 0.90, 95% CI: 0.53 to 1.54) (P = 0.004). Half of all BRCA-like(CGH) tumors were ER-positive. Conclusions: Distinct aCGH patterns differentiated between HER2-negative patients with a markedly improved outcome after adjuvant treatment with an intensified DNA-DSB-inducing regimen (BRCA-like(CGH) patients) and those without benefit (non-BRCA-like(CGH) patients)
Effectiveness of medication withdrawal in older fallers: Results from the improving medication prescribing to reduce risk of falls (IMPROveFALL) trial
Objectives: to investigate the effect of withdrawal of fall-risk-increasing-drugs (FRIDs) versus 'care as usual' on reducing falls in community-dwelling older fallers. Design: randomised multicentre trial. Participants: six hundred and twelve older adults who visited an Emergency Department (ED) because of a fall. Interventions: withdrawal of FRIDs. Main Outcomes and Measures: primary outcome was time to the first self-reported fall. Secondary outcomes were time to the second self-reported fall and to falls requiring a general practitioner (GP)-consultation or ED-visit. Intention-to-treat (primary) and a per-protocol (secondary) analysis were conducted. The hazard ratios (HRs) for time-to-fall were calculated using a Cox-regression model. Differences in cumulative incidence of falls were analysed using Poisson regression. Results: during 12 months follow-up, 91 (34%) control and 115 (37%) intervention
Cost-utility of medication withdrawal in older fallers: results from the improving medication prescribing to reduce risk of FALLs (IMPROveFALL) trial
Background: The use of Fall-Risk-Increasing-Drugs (FRIDs) has been associated with increased risk of falls and associated injuries. This study investigates the effect of withdrawal of FRIDs versus 'care as usual' on health-related quality of life (HRQoL), costs, and cost-utility in community-dwelling older fallers. Methods: In a prospective multicenter randomized controlled trial FRIDs assessment combined with FRIDs-withdrawal or modification was compared with 'care as usual' in older persons, who visited the emergency department after experiencing a fall. For the calculation of costs the direct medical costs (intramural and extramural) and indirect costs (travel costs) were collected for a 12 month period. HRQoL was measured at baseline and at 12 months follow-up using the EuroQol-5D and Short Form-12 version 2. The change in EuroQol-5D and Short Form-12 scores over 12 months follow-up within the control and intervention groups was compared using the Wilcoxon Signed Rank test for continuous variables and the McNemar test for dichotomous variables. The change in scores between the control and intervention groups were compared using a two-way analysis of variance. Results: We included 612 older persons who visited an emergency department because of a fall. The mean cost of the FRIDs intervention was €120 per patient. The total fall-related healthcare costs (without the intervention costs) did not differ significantly between the intervention group and the control group (€2204 versus €2285). However, the withdrawal of FRIDs reduced medication costs with a mean of €38 per participant. Furthermore, the control group had a greater decline in EuroQol-5D utility score during the 12-months follow-up than the intervention group (p = 0.02). The change in the Short Form-12 Physical Component Summary and Mental Component Summary scores did not differ significantly between the two groups. Conclusions: Withdrawal of FRID's in older persons who visited an emergency department due to a fall, did not lead to reduction of total health-care costs. However, the withdrawal of FRIDs reduced medication costs with a mean of €38 per participant in combination with less decline in HRQoL is an important result
Quantitative copy number analysis by Multiplex Ligation-dependent Probe Amplification (MLPA) of BRCA1-associated breast cancer regions identifies BRCAness
Our group has previously employed array Comparative Genomic Hybridization (aCGH) to assess the genomic patterns of BRCA1-mutated breast cancers. We have shown that the so-called BRCA1-like(aCGH) profile is also present in about half of all triple-negative sporadic breast cancers and is predictive for benefit from intensified alkylating chemotherapy. As aCGH is a rather complex method, we translated the BRCA1(aCGH) profile to a Multiplex Ligation-dependent Probe Amplification (MLPA) assay, to identify both BRCA1-mutated breast cancers and sporadic cases with a BRCA1-like(aCGH) profile. The most important genomic regions of the original aCGH based classifier (3q22-27, 5q12-14, 6p23-22, 12p13, 12q21-23, 13q31-34) were mapped to a set of 34 MLPA probes. The training set consisted of 39 BRCA1-like(aCGH) breast cancers and 45 non-BRCA1-like(aCGH) breast cancers, which had previously been analyzed by aCGH. The BRCA1-like(aCGH) group consisted of germline BRCA1-mutated cases and sporadic tumours with low BRCA1 gene expression and/or BRCA1 promoter methylation. We trained a shrunken centroids classifier on the training set and validation was performed on an independent test set of 40 BRCA1-like(aCGH) breast cancers and 32 non-BRCA1-like(aCGH) breast cancer tumours. In addition, we validated the set prospectively on 69 new triple-negative tumours. BRCAness in the training set of 84 tumours could accurately be predicted by prediction analysis of microarrays (PAM) (accuracy 94%). Application of this classifier on the independent validation set correctly predicted BRCA-like status of 62 out of 72 breast tumours (86%). Sensitivity and specificity were 85% and 87%, respectively. When the MLPA-test was subsequently applied to 46 breast tumour samples from a randomized clinical trial, the same survival benefit for BRCA1-like tumours associated with intensified alkylating chemotherapy was shown as was previously reported using the aCGH assay. Since the MLPA assay can identify BRCA1-deficient breast cancer patients, this method could be applied both for clinical genetic testing and as a predictor of treatment benefit. BRCA1-like tumours are highly sensitive to chemotherapy with DNA damaging agents, and most likely to poly ADP ribose polymerase (PARP)-inhibitors. The MLPA assay is rapid and robust, can easily be multiplexed, and works well with DNA derived from paraffin-embedded tissue
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Ductal carcinoma in situ: to treat or not to treat, that is the question
Abstract: Ductal carcinoma in situ (DCIS) now represents 20–25% of all ‘breast cancers’ consequent upon detection by population-based breast cancer screening programmes. Currently, all DCIS lesions are treated, and treatment comprises either mastectomy or breast-conserving surgery supplemented with radiotherapy. However, most DCIS lesions remain indolent. Difficulty in discerning harmless lesions from potentially invasive ones can lead to overtreatment of this condition in many patients. To counter overtreatment and to transform clinical practice, a global, comprehensive and multidisciplinary collaboration is required. Here we review the incidence of DCIS, the perception of risk for developing invasive breast cancer, the current treatment options and the known molecular aspects of progression. Further research is needed to gain new insights for improved diagnosis and management of DCIS, and this is integrated in the PRECISION (PREvent ductal Carcinoma In Situ Invasive Overtreatment Now) initiative. This international effort will seek to determine which DCISs require treatment and prevent the consequences of overtreatment on the lives of many women affected by DCIS
Somatic mutations and copy number variations in breast cancers with heterogeneous HER2 amplification
Intratumour heterogeneity fuels carcinogenesis and allows circumventing
specific targeted therapies. HER2 gene amplification is associated with poor
outcome in invasive breast cancer. Heterogeneous HER2 amplification has
been described in 5–41% of breast cancers. Here, we investigated the genetic
differences between HER2-positive and HER2-negative admixed breast cancer components. We performed an in-depth analysis to explore the potential
heterogeneity in the somatic mutational landscape of each individual tumour
component. Formalin-fixed, paraffin-embedded breast cancer tissue of ten
patients with at least one HER2-negative and at least one HER2-positive
component was microdissected. Targeted next-generation sequencing was
performed using a customized 53-gene panel. Somatic mutations and copy
number variations were analysed. Overall, the tumours showed a heterogeneous distribution of 12 deletions, 9 insertions, 32 missense variants and 7
nonsense variants in 26 different genes, which are (likely) pathogenic. Three
splice site alterations were identified. One patient had an EGFR copy number gain restricted to a HER2-negative in situ component, resulting in
EGFR protein overexpression. Two patients had FGFR1 copy number gains
in at least one tumour component. Two patients had an 8q24 gain in at least
one tumour component, resulting in a copy number increase in MYC and
PVT1. One patient had a CCND1 copy number gain restricted to a HER2-
negative tumour comp
Integrating chromosomal aberrations and gene expression profiles to dissect rectal tumorigenesis
<p>Abstract</p> <p>Background</p> <p>Accurate staging of rectal tumors is essential for making the correct treatment choice. In a previous study, we found that loss of 17p, 18q and gain of 8q, 13q and 20q could distinguish adenoma from carcinoma tissue and that gain of 1q was related to lymph node metastasis. In order to find markers for tumor staging, we searched for candidate genes on these specific chromosomes.</p> <p>Methods</p> <p>We performed gene expression microarray analysis on 79 rectal tumors and integrated these data with genomic data from the same sample series. We performed supervised analysis to find candidate genes on affected chromosomes and validated the results with qRT-PCR and immunohistochemistry.</p> <p>Results</p> <p>Integration of gene expression and chromosomal instability data revealed similarity between these two data types. Supervised analysis identified up-regulation of <it>EFNA1 </it>in cases with 1q gain, and <it>EFNA1 </it>expression was correlated with the expression of a target gene (<it>VEGF</it>). The <it>BOP1 </it>gene, involved in ribosome biogenesis and related to chromosomal instability, was over-expressed in cases with 8q gain. <it>SMAD2 </it>was the most down-regulated gene on 18q, and on 20q, <it>STMN3 </it>and <it>TGIF2 </it>were highly up-regulated. Immunohistochemistry for SMAD4 correlated with <it>SMAD2 </it>gene expression and 18q loss.</p> <p>Conclusion</p> <p>On basis of integrative analysis this study identified one well known CRC gene (<it>SMAD2</it>) and several other genes (<it>EFNA1, BOP1, TGIF2 </it>and <it>STMN3</it>) that possibly could be used for rectal cancer characterization.</p
Contralateral breast cancer risk in patients with ductal carcinoma in situ and invasive breast cancer
We aimed to assess contralateral breast cancer (CBC) risk in patients with ductal carcinoma in situ (DCIS) compared with invasive
breast cancer (BC). Women diagnosed with DCIS (N = 28,003) or stage I–III BC (N = 275,836) between 1989 and 2017 were identified
from the nationwide Netherlands Cancer Registry. Cumulative incidences were estimated, accounting for competing risks, and
hazard ratios (HRs) for metachronous invasive CBC. To evaluate effects of adjuvant systemic therapy and screening, separate
analyses were performed for stage I BC without adjuvant systemic therapy and by mode of first BC detection. Multivariable models
including clinico-pathological and treatment data were created to assess CBC risk prediction performance in DCIS patients. The 10-
year cumulative incidence of invasive CBC was 4.8% for DCIS patients (CBC = 1334). Invasive CBC risk was higher in DCIS patients
compared with invasive BC overall (HR = 1.10, 95% confidence interval (CI) = 1.04–1.17), and lower compared with stage I BC
without adjuvant systemic therapy (HR = 0.87; 95% CI = 0.82–0.92). In patients diagnosed ≥2011, the HR for invasive CBC was 1.38
(95% CI = 1.35–1.68) after screen-detected DCIS compared with screen-detected invasive BC, and was 2.14 (95% CI = 1.46–3.13)
when not screen-detected. The C-index was 0.52 (95% CI = 0.50–0.54) for invasive CBC prediction in DCIS patients. In conclusion,
CBC risks are low overall. DCIS patients had a slightly higher risk of invasive CBC compared with invasive BC, likely explained by the
risk-reducing effect of (neo)adjuvant systemic therapy among BC patients. For support of clinical decision making more information
is needed to differentiate CBC risks among DCIS patient
Nationwide oncological networks for resection of colorectal liver metastases in the Netherlands:Differences and postoperative outcomes
INTRODUCTION: Widespread differences in patient demographics and disease burden between hospitals for resection of colorectal liver metastases (CRLM) have been described. In the Netherlands, networks consisting of at least one tertiary referral centre and several regional hospitals have been established to optimize treatment and outcomes. The aim of this study was to assess variation in case-mix, and outcomes between these networks. METHODS: This was a population-based study including all patients who underwent CRLM resection in the Netherlands between 2014 and 2019. Variation in case-mix and outcomes between seven networks covering the whole country was evaluated. Differences in case-mix, expected 30-day major morbidity (Clavien-Dindo ≥3a) and 30-day mortality between networks were assessed. RESULTS: In total 5383 patients were included. Thirty-day major morbidity was 5.7% and 30-day mortality was 1.5%. Significant differences between networks were observed for Charlson Comorbidity Index, ASA 3+, previous liver resection, liver disease, preoperative MRI, preoperative chemotherapy, ≥3 CRLM, diameter of largest CRLM ≥55 mm, major resection, combined resection and ablation, rectal primary tumour, bilobar and extrahepatic disease. Uncorrected 30-day major morbidity ranged between 3.3% and 13.1% for hospitals, 30-day mortality ranged between 0.0% and 4.5%. Uncorrected 30-day major morbidity ranged between 4.4% and 6.0% for networks, 30-day mortality ranged between 0.0% and 2.5%. No negative outliers were observed after case-mix correction. CONCLUSION: Variation in case-mix and outcomes are considerably smaller on a network level as compared to a hospital level. Therefore, auditing is more meaningful at a network level and collaboration of hospitals within networks should be pursued
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