Prevalence and development of hip and knee osteoarthritis according to American College of Rheumatology criteria in the CHECK cohort

_Background:_ We aimed to evaluate the prevalence of hip and knee osteoarthritis (HOA and KOA) according to American College of Rheumatology (ACR) criteria among participants with suspected early symptomatic osteoarthritis (OA) in the CHECK cohort. We also assessed whether participants not fulfilling ACR criteria at baseline develop ACR-defined OA at 2-year and/or 5-year follow up, and which baseline factors are associated with this development. _Methods:_ The CHECK cohort included 1002 subjects with first presentation of knee and/or hip complaints. The primary outcome was onset of HOA and/or KOA according to the ACR criteria, including the clinical classification criteria and the combined clinical and radiographic classification criteria at 2-year and/or 5-year follow up. _Results:_ Of the participants with hip complaints, 63% (n = 370) were classified as having HOA at baseline according to the ACR criteria. Of those not classified with HOA at baseline, 40% developed HOA according to the clinical or combined clinical/radiographic ACR criteria after 2 and/or 5 years. Up to 92% of participants (n = 829) with knee complaints were classified as having KOA at baseline; of those not classified with KOA at baseline, 55% developed KOA according to the clinical ACR criteria or the clinical/radiographic ACR criteria after 2 and/or 5 years. The following factors were associated with development of HOA: morning stiffness (OR 2.39; 95% CI 1.14-4.98), painful internal rotation (OR 2.53; 95% CI 1.23-5.19), hip flexion < 115° (OR 2.33; 95% CI 1.17-4.64) and erythrocyte sedimentation rate (ESR) < 20 mm/h (OR 2.94; 95% CI 1.13-7.61). No variables were associated with development o

Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large-scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose-response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large-scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker-specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.Peer reviewe

Annexin A1 expression in a pooled breast cancer series: Association with tumor subtypes and prognosis

Background: Annexin A1 (ANXA1) is a protein related with the carcinogenesis process and metastasis formation in many tumors. However, little is known about the prognostic value of ANXA1 in breast cancer. The purpose of this study is to evaluate the association between ANXA1 expression, BRCA1/2 germline carriership, specific tumor subtypes and survival in breast cancer patients. Methods: Clinical-pathological information and follow-up data were collected from nine breast cancer studies from the Breast Cancer Association Consortium (BCAC) (n = 5,752) and from one study of familial breast cancer patients with BRCA1/2 mutations (n = 107). ANXA1 expression was scored based on the percentage of immunohistochemical staining in tumor cells. Survival analyses were performed using a multivariable Cox model. Results: The frequency of ANXA1 positive tumors was higher in familial breast cancer patients with BRCA1/2 mutations than in BCAC patients, with 48.6 % versus 12.4 %, respectively; P adj = 1.35; 95 % CI = 1.05-1.73), but the association weakened after 10 years (HRadj = 1.13; 95 % CI = 0.91-1.40). ANXA1 was a significant independent predictor of survival in HER2+ patients (10-years BCSS: HRadj = 1.70; 95 % CI = 1.17-2.45). Conclusions: ANXA1 is overexpressed in familial breast cancer patients with BRCA1/2 mutations and correlated with poor prognosis features: triple negative and poorly differentiated tumors. ANXA1 might be a biomarker candidate for breast cancer survival prediction in high risk groups such as HER2+ cases

Genetic predisposition to ductal carcinoma in situ of the breast

Background: Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer. It is often associated with invasive ductal carcinoma (IDC), and is considered to be a non-obligate precursor of IDC. It is not clear to what extent these two forms of cancer share low-risk susceptibility loci, or whether there are differences in the strength of association for shared loci. Methods: To identify genetic polymorphisms that predispose to DCIS, we pooled data from 38 studies comprising 5,067 cases of DCIS, 24,584 cases of IDC and 37,467 controls, all genotyped using the iCOGS chip. Results: Most (67 %) of the 76 known breast cancer predisposition loci showed an association with DCIS in the same direction as previously reported for invasive breast cancer. Case-only analysis showed no evidence for differences between associations for IDC and DCIS after considering multiple testing. Analysis by estrogen receptor (ER) status confirmed that loci associated with ER positive IDC were also associated with ER positive DCIS. Analysis of DCIS by grade suggested that two independent SNPs at 11q13.3 near CCND1 were specific to low/intermediate grade DCIS (rs75915166, rs554219). These associations with grade remained after adjusting for ER status and were also found in IDC. We found no novel DCIS-specific loci at a genome wide significance level of P < 5.0x10-8. Conclusion: In conclusion, this study provides the strongest evidence to date of a shared genetic susceptibility for IDC and DCIS. Studies with larger numbers of DCIS are needed to determine if IDC or DCIS specific loci exist

Genetic predisposition to ductal carcinoma in situ of the breast.

BACKGROUND: Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer. It is often associated with invasive ductal carcinoma (IDC), and is considered to be a non-obligate precursor of IDC. It is not clear to what extent these two forms of cancer share low-risk susceptibility loci, or whether there are differences in the strength of association for shared loci. METHODS: To identify genetic polymorphisms that predispose to DCIS, we pooled data from 38 studies comprising 5,067 cases of DCIS, 24,584 cases of IDC and 37,467 controls, all genotyped using the iCOGS chip. RESULTS: Most (67 %) of the 76 known breast cancer predisposition loci showed an association with DCIS in the same direction as previously reported for invasive breast cancer. Case-only analysis showed no evidence for differences between associations for IDC and DCIS after considering multiple testing. Analysis by estrogen receptor (ER) status confirmed that loci associated with ER positive IDC were also associated with ER positive DCIS. Analysis of DCIS by grade suggested that two independent SNPs at 11q13.3 near CCND1 were specific to low/intermediate grade DCIS (rs75915166, rs554219). These associations with grade remained after adjusting for ER status and were also found in IDC. We found no novel DCIS-specific loci at a genome wide significance level of P < 5.0x10(-8). CONCLUSION: In conclusion, this study provides the strongest evidence to date of a shared genetic susceptibility for IDC and DCIS. Studies with larger numbers of DCIS are needed to determine if IDC or DCIS specific loci exist

Residual cancer burden after neoadjuvant chemotherapy and long-term survival outcomes in breast cancer : a multicentre pooled analysis of 5161 patients

Background Previous studies have independently validated the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. We used results from several independent cohorts in a pooled patient-level analysis to evaluate the relationship of RCB with long-term prognosis across different phenotypic subtypes of breast cancer, to assess generalisability in a broad range of practice settings. Methods In this pooled analysis, 12 institutes and trials in Europe and the USA were identified by personal communications with site investigators. We obtained participant-level RCB results, and data on clinical and pathological stage, tumour subtype and grade, and treatment and follow-up in November, 2019, from patients (aged ≥18 years) with primary stage I–III breast cancer treated with neoadjuvant chemotherapy followed by surgery. We assessed the association between the continuous RCB score and the primary study outcome, event-free survival, using mixed-effects Cox models with the incorporation of random RCB and cohort effects to account for between-study heterogeneity, and stratification to account for differences in baseline hazard across cancer subtypes defined by hormone receptor status and HER2 status. The association was further evaluated within each breast cancer subtype in multivariable analyses incorporating random RCB and cohort effects and adjustments for age and pretreatment clinical T category, nodal status, and tumour grade. Kaplan-Meier estimates of event-free survival at 3, 5, and 10 years were computed for each RCB class within each subtype. Findings We analysed participant-level data from 5161 patients treated with neoadjuvant chemotherapy between Sept 12, 1994, and Feb 11, 2019. Median age was 49 years (IQR 20–80). 1164 event-free survival events occurred during follow-up (median follow-up 56 months [IQR 0–186]). RCB score was prognostic within each breast cancer subtype, with higher RCB score significantly associated with worse event-free survival. The univariable hazard ratio (HR) associated with one unit increase in RCB ranged from 1·55 (95% CI 1·41–1·71) for hormone receptor-positive, HER2-negative patients to 2·16 (1·79–2·61) for the hormone receptor-negative, HER2-positive group (with or without HER2-targeted therapy; p<0·0001 for all subtypes). RCB score remained prognostic for event-free survival in multivariable models adjusted for age, grade, T category, and nodal status at baseline: the adjusted HR ranged from 1·52 (1·36–1·69) in the hormone receptor-positive, HER2-negative group to 2·09 (1·73–2·53) in the hormone receptor-negative, HER2-positive group (p<0·0001 for all subtypes). Interpretation RCB score and class were independently prognostic in all subtypes of breast cancer, and generalisable to multiple practice settings. Although variability in hormone receptor subtype definitions and treatment across patients are likely to affect prognostic performance, the association we observed between RCB and a patient's residual risk suggests that prospective evaluation of RCB could be considered to become part of standard pathology reporting after neoadjuvant therapy

Feeding soy protein isolate and oils rich in omega-3 polyunsaturated fatty acids affected mineral balance, but not bone in a rat model of autosomal recessive polycystic kidney disease

Background: Polycystic kidney disease (PKD), a genetic disorder characterized by multiple cysts and renal failure at an early age. In children, kidney disease is often accompanied by disordered mineral metabolism, failure to achieve peak bone mass, and reduced adult height. Optimizing bone health during the growth stage may preserve against bone loss associated with early renal dysfunction in PKD. Dietary soy protein and omega-3 polyunsaturated fatty acid (n-3 PUFA) have been reported to ameliorate PKD and to promote bone health. The study objective was to determine the bone effects of feeding soy protein and/or n-3 PUFAs in a rat model of PKD.Methods: Weanling female PCK rats (n = 12/group) were randomly assigned to casein + corn oil (Casein + CO), casein + soybean oil (Casein + SO), soy protein isolate + soybean oil (SPI + SO) or soy protein isolate + 1:1 soybean oil:salmon oil blend (SPI + SB) for 12 weeks.Results: Rats fed SPI + SO diet had shorter (P = 0.001) femur length than casein-fed rats. Rats fed SPI + SO and SPI + SB diet had higher (P = 0.04) calcium (Ca) and phosphorus (P) retention. However, there were no significant differences in femur and tibial Ca, P or bone mass between diet groups. There were also no significant difference in bone microarchitecture measured by micro-computed tomography or bone strength determined by three-point bending test between diet groups.Conclusions: Early diet management of PKD using SPI and/or n-3 PUFAs influenced bone longitudinal growth and mineral balance, but neither worsened nor enhanced bone mineralization, microarchitecture or strength.Peer reviewedNutritional Science

Annexin A1 expression in a pooled breast cancer series : association with tumor subtypes and prognosis

Background: Annexin A1 (ANXA1) is a protein related with the carcinogenesis process and metastasis formation in many tumors. However, little is known about the prognostic value of ANXA1 in breast cancer. The purpose of this study is to evaluate the association between ANXA1 expression, BRCA1/2 germline carriership, specific tumor subtypes and survival in breast cancer patients. Methods: Clinical-pathological information and follow-up data were collected from nine breast cancer studies from the Breast Cancer Association Consortium (BCAC) (n = 5,752) and from one study of familial breast cancer patients with BRCA1/2 mutations (n = 107). ANXA1 expression was scored based on the percentage of immunohistochemical staining in tumor cells. Survival analyses were performed using a multivariable Cox model. Results: The frequency of ANXA1 positive tumors was higher in familial breast cancer patients with BRCA1/2 mutations than in BCAC patients, with 48.6 % versus 12.4 %, respectively; P <0.0001. ANXA1 was also highly expressed in BCAC tumors that were poorly differentiated, triple negative, EGFR-CK5/6 positive or had developed in patients at a young age. In the first 5 years of follow-up, patients with ANXA1 positive tumors had a worse breast cancer-specific survival (BCSS) than ANXA1 negative (HRadj = 1.35; 95 % CI = 1.05-1.73), but the association weakened after 10 years (HRadj = 1.13; 95 % CI = 0.91-1.40). ANXA1 was a significant independent predictor of survival in HER2+ patients (10-years BCSS: HRadj = 1.70; 95 % CI = 1.17-2.45). Conclusions: ANXA1 is overexpressed in familial breast cancer patients with BRCA1/2 mutations and correlated with poor prognosis features: triple negative and poorly differentiated tumors. ANXA1 might be a biomarker candidate for breast cancer survival prediction in high risk groups such as HER2+ cases.Peer reviewe

Subtyping of Breast Cancer by Immunohistochemistry to Investigate a Relationship between Subtype and Short and Long Term Survival: A Collaborative Analysis of Data for 10,159 Cases from 12 Studies

Peer reviewe