Collateral damage: the impact on outcomes from cancer surgery of the COVID-19 pandemic.

BACKGROUND: Cancer diagnostics and surgery have been disrupted by the response of health care services to the coronavirus disease 2019 (COVID-19) pandemic. Progression of cancers during delay will impact on patients' long-term survival. PATIENTS AND METHODS: We generated per-day hazard ratios of cancer progression from observational studies and applied these to age-specific, stage-specific cancer survival for England 2013-2017. We modelled per-patient delay of 3 and 6 months and periods of disruption of 1 and 2 years. Using health care resource costing, we contextualise attributable lives saved and life-years gained (LYGs) from cancer surgery to equivalent volumes of COVID-19 hospitalisations. RESULTS: Per year, 94 912 resections for major cancers result in 80 406 long-term survivors and 1 717 051 LYGs. Per-patient delay of 3/6 months would cause attributable death of 4755/10 760 of these individuals with loss of 92 214/208 275 life-years, respectively. For cancer surgery, average LYGs per patient are 18.1 under standard conditions and 17.1/15.9 with a delay of 3/6 months (an average loss of 0.97/2.19 LYGs per patient), respectively. Taking into account health care resource units (HCRUs), surgery results on average per patient in 2.25 resource-adjusted life-years gained (RALYGs) under standard conditions and 2.12/1.97 RALYGs following delay of 3/6 months. For 94 912 hospital COVID-19 admissions, there are 482 022 LYGs requiring 1 052 949 HCRUs. Hospitalisation of community-acquired COVID-19 patients yields on average per patient 5.08 LYG and 0.46 RALYGs. CONCLUSIONS: Modest delays in surgery for cancer incur significant impact on survival. Delay of 3/6 months in surgery for incident cancers would mitigate 19%/43% of LYGs, respectively, by hospitalisation of an equivalent volume of admissions for community-acquired COVID-19. This rises to 26%/59%, respectively, when considering RALYGs. To avoid a downstream public health crisis of avoidable cancer deaths, cancer diagnostic and surgical pathways must be maintained at normal throughput, with rapid attention to any backlog already accrued.

Lymphocyte density determined by computational pathology validated as a predictor of response to neoadjuvant chemotherapy in breast cancer: secondary analysis of the ARTemis trial.

BACKGROUND: We have previously shown lymphocyte density, measured using computational pathology, is associated with pathological complete response (pCR) in breast cancer. The clinical validity of this finding in independent studies, among patients receiving different chemotherapy, is unknown. PATIENTS AND METHODS: The ARTemis trial randomly assigned 800 women with early stage breast cancer between May 2009 and January 2013 to three cycles of docetaxel, followed by three cycles of fluorouracil, epirubicin and cyclophosphamide once every 21 days with or without four cycles of bevacizumab. The primary endpoint was pCR (absence of invasive cancer in the breast and lymph nodes). We quantified lymphocyte density within haematoxylin and eosin (H&E) whole slide images using our previously described computational pathology approach: for every detected lymphocyte the average distance to the nearest 50 lymphocytes was calculated and the density derived from this statistic. We analyzed both pre-treatment biopsies and post-treatment surgical samples of the tumour bed. RESULTS: Of the 781 patients originally included in the primary endpoint analysis of the trial, 609 (78%) were included for baseline lymphocyte density analyses and a subset of 383 (49% of 781) for analyses of change in lymphocyte density. The main reason for loss of patients was the availability of digitized whole slide images. Pre-treatment lymphocyte density modelled as a continuous variable was associated with pCR on univariate analysis (odds ratio [OR], 2.92; 95% CI, 1.78-4.85; P < 0.001) and after adjustment for clinical covariates (OR, 2.13; 95% CI, 1.24-3.67; P = 0.006). Increased pre- to post-treatment lymphocyte density showed an independent inverse association with pCR (adjusted OR, 0.1; 95% CI, 0.033-0.31; P < 0.001). CONCLUSIONS: Lymphocyte density in pre-treatment biopsies was validated as an independent predictor of pCR in breast cancer. Computational pathology is emerging as a viable and objective means of identifying predictive biomarkers for cancer patients. CLINICALTRIALS.GOV: NCT01093235.

An evaluation of the prognostic model PREDICT using the POSH cohort of women aged ⩽40 years at breast cancer diagnosis.

BACKGROUND: Breast cancer is the most common cancer in younger women (aged ⩽40 years) in the United Kingdom. PREDICT (http://www.predict.nhs.uk) is an online prognostic tool developed to help determine the best available treatment and outcome for early breast cancer. This study was conducted to establish how well PREDICT performs in estimating survival in a large cohort of younger women recruited to the UK POSH study. METHODS: The POSH cohort includes data from 3000 women aged ⩽40 years at breast cancer diagnosis. Study end points were overall and breast cancer-specific survival at 5, 8, and 10 years. Evaluation of PREDICT included model discrimination and comparison of the number of predicted versus observed events. RESULTS: PREDICT provided accurate long-term (8- and 10-year) survival estimates for younger women. Five-year estimates were less accurate, with the tool overestimating survival by 25% overall, and by 56% for patients with oestrogen receptor (ER)-positive tumours. PREDICT underestimated survival at 5 years among patients with ER-negative tumours. CONCLUSIONS: PREDICT is a useful tool for providing reliable long-term (10-year) survival estimates for younger patients. However, for more accurate short-term estimates, the model requires further calibration using more data from young onset cases. Short-term prediction may be most relevant for the increasing number of women considering risk-reducing bilateral mastectomy.

PD-L1 protein expression in breast cancer is rare, enriched in basal-like tumours and associated with infiltrating lymphocytes.

BACKGROUND: Expression of programmed death ligand 1 (PD-L1) in solid tumours has been shown to predict whether patients are likely to respond to anti-PD-L1 therapies. To estimate the therapeutic potential of PD-L1 inhibition in breast cancer, we evaluated the prevalence and significance of PD-L1 protein expression in a large collection of breast tumours. PATIENTS AND METHODS: Correlations between CD274 (PD-L1) copy number, transcript and protein levels were evaluated in tumours from 418 patients recruited to the METABRIC genomic study. Immunohistochemistry was used to detect PD-L1 protein in breast tumours in tissue microarrays from 5763 patients recruited to the SEARCH population-based study (N = 4079) and the NEAT randomised, controlled trial (N = 1684). RESULTS: PD-L1 protein data was available for 3916 of the possible 5763 tumours from the SEARCH and NEAT studies. PD-L1 expression by immune cells was observed in 6% (235/3916) of tumours and expression by tumour cells was observed in just 1.7% (66/3916). PD-L1 was most frequently expressed in basal-like tumours. This was observed both where tumours were subtyped by combined copy number and expression profiling [39% (17/44) of IntClust 10 i.e. basal-like tumours were PD-L1 immune cell positive; P < 0.001] and where a surrogate IHC-based classifier was used [19% (56/302) of basal-like tumours were PD-L1 immune cell positive; P < 0.001]. Moreover, CD274 (PD-L1) amplification was observed in five tumours of which four were IntClust 10. Expression of PD-L1 by either tumour cells or infiltrating immune cells was positively correlated with infiltration by both cytotoxic and regulatory T cells (P < 0.001). There was a nominally significant association between PD-L1 and improved disease-specific survival (hazard ratio 0.53, 95% confidence interval 0.26-1.07; P = 0.08) in ER-negative disease. CONCLUSIONS: Expression of PD-L1 is rare in breast cancer, markedly enriched in basal-like tumours and is correlated with infiltrating lymphocytes. PD-L1 inhibition may benefit the 19% of patients with basal-like tumours in which the protein is expressed. NEAT CLINICALTRIALSGOV: NCT00003577.

Evidence for a time-dependent association between FOLR1 expression and survival from ovarian carcinoma: implications for clinical testing. An Ovarian Tumour Tissue Analysis consortium study.

BACKGROUND: Folate receptor 1 (FOLR1) is expressed in the majority of ovarian carcinomas (OvCa), making it an attractive target for therapy. However, clinical trials testing anti-FOLR1 therapies in OvCa show mixed results and require better understanding of the prognostic relevance of FOLR1 expression. We conducted a large study evaluating FOLR1 expression with survival in different histological types of OvCa. METHODS: Tissue microarrays composed of tumour samples from 2801 patients in the Ovarian Tumour Tissue Analysis (OTTA) consortium were assessed for FOLR1 expression by centralised immunohistochemistry. We estimated associations for overall (OS) and progression-free (PFS) survival using adjusted Cox regression models. High-grade serous ovarian carcinomas (HGSC) from The Cancer Genome Atlas (TCGA) were evaluated independently for association between FOLR1 mRNA upregulation and survival. RESULTS: FOLR1 expression ranged from 76% in HGSC to 11% in mucinous carcinomas in OTTA. For HGSC, the association between FOLR1 expression and OS changed significantly during the years following diagnosis in OTTA (Pinteraction=0.01, N=1422) and TCGA (Pinteraction=0.01, N=485). In OTTA, particularly for FIGO stage I/II tumours, patients with FOLR1-positive HGSC showed increased OS during the first 2 years only (hazard ratio=0.44, 95% confidence interval=0.20-0.96) and patients with FOLR1-positive clear cell carcinomas (CCC) showed decreased PFS independent of follow-up time (HR=1.89, 95% CI=1.10-3.25, N=259). In TCGA, FOLR1 mRNA upregulation in HGSC was also associated with increased OS during the first 2 years following diagnosis irrespective of tumour stage (HR: 0.48, 95% CI: 0.25-0.94). CONCLUSIONS: FOLR1-positive HGSC tumours were associated with an increased OS in the first 2 years following diagnosis. Patients with FOLR1-negative, poor prognosis HGSC would be unlikely to benefit from anti-FOLR1 therapies. In contrast, a decreased PFS interval was observed for FOLR1-positive CCC. The clinical efficacy of FOLR1-targeted interventions should therefore be evaluated according to histology, stage and time following diagnosis.

Association between CD8+ T-cell infiltration and breast cancer survival in 12,439 patients.

BACKGROUND: T-cell infiltration in estrogen receptor (ER)-negative breast tumours has been associated with longer survival. To investigate this association and the potential of tumour T-cell infiltration as a prognostic and predictive marker, we have conducted the largest study of T cells in breast cancer to date. PATIENTS AND METHODS: Four studies totalling 12 439 patients were used for this work. Cytotoxic (CD8+) and regulatory (forkhead box protein 3, FOXP3+) T cells were quantified using immunohistochemistry (IHC). IHC for CD8 was conducted using available material from all four studies (8978 samples) and for FOXP3 from three studies (5239 samples)-multiple imputation was used to resolve missing data from the remaining patients. Cox regression was used to test for associations with breast cancer-specific survival. RESULTS: In ER-negative tumours [triple-negative breast cancer and human epidermal growth factor receptor 2 (human epidermal growth factor receptor 2 (HER2) positive)], presence of CD8+ T cells within the tumour was associated with a 28% [95% confidence interval (CI) 16% to 38%] reduction in the hazard of breast cancer-specific mortality, and CD8+ T cells within the stroma with a 21% (95% CI 7% to 33%) reduction in hazard. In ER-positive HER2-positive tumours, CD8+ T cells within the tumour were associated with a 27% (95% CI 4% to 44%) reduction in hazard. In ER-negative disease, there was evidence for greater benefit from anthracyclines in the National Epirubicin Adjuvant Trial in patients with CD8+ tumours [hazard ratio (HR) = 0.54; 95% CI 0.37-0.79] versus CD8-negative tumours (HR = 0.87; 95% CI 0.55-1.38). The difference in effect between these subgroups was significant when limited to cases with complete data (P heterogeneity = 0.04) and approached significance in imputed data (P heterogeneity = 0.1). CONCLUSIONS: The presence of CD8+ T cells in breast cancer is associated with a significant reduction in the relative risk of death from disease in both the ER-negative [supplementary Figure S1, available at Annals of Oncology online] and the ER-positive HER2-positive subtypes. Tumour lymphocytic infiltration may improve risk stratification in breast cancer patients classified into these subtypes. NEAT ClinicalTrials.gov: NCT00003577.

Implementing risk-stratified screening for common cancers: a review of potential ethical, legal and social issues.

BACKGROUND: The identification of common genetic variants associated with common cancers including breast, prostate and ovarian cancers would allow population stratification by genotype to effectively target screening and treatment. As scientific, clinical and economic evidence mounts there will be increasing pressure for risk-stratified screening programmes to be implemented. METHODS: This paper reviews some of the main ethical, legal and social issues (ELSI) raised by the introduction of genotyping into risk-stratified screening programmes, in terms of Beauchamp and Childress's four principles of biomedical ethics--respect for autonomy, non-maleficence, beneficence and justice. Two alternative approaches to data collection, storage, communication and consent are used to exemplify the ELSI issues that are likely to be raised. RESULTS: Ultimately, the provision of risk-stratified screening using genotyping raises fundamental questions about respective roles of individuals, healthcare providers and the state in organizing or mandating such programmes, and the principles, which underpin their provision, particularly the requirement for distributive justice. CONCLUSIONS: The scope and breadth of these issues suggest that ELSI relating to risk-stratified screening will become increasingly important for policy-makers, healthcare professionals and a wide diversity of stakeholders.

Astronomical algorithms for automated analysis of tissue protein expression in breast cancer.

BACKGROUND: High-throughput evaluation of tissue biomarkers in oncology has been greatly accelerated by the widespread use of tissue microarrays (TMAs) and immunohistochemistry. Although TMAs have the potential to facilitate protein expression profiling on a scale to rival experiments of tumour transcriptomes, the bottleneck and imprecision of manually scoring TMAs has impeded progress. METHODS: We report image analysis algorithms adapted from astronomy for the precise automated analysis of IHC in all subcellular compartments. The power of this technique is demonstrated using over 2000 breast tumours and comparing quantitative automated scores against manual assessment by pathologists. RESULTS: All continuous automated scores showed good correlation with their corresponding ordinal manual scores. For oestrogen receptor (ER), the correlation was 0.82, P<0.0001, for BCL2 0.72, P<0.0001 and for HER2 0.62, P<0.0001. Automated scores showed excellent concordance with manual scores for the unsupervised assignment of cases to 'positive' or 'negative' categories with agreement rates of up to 96%. CONCLUSION: The adaptation of astronomical algorithms coupled with their application to large annotated study cohorts, constitutes a powerful tool for the realisation of the enormous potential of digital pathology.

Public health genomics and personalized prevention: lessons from the COGS project.

Using the principles of public health genomics, we examined the opportunities and challenges of implementing personalized prevention programmes for cancer at the population level. Our model-based estimates indicate that polygenic risk stratification can potentially improve the effectiveness and cost-effectiveness of screening programmes. However, compared with 'one-size-fits-all' screening programmes, personalized screening adds further layers of complexity to the organization of screening services and raises ethical, legal and social challenges. Before polygenic inheritance is translated into population screening strategy, evidence from empirical research and engagement with and education of the public and the health professionals are needed.

A common variant in BRCA2 is associated with both breast cancer risk and prenatal viability.

Inherited mutations in the gene BRCA2 predispose carriers to early onset breast cancer, but such mutations account for fewer than 2% of all cases in East Anglia. It is likely that low penetrance alleles explain the greater part of inherited susceptibility to breast cancer; polymorphic variants in strongly predisposing genes, such as BRCA2, are candidates for this role. BRCA2 is thought to be involved in DNA double strand break-repair. Few mice in which Brca2 is truncated survive to birth; of those that do, most are male, smaller than their normal littermates and have high cancer incidence. Here we show that a common human polymorphism (N372H) in exon 10 of BRCA2 confers an increased risk of breast cancer: the HH homozygotes have a 1.31-fold (95% CI, 1.07-1.61) greater risk than the NN group. Moreover, in normal female controls of all ages there is a significant deficiency of homozygotes compared with that expected from Hardy-Weinberg equilibrium, whereas in males there is an excess of homozygotes: the HH group has an estimated fitness of 0.82 in females and 1.38 in males. Therefore, this variant of BRCA2 appears also to affect fetal survival in a sex-dependent manner.

Aurora kinase A outperforms Ki67 as a prognostic marker in ER-positive breast cancer.

BACKGROUND: Proliferation has emerged as a major prognostic factor in luminal breast cancer. The immunohistochemical (IHC) proliferation marker Ki67 has been most extensively investigated but has not gained widespread clinical acceptance. METHODS: We have conducted a head-to-head comparison of a panel of proliferation markers, including Ki67. Our aim was to establish the marker of the greatest prognostic utility. Tumour samples from 3093 women with breast cancer were constructed as tissue microarrays. We used IHC to detect expression of mini-chromosome maintenance protein 2, Ki67, aurora kinase A (AURKA), polo-like kinase 1, geminin and phospho-histone H3. We used a Cox proportional-hazards model to investigate the association with 10-year breast cancer-specific survival (BCSS). Missing values were resolved using multiple imputation. RESULTS: The prognostic significance of proliferation was limited to oestrogen receptor (ER)-positive breast cancer. Aurora kinase A emerged as the marker of the greatest prognostic significance in a multivariate model adjusted for the standard clinical and molecular covariates (hazard ratio 1.3; 95% confidence interval 1.1-1.5; P=0.005), outperforming all other markers including Ki67. CONCLUSION: Aurora kinase A outperforms other proliferation markers as an independent predictor of BCSS in ER-positive breast cancer. It has the potential for use in routine clinical practice.

Adjuvant epirubicin followed by cyclophosphamide, methotrexate and fluorouracil (CMF) vs CMF in early breast cancer: results with over 7 years median follow-up from the randomised phase III NEAT/BR9601 trials.

BACKGROUND: The National Epirubicin Adjuvant Trial (NEAT) and BR9601 trials tested the benefit of epirubicin when added to cyclophosphamide, methotrexate and 5-fluorouracil (E-CMF) compared with standard CMF in adjuvant chemotherapy for women with early breast cancer. This report details longer follow-up with interesting additional time-dependent analyses. METHODS: National Epirubicin Adjuvant Trial used epirubicin (E) 3-weekly for four cycles followed by classical (c) CMF for four cycles (E-CMF) compared with cCMF for six cycles. BR9601 used E 3-weekly for four cycles followed by CMF 3-weekly for four cycles, compared with CMF 3-weekly for eight cycles. RESULTS: In all, 2391 eligible patients were randomised and with a median 7.4-year follow-up, E-CMF confirmed a significant benefit over CMF in both relapse-free survival (RFS) (78% vs 71% 5 years RFS, respectively, hazard ratio (HR)=0.75 (95% CI: 0.65-0.86), P<0.0001) and overall survival (OS) (84% vs 78% 5 years OS, respectively, HR=0.76 (95% CI: 0.65-0.89), P=0.0007). Interaction of treatment effect and prognostic factors was demonstrated for duplication of chromosome 17 centromeric enumeration (Ch17CEP) as previously reported. Poor prognostic factors at diagnosis (ER and PR negative and HER2 positive) showed time-dependent annual hazard rates for RFS and OS. In univariate analysis, these factors demonstrated more favourable HRs for RFS after 5 years. Treatment effects also suggested a differential benefit for E-CMF within the first 5 years for poor prognosis tumours. CONCLUSION: Longer follow-up has confirmed E-CMF as significantly superior to CMF for all patients. Ch17CEP duplication was the only biomarker that demonstrated significant treatment interaction. Standard poor prognostic factors at diagnosis were time-dependent, and after 5 years disease-free, poor prognosis patients demonstrated favourable HRs for survival.

PREDICT Plus: development and validation of a prognostic model for early breast cancer that includes HER2.

BACKGROUND: Predict (www.predict.nhs.uk) is an online, breast cancer prognostication and treatment benefit tool. The aim of this study was to incorporate the prognostic effect of HER2 status in a new version (Predict+), and to compare its performance with the original Predict and Adjuvant!. METHODS: The prognostic effect of HER2 status was based on an analysis of data from 10 179 breast cancer patients from 14 studies in the Breast Cancer Association Consortium. The hazard ratio estimates were incorporated into Predict. The validation study was based on 1653 patients with early-stage invasive breast cancer identified from the British Columbia Breast Cancer Outcomes Unit. Predicted overall survival (OS) and breast cancer-specific survival (BCSS) for Predict+, Predict and Adjuvant! were compared with observed outcomes. RESULTS: All three models performed well for both OS and BCSS. Both Predict models provided better BCSS estimates than Adjuvant!. In the subset of patients with HER2-positive tumours, Predict+ performed substantially better than the other two models for both OS and BCSS. CONCLUSION: Predict+ is the first clinical breast cancer prognostication tool that includes tumour HER2 status. Use of the model might lead to more accurate absolute treatment benefit predictions for individual patients.

Meta-analysis of the association between emphysematous change on thoracic computerized tomography scan and recurrent pneumothorax.

OBJECTIVES: At least a third of patients go on to suffer a recurrence following a first spontaneous pneumothorax. Surgical intervention reduces the risk of recurrence and has been advocated as a primary treatment for pneumothorax. But surgery exposes patients to the risks of anaesthesia and in some cases can cause chronic pain. Risk stratification of patients to identify those most at risk of recurrence would help direct the most appropriate patients to early intervention. Many studies have addressed the role of thoracic computerized tomography (CT) in identifying those individuals at increased risk of recurrence, but a consensus is lacking. AIM: Our objective was to clarify whether CT provides valuable prognostic information for recurrent pneumothorax. DESIGN: Meta-analysis. METHODS: We conducted an exhaustive search of the literature for thoracic CT imaging and pneumothorax, and then performed a meta-analysis using a random effects model to estimate the common odds ratio and standard error. RESULTS: Here, we show by meta-analysis of data from 2475 individuals that emphysematous change on CT scan is associated with a significant increased odds ratio for recurrent pneumothorax ipsilateral to the radiological abnormality (odds ratio 2.49, 95% confidence interval 1.51-4.13). CONCLUSIONS: The association holds true for primary spontaneous pneumothorax when considering emphysematous changes including blebs and bullae. Features, such as bullae at the azygoesophageal recess or increased Goddard score similarly predicted recurrent secondary pneumothorax, as shown by subgroup analysis. Our meta-analysis suggests that CT scanning has value in risk stratifying patients considering surgery for pneumothorax.

Patient and tumour characteristics, management, and age-specific survival in women with breast cancer in the East of England.

BACKGROUND: Breast cancer relative survival (BCRS), which compares the observed survival of women with breast cancer with the expected survival of women for the whole population of the same age, time period, and geographical region, tends to be poorer in older women, but the reasons for this are not clear. We examined the influence of patient and tumour characteristics, and treatment on BCRS to see whether these could explain the age-specific effect. METHODS: Data for 14,048 female breast cancer patients diagnosed from 1999 to 2007, aged 50 years or over were obtained from the Eastern Cancer Registration and Information Centre. We estimated relative 5- and 10-year survival for patients in four age groups (50-69, 70-74, 75-79, and 80+ years). We also modelled relative excess mortality (REM) rate using Poisson regression adjusting for patient characteristics and treatment. The REMs derived from these models quantify the extent to which the hazard of death differs from the hazard in the reference category, after taking into account the background risk of death in the general population. We compared the results with those obtained for breast cancer-specific mortality, analysed using multivariate Cox regression. RESULTS: Median follow-up time was 4.7 years. Relative 5-year survival was 89, 81, 76, and 70% for patients aged 50-69, 70-74, 75-79, and 80+ years, respectively. Corresponding relative 10-year survival was 84, 77, 67, and 66%. Unadjusted REM was 1.93, 2.74, and 3.88 for patients aged 70-74, 75-79, and 80+ years, respectively, (50-69 years as reference). The equivalent hazard ratios from the Cox model were 1.88, 2.45, and 3.81. These were attenuated after adjusting for confounders (REM - 1.49, 1.36, and 1.23; Cox - 1.47, 1.50, and 1.76). CONCLUSION: We confirmed poorer BCRS in older women in our region. This was partially explained by known prognostic factors. Further research is needed to determine whether biological differences or suboptimal management can explain the residual excess mortality.

Polygenic susceptibility to prostate and breast cancer: implications for personalised screening.

BACKGROUND: We modelled the efficiency of a personalised approach to screening for prostate and breast cancer based on age and polygenic risk-profile compared with the standard approach based on age alone. METHODS: We compared the number of cases potentially detectable by screening in a population undergoing personalised screening with a population undergoing screening based on age alone. Polygenic disease risk was assumed to have a log-normal relative risk distribution predicted for the currently known prostate or breast cancer susceptibility variants (N=31 and N=18, respectively). RESULTS: Compared with screening men based on age alone (aged 55-79: 10-year absolute risk ≥2%), personalised screening of men age 45-79 at the same risk threshold would result in 16% fewer men being eligible for screening at a cost of 3% fewer screen-detectable cases, but with added benefit of detecting additional cases in younger men at high risk. Similarly, compared with screening women based on age alone (aged 47-79: 10-year absolute risk ≥2.5%), personalised screening of women age 35-79 at the same risk threshold would result in 24% fewer women being eligible for screening at a cost of 14% fewer screen-detectable cases. CONCLUSION: Personalised screening approach could improve the efficiency of screening programmes. This has potential implications on informing public health policy on cancer screening.

Comparison of methods for handling missing data on immunohistochemical markers in survival analysis of breast cancer.

BACKGROUND: Tissue micro-arrays (TMAs) are increasingly used to generate data of the molecular phenotype of tumours in clinical epidemiology studies, such as studies of disease prognosis. However, TMA data are particularly prone to missingness. A variety of methods to deal with missing data are available. However, the validity of the various approaches is dependent on the structure of the missing data and there are few empirical studies dealing with missing data from molecular pathology. The purpose of this study was to investigate the results of four commonly used approaches to handling missing data from a large, multi-centre study of the molecular pathological determinants of prognosis in breast cancer. PATIENTS AND METHODS: We pooled data from over 11,000 cases of invasive breast cancer from five studies that collected information on seven prognostic indicators together with survival time data. We compared the results of a multi-variate Cox regression using four approaches to handling missing data - complete case analysis (CCA), mean substitution (MS) and multiple imputation without inclusion of the outcome (MI-) and multiple imputation with inclusion of the outcome (MI+). We also performed an analysis in which missing data were simulated under different assumptions and the results of the four methods were compared. RESULTS: Over half the cases had missing data on at least one of the seven variables and 11 percent had missing data on 4 or more. The multi-variate hazard ratio estimates based on multiple imputation models were very similar to those derived after using MS, with similar standard errors. Hazard ratio estimates based on the CCA were only slightly different, but the estimates were less precise as the standard errors were large. However, in data simulated to be missing completely at random (MCAR) or missing at random (MAR), estimates for MI+ were least biased and most accurate, whereas estimates for CCA were most biased and least accurate. CONCLUSION: In this study, empirical results from analyses using CCA, MS, MI- and MI+ were similar, although results from CCA were less precise. The results from simulations suggest that in general MI+ is likely to be the best. Given the ease of implementing MI in standard statistical software, the results of MI+ and CCA should be compared in any multi-variate analysis where missing data are a problem.

Identification of a novel prostate cancer susceptibility variant in the KLK3 gene transcript.

Genome-wide association studies (GWAS) have identified more than 30 prostate cancer (PrCa) susceptibility loci. One of these (rs2735839) is located close to a plausible candidate susceptibility gene, KLK3, which encodes prostate-specific antigen (PSA). PSA is widely used as a biomarker for PrCa detection and disease monitoring. To refine the association between PrCa and variants in this region, we used genotyping data from a two-stage GWAS using samples from the UK and Australia, and the Cancer Genetic Markers of Susceptibility (CGEMS) study. Genotypes were imputed for 197 and 312 single nucleotide polymorphisms (SNPs) from HapMap2 and the 1000 Genome Project, respectively. The most significant association with PrCa was with a previously unidentified SNP, rs17632542 (combined P = 3.9 × 10(-22)). This association was confirmed by direct genotyping in three stages of the UK/Australian GWAS, involving 10,405 cases and 10,681 controls (combined P = 1.9 × 10(-34)). rs17632542 is also shown to be associated with PSA levels and it is a non-synonymous coding SNP (Ile179Thr) in KLK3. Using molecular dynamic simulation, we showed evidence that this variant has the potential to introduce alterations in the protein or affect RNA splicing. We propose that rs17632542 may directly influence PrCa risk.

Common germ-line polymorphism of C1QA and breast cancer survival.

BACKGROUND: A synonymous single nucleotide polymorphism (SNP) rs172378 (A>G, Gly->Gly) in the complement component C1QA has been proposed to be associated with distant breast cancer metastasis. We previously reported overexpression of this gene to be significantly associated with better prognosis in oestrogen-receptor-negative tumours. The purpose of this study was to investigate the association of rs172378 with expression of C1QA and breast cancer survival. METHODS: We analysed the gene expression pattern of rs172378 in normal and tumour tissue samples, and further explored its involvement in relation to mortality in 2270 women with breast cancer participating in Studies of Epidemiology and Risk factors in Cancer Heredity, a population-based case-control study. RESULTS: We found that although rs172378 showed differential allelic expression significantly different between normal (preferentially expressing the G allele) and tumour tissue samples (preferentially expressing the A allele), there was no significant difference in survival by rs172378 genotype (per allele hazard ratio (HR) 1.02, 95% CI: 0.88-1.19, P=0.78 for all-cause mortality; HR 1.03, 95% CI: 0.87-1.22, P=0.72 for breast-cancer-specific mortality). CONCLUSION: Our study results show that rs172378 is linked to a cis-regulatory element affecting gene expression and that allelic preferential expression is altered in tumour samples, but do not support an association between genetic variation in C1QA and breast cancer survival.