ABSTRACT
Residents of long-term care facilities (LTCFs) were disproportionately affected by the COVID-19 pandemic. We assessed the extent to which hospital-associated infections contributed to COVID-19 LTCF outbreaks in England. We matched addresses of cases between March 2020 and June 2021 to reference databases to identify LTCF residents. Linkage to health service records identified hospital-associated infections, with the number of days spent in hospital before positive specimen date used to classify these as definite or probable. Of 149,129 cases in LTCF residents during the study period, 3,748 (2.5%) were definite or probable hospital-associated and discharged to an LTCF. Overall, 431 (0.3%) were identified as index cases of potentially nosocomial-seeded outbreaks (2.7% (431/15,797) of all identified LTCF outbreaks). These outbreaks involved 4,521 resident cases and 1,335 deaths, representing 3.0% and 3.6% of all cases and deaths in LTCF residents, respectively. The proportion of outbreaks that were potentially nosocomial-seeded peaked in late June 2020, early December 2020, mid-January 2021, and mid-April 2021. Nosocomial seeding contributed to COVID-19 LTCF outbreaks but is unlikely to have accounted for a substantial proportion. The continued identification of such outbreaks after the implementation of preventative policies highlights the challenges of preventing their occurrence.
Subject(s)
COVID-19 , Cross Infection , Humans , COVID-19/epidemiology , Long-Term Care , Cross Infection/epidemiology , Pandemics , Nursing Homes , Hospitals , Disease Outbreaks/prevention & controlABSTRACT
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant (B.1.1.529) rapidly replaced Delta (B.1.617.2) to become dominant in England. Our study assessed differences in transmission between Omicron and Delta using two independent data sources and methods. Omicron and Delta cases were identified through genomic sequencing, genotyping and S-gene target failure in England from 5-11 December 2021. Secondary attack rates for named contacts were calculated in household and non-household settings using contact tracing data, while household clustering was identified using national surveillance data. Logistic regression models were applied to control for factors associated with transmission for both methods. For contact tracing data, higher secondary attack rates for Omicron vs. Delta were identified in households (15.0% vs. 10.8%) and non-households (8.2% vs. 3.7%). For both variants, in household settings, onward transmission was reduced from cases and named contacts who had three doses of vaccine compared to two, but this effect was less pronounced for Omicron (adjusted risk ratio, aRR 0.78 and 0.88) than Delta (aRR 0.62 and 0.68). In non-household settings, a similar reduction was observed only in contacts who had three doses vs. two doses for both Delta (aRR 0.51) and Omicron (aRR 0.76). For national surveillance data, the risk of household clustering, was increased 3.5-fold for Omicron compared to Delta (aRR 3.54 (3.29-3.81)). Our study identified increased risk of onward transmission of Omicron, consistent with its successful global displacement of Delta. We identified a reduced effectiveness of vaccination in lowering risk of transmission, a likely contributor for the rapid propagation of Omicron.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , Cohort Studies , COVID-19/epidemiology , COVID-19/prevention & control , Vaccination , England/epidemiologyABSTRACT
Persons experiencing homelessness (PEH) or rough sleeping are a vulnerable population, likely to be disproportionately affected by the coronavirus disease 2019 (COVID-19) pandemic. The impact of COVID-19 infection on this population is yet to be fully described in England. We present a novel method to identify COVID-19 cases in this population and describe its findings. A phenotype was developed and validated to identify PEH or rough sleeping in a national surveillance system. Confirmed COVID-19 cases in England from March 2020 to March 2022 were address-matched to known homelessness accommodations and shelters. Further cases were identified using address-based indicators, such as NHS pseudo postcodes. In total, 1835 cases were identified by the phenotype. Most were <39 years of age (66.8%) and male (62.8%). The proportion of cases was highest in London (29.8%). The proportion of cases of a minority ethnic background and deaths were disproportionality greater in this population, compared to all COVID-19 cases in England. This methodology provides an approach to track the impact of COVID-19 on a subset of this population and will be relevant to policy making. Future surveillance systems and studies may benefit from this approach to further investigate the impact of COVID-19 and other diseases on select populations.
Subject(s)
COVID-19 , Ill-Housed Persons , Male , Humans , COVID-19/epidemiology , SARS-CoV-2 , England/epidemiology , LondonABSTRACT
BACKGROUND: From 12th March 2020, individuals in England were advised to quarantine in their home if a household member tested positive for SARS-CoV-2. A mandatory isolation period of 10 days was introduced on 28th September 2020 and applied to all individuals with COVID-19. We assessed the frequency, timing, and characteristics of recovered COVID-19 cases requiring subsequent quarantine episodes due to household re-exposure. METHODS: In this case cohort study, all laboratory-confirmed COVID-19 cases notified in England (29th June to 28th December 2020) were analysed to identify consecutive household case(s). Multivariable logistic regression was used to determine associations between case characteristics and need to quarantine following recent infection (within 28 days of diagnosis). RESULTS: Among 1,651,550 cases resident in private dwellings and Houses of Multiple Occupancy (HMOs), 744,548 (45.1%) were the only case in their home and 56,179 (3.4%) were succeeded by further household cases diagnosed within 11-28 days of their diagnosis. Of 1,641,412 cases arising in private homes, the likelihood of further household cases was highest for Bangladeshi (aOR = 2.20, 95% CI = 2.10-2.31) and Pakistani (aOR = 2.15, 95% CI = 2.08-2.22) individuals compared to White British, as well as among young people (17-24y vs. 25-64y; aOR = 1.19, 95% CI = 1.16-1.22), men (vs. women; aOR = 1.06, 95% CI = 1.04-1.08), London residents (vs. Yorkshire and Humber; aOR = 1.57, 95% CI = 1.52-1.63) and areas of high deprivation (IMD 1 vs. 10; aOR = 1.13, 95% CI = 1.09-1.19). CONCLUSION: Policies requiring quarantine on re-exposure differentially impact some of the most disadvantaged populations. Quarantine exemption for recently recovered individuals could mitigate the socioeconomic impact of responses to COVID-19 or similar infectious disease outbreaks.
Subject(s)
COVID-19 , Quarantine , Adolescent , COVID-19/epidemiology , Cohort Studies , Female , Humans , Male , Policy , SARS-CoV-2ABSTRACT
Each September in England, ≈1 million students relocate to study at universities. To determine COVID-19 cases and outbreaks among university students after their return to university during the COVID pandemic in September 2020, we identified students with COVID-19 (student case-patients) by reviewing contact tracing records identifying attendance at university and residence in student accommodations identified by matching case-patients' residential addresses with national property databases. We determined COVID-19 rates in towns/cities with and without a university campus. We identified 53,430 student case-patients during September 1-December 31, 2020, which accounted for 2.7% of all cases during this period. Student case-patients increased rapidly after the start of the term, driven initially by cases and outbreaks in student accommodations. Case rates among students 18-23 years of age doubled at the start of term in towns with universities. Our findings highlight the need for face-to-face and control measures to reduce virus transmission.
Subject(s)
COVID-19 , COVID-19/epidemiology , Humans , Pandemics/prevention & control , SARS-CoV-2 , Students , UniversitiesABSTRACT
BACKGROUND: The emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) B.1.1.7 variant in England in 2020 and subsequent global spread emphasized the need to understand epidemiologic characteristics of SARS-CoV-2 variants. A diagnostic proxy for this variant, referred to as S-gene target failure, provided a rich dataset to assess transmissibility of the variant in an analysis of clustering in residential settings. METHODS: We used a pair-matched case-control study design to estimate odds of onward transmission within households with S-gene target failure index cases versus nontarget failure index cases. We defined cases as the index in a household cluster (clustered case) and controls as a case with no subsequent household cluster (sporadic). We matched clustered and sporadic cases one-to-one on specimen week, geography, and property type. We used conditional logistic regression, adjusting for age, sex, ethnicity, and symptom status, to assess odds of residential clustering. RESULTS: Our study population comprised 57,244 individuals with specimen dates from 23 November 2020 to 4 January 2021. Crude analysis yielded 54% increased odds (odds ratio [OR] = 1.5; 95% confidence interval [CI] = 1.5, 1.6) of residential clustering associated with S-gene target failure; the association remained in the fully adjusted model (OR = 1.6, 95% CI = 1.5, 1.6). Stratified analyses by region showed increased odds of residential clustering associated with target failure in all regions apart from the Southwest, where we observed lower precision. Similar adjusted odds ratios with precise confidence intervals remained in stratified analyses by property category. CONCLUSION: We observed increased odds in all property types, consistent with greater transmissibility of the B.1.1.7 variant in this high-risk setting.
Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Case-Control Studies , Cluster Analysis , Humans , SARS-CoV-2/geneticsABSTRACT
BackgroundThe emergence of the SARS-CoV-2 Alpha variant in England coincided with a rapid increase in the number of PCR-confirmed COVID-19 cases in areas where the variant was concentrated.AimOur aim was to assess whether infection with Alpha was associated with more severe clinical outcomes than the wild type.MethodsLaboratory-confirmed infections with genomically sequenced SARS-CoV-2 Alpha and wild type between October and December 2020 were linked to routine healthcare and surveillance datasets. We conducted two statistical analyses to compare the risk of hospital admission and death within 28 days of testing between Alpha and wild-type infections: a matched cohort study and an adjusted Cox proportional hazards model. We assessed differences in disease severity by comparing hospital admission and mortality, including length of hospitalisation and time to death.ResultsOf 63,609 COVID-19 cases sequenced in England between October and December 2020, 6,038 had the Alpha variant. In the matched cohort analysis, we matched 2,821 cases with Alpha to 2,821 to cases with wild type. In the time-to-event analysis, we observed a 34% increased risk in hospitalisation associated with Alpha compared with wild type, but no significant difference in the risk of mortality.ConclusionWe found evidence of increased risk of hospitalisation after adjusting for key confounders, suggesting increased infection severity associated with the Alpha variant. Rapid assessments of the relative morbidity in terms of clinical outcomes and mortality associated with emerging SARS-CoV-2 variants compared with dominant variants are required to assess overall impact of SARS-CoV-2 mutations.
Subject(s)
COVID-19 , SARS-CoV-2 , Cohort Studies , England/epidemiology , Hospitalization , Hospitals , Humans , SARS-CoV-2/geneticsABSTRACT
BACKGROUND: DNA double strand breaks can affect genome integrity potentially leading to cancer. RAD51-associated protein 1 (RAD51AP1), an accessory protein to RAD51, is critical for homologous recombination, a key DNA damage response pathway. Emerging studies indicate a novel role for RAD51AP1 in carcinogenesis. Here we provide additional insight into the role of RAD51AP1 in ovarian cancer (OvCa). METHODS: Gene expression and patient phenotype data were obtained from TCGA and GTEX project consortia for bioinformatics analysis. Immunohistochemistry of OvCa tissue microarray was undertaken. Functional analyses were performed in a SKOV3 OvCa cell line with down-regulation of RAD51AP1 using siRNA. RESULTS: RAD51AP1 is overexpressed at gene level in primary and recurrent OvCa compared to controls. At protein level, RAD51AP1 was up-regulated in low grade serous tumors compared to high grade OvCa. There was higher expression of RAD51AP1 in OvCa metastatic to lymph nodes compared to primary cancer samples. Gene enrichment analyses identified 12 differentially expressed genes (DEGs) related to OvCa, eight of which are also common in tissue from patients with type 2 diabetes mellitus (T2DM). CONCLUSIONS: RAD51AP1 is overexpressed in OvCa, Given the link between OvCa and T2DM, the eight-gene signature shows potential for predictive value.
ABSTRACT
OBJECTIVES: Prisons are high-risk settings for infectious disease outbreaks because of their highly dynamic and crowded nature. During late 2020, prisons in England observed a surge in COVID-19 infection. This study describes the emergence of the Alpha variant in prisons during this period. METHODS: Alpha and non-Alpha variant COVID-19 cases were identified in prisoners in England using address-matched laboratory notifications and genomic information from COG-UK. RESULTS: Of 14,094 COVID-19-positive prisoner cases between 1 October 2020 and 28 March 2021, 11.5% (n = 1621) had sequencing results. Of these, 1082 (66.7%) were identified as the Alpha variant. Twenty-nine (2.7%) Alpha cases required hospitalisation compared with only five (1.0%; P = 0.02) non-Alpha cases. A total of 14 outbreaks were identified with the median attack rate higher for Alpha (17.9%, interquartile range [IQR] 3.2%-32.2%; P = 0.11) than non-Alpha outbreaks (3.5%, IQR 2.0%-10.2%). CONCLUSION: Higher attack rates and increased likelihood of hospitalisations were observed for Alpha cases compared with non-Alpha. This suggests a key contribution to the rise in cases, hospitalisations and outbreaks in prisons in the second wave. With prisons prone to COVID-19 outbreaks and the potential to act as reservoirs for variants of concern, sequencing of prison-associated cases alongside whole-institution vaccination should be prioritised.
Subject(s)
COVID-19 , Prisoners , COVID-19/epidemiology , England/epidemiology , Humans , Prisons , SARS-CoV-2/geneticsABSTRACT
BACKGROUND: Long-term care facilities (LTCF) worldwide have suffered high rates of COVID-19, reflecting the vulnerability of the persons who live there and the institutional nature of care delivered. This study describes the impact of the pandemic on incidences and deaths in LTCF across England. METHODS: Laboratory-confirmed SARS-CoV-2 cases in England, notified to Public Health England from 01 Jan to 25 Dec 2020, were address-matched to an Ordnance Survey reference database to identify residential property classifications. Data were analysed to characterize cases and identify clusters. Associated deaths were defined as death within 60 days of diagnosis or certified as cause of death. RESULTS: Of 1 936 315 COVID-19 cases, 81 275 (4.2%) and 10 050 (0.52%) were identified as resident or staff in an LTCF, respectively, with 20 544 associated deaths in residents, accounting for 31.3% of all COVID-19 deaths. Cases were identified in 69.5% of all LTCFs in England, with 33.1% experiencing multiple outbreaks. Multivariable analysis showed a 67% increased odds of death in residents [adjusted odds ratio (aOR): 1.67, 95% confidence interval (CI): 1.63-1.72], compared with those not residing in LTCFs. A total of 10 321 outbreaks were identified at these facilities, of which 8.2% identified the first case as a staff member. CONCLUSIONS: Over two-thirds of LTCFs have experienced large and widespread outbreaks of COVID-19, and just under one-third of all COVID-19 deaths occurring in this setting in spite of early policies. A key implication of our findings is upsurges in community incidences seemingly leading to increased outbreaks in LTCFs; thus, identifying and shielding residents from key sources of infection are vital to reduce the number of future outbreaks.
Subject(s)
COVID-19 , Long-Term Care , Humans , Pandemics , Population Surveillance , SARS-CoV-2ABSTRACT
BACKGROUND: The SARS-CoV-2 Delta variant (B.1.617.2), first detected in India, has rapidly become the dominant variant in England. Early reports suggest this variant has an increased growth rate suggesting increased transmissibility. This study indirectly assessed differences in transmissibility between the emergent Delta variant compared to the previously dominant Alpha variant (B.1.1.7). METHODS: A matched case-control study was conducted to estimate the odds of household transmission (≥ 2 cases within 14 days) for Delta variant index cases compared with Alpha cases. Cases were derived from national surveillance data (March to June 2021). One-to-two matching was undertaken on geographical location of residence, time period of testing and property type, and a multivariable conditional logistic regression model was used for analysis. FINDINGS: In total 5,976 genomically sequenced index cases in household clusters were matched to 11,952 sporadic index cases (single case within a household). 43.3% (n=2,586) of cases in household clusters were confirmed Delta variant compared to 40.4% (n= 4,824) of sporadic cases. The odds ratio of household transmission was 1.70 among Delta variant cases (95% CI 1.48-1.95, p <0.001) compared to Alpha cases after adjusting for age, sex, ethnicity, index of multiple deprivation (IMD), number of household contacts and vaccination status of index case. INTERPRETATION: We found evidence of increased household transmission of SARS-CoV-2 Delta variant, potentially explaining its success at displacing Alpha variant as the dominant strain in England. With the Delta variant now having been detected in many countries worldwide, the understanding of the transmissibility of this variant is important for informing infection prevention and control policies internationally.
ABSTRACT
Easing of COVID-19 restrictions in England in the summer of 2021 was followed by a sharp rise in cases among school-aged children. Weekly rates of SARS-CoV-2 infection in primary and secondary school children reached 733.3 and 1,664.7/100,000 population, respectively, by week 39 2021. A surge in household clusters with school-aged index cases was noted at the start of the school term, with secondary cases predominantly in children aged 5-15 years and adults aged 30-49 years.
Subject(s)
COVID-19 , SARS-CoV-2 , Adult , Child , England/epidemiology , Family Characteristics , Humans , SchoolsABSTRACT
BACKGROUND: Persons living in long-term care facilities (LTCFs) are presumed to be at higher risk of adverse outcomes from SARS-CoV-2 infection due to increasing age and frailty, but the magnitude of increased risk is not well quantified. METHODS: After linking demographic and mortality data for cases with confirmed SARS-CoV-2 infection between March 2020 and January 2021 in England, a random sample of 6000 persons who died and 36 000 who did not die within 28 days of a positive test was obtained from the dataset of 3 020 800 patients. Based on an address-matching process, the residence type of each case was categorised into one of private home and residential or nursing LTCF. Univariable and multivariable logistic regression analysis was conducted. RESULTS: Multivariable analysis showed that an interaction effect between age and residence type determined the outcome. Compared with a 60-year-old person not living in LTCF, the adjusted OR (aOR) for same-aged persons living in residential and nursing LTCFs was 1.77 (95% CI 1.21 to 2.6, p=0.0017) and 3.95 (95% CI 2.77 to 5.64, p<0.0001), respectively. At 90 years of age, aORs were 0.87 (95% CI 0.72 to 1.06, p=0.21) and 0.74 (95% CI 0.61 to 0.9, p=0.001), respectively. The model had an overall accuracy of 94.2% (94.2%) when applied to the full dataset of 2 978 800 patients. CONCLUSION: This study found that residents of LTCFs in England had higher odds of death up to 80 years of age. Beyond 80 years, there was no difference in the odds of death for LTCF residents compared with those in the wider community.
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Using laboratory data and a novel address matching methodology, we identified 734 cases of coronavirus disease in 88 prisons in England during March 16-October 12, 2020. An additional 412 cases were identified in prison staff and household members. We identified 84 prison outbreaks involving 86% of all prison-associated cases.
Subject(s)
COVID-19 , Prisoners , Disease Outbreaks , England/epidemiology , Humans , Prisons , SARS-CoV-2Subject(s)
COVID-19 , Family Characteristics , COVID-19/virology , Cluster Analysis , England/epidemiology , Humans , SARS-CoV-2 , United KingdomABSTRACT
Circulating tumour cells (CTCs) are cancer cells of epithelial origin that are present in peripheral blood samples. ScreenCell detection of CTCs and the association with long term survival in non-small cell lung cancer (NSCLC) patients was evaluated in the present study. A total of 33 patients undergoing surgical resection for NSCLC were recruited. Patients were followed up for 5-years post-operatively. Pre-operative patient bloods samples were processed using ScreenCell. CTCs were detected in 26 (79%) patients. In patients who were positive for CTCs, a total of 9 (35%) patients succumbed to the disease, whereas in patients negative for CTCs, a total of 4 (57%) patients succumbed to the disease (P=0.29). No association was identified between positive CTCs and poorer survival (Chi-squared 1.47, P=0.23; hazard ratio, 0.42; 95% confidence interval: 0.1-1.7). The presence of CTCs detected with ScreenCell does not influence prognosis in patients with NSCLC that was operated on. The high rate of CTC detection is encouraging in supporting this technology to aid early lung cancer diagnosis.
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Ovarian cancer is fifth in the rankings of cancer deaths among women, and accounts for more deaths than any other gynecological malignancy. Despite some improvement in overall-(OS) and progression-free survival (PFS) following surgery and first-line chemotherapy, there is a need for development of novel and more effective therapeutic strategies. In this mini review, we provide a summary of the current landscape of the clinical use of tyrosine kinase inhibitors (TKIs) and mechanistic target of rapamycin (mTOR) inhibitors in ovarian cancer. Emerging data from phase I and II trials reveals that a combinatorial treatment that includes TKIs and chemotherapy agents seems promising in terms of PFS despite some adverse effects recorded; whereas the use of mTOR inhibitors seems less effective. There is a need for further research into the inhibition of multiple signaling pathways in ovarian cancer and progression to phase III trials for drugs that seem most promising.
ABSTRACT
:Background: Current diagnosis and staging of advanced epithelial ovarian cancer (aEOC) has important limitations and better biomarkers are needed. We investigate the performance of non-haematopoietic circulating cells (CCs) at the time of disease presentation and relapse. Methods: Venous blood was collected prospectively from 37 aEOC patients and 39 volunteers. CCs were evaluated using ImageStream TechnologyTM and specific antibodies to differentiate epithelial cells from haematopoetic cells. qRT-PCR from whole blood of relapsed aEOC patients was carried out for biomarker discovery. Results: Significant numbers of CCs (CK+/WT1+/CD45-) were identified, quantified and characterised from aEOC patients compared to volunteers. CCs are abundant in women with newly diagnosed aEOC, prior to any treatment. Evaluation of RNA from the CCs in relapsed aEOC patients (n = 5) against a 79-gene panel revealed several differentially expressed genes compared to volunteers (n = 14). Size differentiation of CCs versus CD45+ haematopoietic cells was not reliable. Conclusion: CCs of non-haematopoetic origin are prevalent, particularly in patients with newly diagnosed aEOC. Exploiting a CC-rich population in aEOC patients offers insights into a part of the circulating microenvironment.
Subject(s)
Carcinoma/blood , Neoplastic Cells, Circulating/metabolism , Ovarian Neoplasms/blood , Biomarkers, Tumor/metabolism , Cell Line, Tumor , Female , Humans , Leukocyte Common Antigens/metabolism , Middle Aged , Neoplastic Cells, Circulating/pathology , WT1 Proteins/metabolismABSTRACT
Background: Liquid biopsies offer a promising alternative to tissue samples, providing non-invasive diagnostic approaches or serial monitoring of disease evolution. However, certain challenges remain, and the full potential of liquid biopsies has yet to be reached. Here we report several methodological approaches to interrogate liquid biopsies using circulating tumour cell (CTC) enumeration and characterisation, transcriptomics, Raman spectroscopy, and copy number instability (CNI) scores using blood samples of lung cancer (LC) patients. Methods: We choose LC; since it still is the most common cause of cancer-related mortality worldwide, and therefore there is a need for development of new non-invasive diagnostic/prognostic technologies. Changes in gene expression were assessed using RNA-seq, and in CTCs using ImageStream, an imaging flow-cytometer. CNI scores, from paired tissue/ctDNA were also explored. Raman spectroscopy was used to provide chemical fingerprints of plasma samples. Results: CTCs were detected in all LC patients (n = 10). We observed a significant increase in CTC levels in LC patients (n = 10) compared to controls (n = 21). A similar CNI was noted in the tissue and plasma of 2 patients, where higher CNI scores corresponded with poorer outcome. Significant changes in Raman spectra (carotenoid concentrations) were noted in LC patients (n = 20) compared to controls (n = 10). RNA-seq revealed differential expression of 21 genes between LC cases and controls in both LC tissue and blood samples. Conclusions: Liquid biopsies can potentially provide a more comprehensive picture of the disease compared to a single tissue biopsy. CTC enumeration is feasible and sensitive for LC patients. Molecular profiling of CTCs is also possible from total blood. CNI scores and Raman spectra require further investigation. Further work is being undertaken to explore these methods of detection in a larger LC cohort.
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INTRODUCTION: Lung cancer survival remains poor in the western world due to late presentation in most cases, leading to difficulty of treatment in these advanced and metastatic patients. Therefore, the development of a robust biomarker for prognosis and to monitor treatment response and relapse would be of great benefit. The use of Alu repeats and DNA Integrity Index has been shown to hold both diagnostic and prognostic value, and as it is obtained from the plasma of patients, it can serve as a non-invasive tool for routine monitoring. This study evaluates the efficiency of this technique in malignant lung cancer patients. METHODS: Plasma samples were collected from 48 patients, consisting of 29 lung cancer patients and 19 non-cancer controls. Alu repeat ratio and confounders were measured. RESULTS: Observations showed a higher Alu repeat ratio amongst the cancer group compared to controls (p=0.035), mean Alu ratio 0.38 (range 0.01-0.93) and 0.22 (0.007-0.44) respectively, ROC curve analysis AUC 0.61 (p=0.22). Analysis by staging was more promising, whereby a higher DNA Integrity Index was seen in advanced cases compared to both early stage and controls, p<0.0001; AUC: 0.92 (P=0.0002) and p=0.0006, AUC - 0.88 (p=0.0007) respectively, however no significant difference was observed in the early stage compared to controls. Short term survival data also showed a DNA Integrity Index of >0.5 to be associated with poorer overall survival p=0.03. CONCLUSION: The results of this study show a potential use of Alu repeats ratios for prognostic purposes in the advanced setting for lung cancer patients.