A comparison of the carbon footprint of alternative sampling approaches for cervical screening in the UK: A descriptive study.

OBJECTIVE: To understand whether self-sampling can reduce carbon emissions (CO2 e) from the NHS cervical screening programme (NHSCSP) by comparing the carbon footprint of three sampling strategies: routine cervical sampling, vaginal self-sampling and first-void (FV) urine collection. DESIGN: Descriptive study. SETTING: National Health Service (NHS), United Kingdom (UK). POPULATION OR SAMPLE: Patients aged 25-64 years eligible for cervical screening in the UK. METHODS: A carbon footprint analysis was undertaken for three cervical screening sampling approaches, from point of invitation to screening through to preparation for transport to the laboratory for HPV testing. A combination of primary and secondary data were used, with a bottom-up approach applied to collection of primary data. MAIN OUTCOME MEASURES: We report CO2 e per sampling approach, which is the unit used to express carbon footprint and harmonise the contributions of greenhouse gases with different global warming potentials. RESULTS: The total carbon footprint of routine cervical sampling is 3670 g CO2 e. By comparison, vaginal self-sampling had a total carbon footprint of 423 g CO2 e, and FV urine sampling 570 g CO2 e. The largest share of emissions for routine sampling was attributable to the carbon footprint associated with an appointment in a primary care setting, which totalled 2768 g CO2 e. CONCLUSIONS: Routine cervical sampling is up to 8.7-fold more carbon-intensive than self-sampling approaches with equivalent effectiveness. We found negligible differences in the carbon footprint of alternative self-sampling methods, supporting the need for an informed choice of screening options for participants, which includes sharing information on their environmental impacts.

Urine high-risk human papillomavirus testing as an alternative to routine cervical screening: A comparative diagnostic accuracy study of two urine collection devices using a randomised study design trial.

OBJECTIVE: To evaluate the sensitivity of human papillomavirus (HPV) tested urine to detect high-grade cervical precancer (cervical intraepithelial neoplasia grade 2+ [CIN2+]) using two urine collection devices. DESIGN: Randomised controlled trial. SETTING: St Mary's Hospital, Manchester, UK. POPULATION: Colposcopy attendees with abnormal cervical screening; a total of 480 participants were randomised. Matched urine and cervical samples were available for 235 and 230 participants using a first-void urine (FVU)-collection device and standard pot, respectively. METHODS: Urine was self-collected and mixed with preservative - randomised 1:1 to FVU-collection device (Novosanis Colli-pee® 10 mL with urine conservation medium [UCM]) or standard pot. Matched clinician-collected cervical samples were taken before colposcopy. HPV testing used Roche cobas® 8800. A questionnaire evaluated urine self-sampling acceptability. MAIN OUTCOME MEASURES: The primary outcome measured sensitivity of HPV-tested urine (FVU-collection device and standard pot) for CIN2+ detection. Secondary outcomes compared HPV-tested cervical and urine samples for CIN2+ and evaluated the acceptability of urine self-sampling. RESULTS: Urine HPV test sensitivity for CIN2+ was higher with the FVU-collection device (90.3%, 95% CI 83.7%-94.9%, 112/124) than the standard pot (73.4%, 95% CI 64.7%-80.9%, 91/124, p = 0.0005). The relative sensitivity of FVU-device-collected urine was 0.92 (95% CI 0.87-0.97, pMcN = 0.004) compared with cervical, considering that all women were referred after a positive cervical HPV test. Urine-based sampling was acceptable to colposcopy attendees. CONCLUSIONS: Testing of FVU-device-collected urine for HPV was superior to standard-pot-collected urine in colposcopy attendees and has promising sensitivity for CIN2+ detection. General population HPV testing of FVU-device-collected urine will establish its clinical performance and acceptability as an alternative to routine cervical screening.

Factors associated with cervical screening coverage: a longitudinal analysis of English general practices from 2013 to 2022.

BACKGROUND: Cervical cancer remains an important global public health concern. Understanding the factors contributing to a decline in screening uptake in high-income countries is fundamental to improving screening rates. We aimed to identify general practice and patient characteristics related to cervical screening coverage in England between 2013 and 2022. METHODS: We analyzed a panel of 59 271 General Practice (GP)-years from 7881 GP practices. We applied correlated random effects regression to examine the association between cervical screening uptake and a rich set of GP practice workforce, size, quality and patient characteristics. RESULTS: Our results show a decline in overall screening rates from 2013/14 to 2021/22 from 77% to 72%. We find GP workforce and list size characteristics are strongly related to screening rates. An increase in 1 FTE Nurse per 1000 patients is related to a 1.94 percentage point increase in cervical screening rates. GP practices located in more deprived areas have lower screening rates. CONCLUSIONS: GP workforce and patient characteristics need to be considered by decision-makers to increase screening rates. The implementation of self-sampling screening methods could help address some of the current barriers to screening, including lack of healthcare staff and facilities.

Longitudinal analysis of urinary proteins in lupus nephritis - A pilot study.

Approximately 30% of adult-onset systemic lupus erythematosus (SLE) patients develop lupus nephritis (LN). The gold standard for LN detection involves renal biopsies, invasive procedures not suitable for routine disease monitoring. A urinary biomarker panel comprised of lipocalin-like prostaglandin D synthase (LPGDS), transferrin, alpha-1-acid glycoprotein (AGP-1), ceruloplasmin, monocyte chemoattractant protein 1 (MCP-1) and soluble vascular cell adhesion molecule-1 (sVCAM-1) has shown promise to predict LN and response to rituximab at baseline. Whether these proteins predict LN during longitudinal sampling, however, remained unknown. Here, we quantified aforementioned urinary proteins at baseline (N = 25), six and twelve months (N = 17 each) after rituximab treatment. Urine MCP-1 (at six and twelve months) and AGP-1 (at twelve months) levels varied between patients with active vs mildly active/inactive LN. Findings support the use of urinary proteins to detect active LN in ongoing disease monitoring in adult-onset SLE patients, but need to be validated in larger cohorts.

A panel of urinary proteins predicts active lupus nephritis and response to rituximab treatment.

OBJECTIVES: ∼30% of patients with SLE develop LN. Presence and/or severity of LN are currently assessed by renal biopsy, but biomarkers in serum or urine samples may provide an avenue for non-invasive routine testing. We aimed to validate a urinary protein panel for its ability to predict active renal involvement in SLE. METHODS: A total of 197 SLE patients and 48 healthy controls were recruited, and urine samples collected. Seventy-five of the SLE patients had active LN and 104 had no or inactive renal disease. Concentrations of lipocalin-like prostaglandin D synthase (LPGDS), transferrin, alpha-1-acid glycoprotein (AGP-1), ceruloplasmin, monocyte chemoattractant protein 1 (MCP-1) and soluble vascular cell adhesion molecule-1 (sVCAM-1) were quantified by MILLIPLEX® Assays using the MAGPIX Luminex platform. Binary logistic regression was conducted to examine whether proteins levels associate with active renal involvement and/or response to rituximab treatment. RESULTS: Urine levels of transferrin (P <0.005), AGP-1 (P <0.0001), MCP-1 (P <0.001) and sVCAM-1 (P <0.005) were significantly higher in SLE patients when compared with healthy controls. Furthermore, levels of transferrin, AGP-1, ceruloplasmin, MCP-1 and sVCAM-1 (all P <0.0001) were higher in SLE patients with active LN when compared with patients without active LN. A combination of five urine proteins, namely LPGDS, transferrin, ceruloplasmin, MCP-1 and sVCAM-1 was a good predictor of active LN (AUC 0.898). A combined model of LPGDS, transferrin, AGP-1, ceruloplasmin, MCP-1 and sVCAM-1 predicted response to rituximab treatment at 12 months (AUC 0.818). CONCLUSIONS: Findings support the use of a urinary protein panel to identify active LN and potentially predict response to treatment with rituximab in adult SLE patients. Prospective studies are required to confirm findings.

Limited value of serum neurofilament light chain in diagnosing amyotrophic lateral sclerosis.

A biomarker specific for the diagnosis of amyotrophic lateral sclerosis must be sensitive across a spectrum of clinical heterogeneity. Neurofilament light chain levels in amyotrophic lateral sclerosis correlate with the rate of disability progression. Previous attempts to establish a diagnostic role for neurofilament light chain have been limited to comparison with healthy individuals or controls with alternative diagnoses unlikely to be confused with amyotrophic lateral sclerosis in real-world clinical practice. In a tertiary amyotrophic lateral sclerosis referral clinic, at first visit, serum was taken for neurofilament light chain measurement after prospectively recording the clinical diagnosis as 'amyotrophic lateral sclerosis', 'primary lateral sclerosis', 'alternative' or 'currently uncertain'. Of 133 referrals, 93 patients were diagnosed with amyotrophic lateral sclerosis (median neurofilament light chain 218.1 pg/ml, interquartile range 130.7-311.9), three primary lateral sclerosis (65.6, 51.5-106.9) and 19 alternative diagnoses (45.2, 13.5-71.9) at first visit. Of 18 initially uncertain diagnoses, eight were subsequently diagnosed with amyotrophic lateral sclerosis (98.5, 45.3-300.1). Neurofilament light chain ≥110.9 pg/ml had a positive predictive value of 0.92 for amyotrophic lateral sclerosis; <110.9 pg/ml had a negative predictive value of 0.48. In a specialized clinic, neurofilament light chain is largely confirmatory to clinical judgement in diagnosing amyotrophic lateral sclerosis and has limited ability to exclude alternative diagnoses. The current, important, value of neurofilament light chain is its potential to stratify patients with amyotrophic lateral sclerosis by disease activity and as a biomarker in therapeutic trials.

Urine and serum S100A8/A9 and S100A12 associate with active lupus nephritis and may predict response to rituximab treatment.

BACKGROUND: Approximately 30% of patients with the systemic autoimmune/inflammatory disorder systemic lupus erythematosus (SLE) develop lupus nephritis (LN) that affects treatment and prognosis. Easily accessible biomarkers do not exist to reliably predict renal disease. The Maximizing SLE Therapeutic Potential by Application of Novel and Systemic Approaches and the Engineering Consortium aims to identify indicators of treatment responses in SLE. This study tested the applicability of calcium-binding S100 proteins in serum and urine as biomarkers for disease activity and response to treatment with rituximab (RTX) in LN. METHODS: S100A8/A9 and S100A12 proteins were quantified in the serum and urine of 243 patients with SLE from the British Isles Lupus Assessment Group Biologics Register (BILAG-BR) study and 48 controls matched for age using Meso Scale Discovery's technology to determine whether they perform as biomarkers for active LN and/or may be used to predict response to treatment with RTX. Renal disease activity and response to treatment was based on BILAG-BR scores and changes in response to treatment. RESULTS: Serum S100A12 (p<0.001), and serum and urine S100A8/A9 (p<0.001) levels are elevated in patients with SLE. While serum and urine S100 levels do not correlate with global disease activity (SLE Disease Activity Index), levels in urine and urine/serum ratios are elevated in patients with active LN. S100 proteins perform better as biomarkers for active LN involvement in patients with SLE who tested positive for anti-double-stranded DNA antibodies. Binary logistic regression and area under the curve analyses suggest the combination of serum S100A8/A9 and S100A12 can predict response to RTX treatment in LN after 6 months. CONCLUSIONS: Findings from this study show promise for clinical application of S100 proteins to predict active renal disease in SLE and response to treatment with RTX.