Noninvasive Screening Test Research Articles

Value of Non-invasive Prenatal Test (NIPT) for comprehensive fetal aneuploidies screening

Value of Non-invasive Prenatal Test (NIPT) for comprehensive fetal aneuploidies screening

FIT as a Comparator for Evaluating the Effectiveness of New Non-invasive CRC Screening Test.

Randomized Controlled Trials (RCT) demonstrated that guaiac-based fecal occult blood test (gFOBT), sigmoidoscopy, or colonoscopy are effective at reducing colorectal cancer (CRC) risk and mortality. Even if the impact of fecal immunochemical test (FIT) has not been evaluated within population-based RCT with mortality as the outcome, the results of comparative analyses with gFOBT provide strong indirect evidence of its effectiveness. Extensive information is also available on sensitivity and specificity of FIT, compared with gFOBT. FIT has almost universally replaced gFOBT in organized screening programs worldwide. Using FIT as a comparator is an efficient way to evaluate the effectiveness of new tests, with respect to test performance and relevant intermediate outcomes such as rates of interval cancer and late-stage cancer incidence. Direct comparison with FIT in the pre-screening evaluation of the accuracy of the new test will guide selection of the cut-off of the new test, and document the potential gain in sensitivity. Comparison in cross-sectional single-round screening evaluation can either use paired or parallel designs. Only parallel designs allow direct comparisons ofparticipation rates. Relative accuracy can be derived in both designs with an assumption of similar colorectal cancer and precursor prevalence between groups in parallel designs. Finally, multiple-rounds prospective comparison will document potential effect on risk of CRC and precancerous lesions, and on absolute reductions in late-stage incidence as a proxy of mortality. This paper provides an overview of evidence and rationale for using FIT as a comparator for evaluating new non-invasive tests with repeated testing at short intervals.

Impact of the COVID-19 pandemic on adherence to diagnostic colonoscopy after a positive non-invasive screening test for colorectal cancer in two Indiana healthcare systems

ObjectiveTo describe trends in the use of non-invasive tests (NIST) and the interval between a positive NIST and diagnostic colonoscopy. MethodsUsing a retrospective time-trend design, we examined medical records of patients within two large Indiana integrated healthcare systems who had a positive NIST between January 2019 and June 2021 and quantified the proportion of patients who had not completed colonoscopy within 60, 90, and 180 days to determine the interval between NIST result and diagnostic colonoscopy in days. ResultsOf 1379 patients with positive NISTs, 930 (68 %) underwent diagnostic colonoscopy during the 30-month study timeframe. Median time to colonoscopy completion was significantly longer in 2020 compared to 2019 (50 vs. 37 days, p < 0.01) and 2021 (46 days, p = 0.06). The proportion of patients completing colonoscopy within 90 days of a positive FIT in 2019, 2020, and 2021 were 79 %, 83 %, and 72 %, respectively (p = 0.63), and were 86 %, 78 %, and 84 %, respectively, after positive FIT/DNA (p = 0.07). Median time to diagnostic colonoscopy completion was significantly longer in 2020, likely due to the COVID-19 pandemic. ConclusionsStudies of outcomes in those who declined or delayed colonoscopy in 2020 are needed to estimate the potential subsequent colorectal cancer disease burden.

An Adjustable Positivity Threshold for Non-invasive Screening Tests for Colorectal Neoplasms Can Improve Screening Program Effectiveness and Feasibility.

In two-step population screening for colorectal cancer (CRC), a simple non-invasive test, commonly a fecal immunochemical test for hemoglobin (FIT), is first undertaken to predict, based on the fecal hemoglobin concentration (f-Hb), who is more likely to have colorectal neoplasia and needs colonoscopy. To evaluate the importance of being able to adjust the f-Hb threshold that triggers follow-up colonoscopy (the "positivity threshold"), we evaluated the predictive value of f-Hb for colorectal neoplasia and its implications for the configuration of new non-invasive tests. A literature review was conducted on the use of quantitative FIT to select the positivity threshold, followed by using f-Hb from a large population to model how adjusting the positivity threshold enabled achievement of the desired program outcomes in a feasible manner. The literature review and the modeling found that while the f-Hb positivity threshold is predictive for colorectal neoplasia across a wide range of f-Hb, there is a complex relationship between program outcomes and f-Hb. The threshold determines not just clinical accuracy (including true- and false-positive results for CRC and/or advanced precursor lesions), but also the colonoscopy workload. A lower f-Hb threshold is associated with a higher sensitivity for neoplasia but a lower specificity and a heavier load of follow-up colonoscopies. Consequently, the threshold determines a program's impact on population CRC mortality and incidence, but also its feasibility and cost-effectiveness within a health-care system. We are entering a new era of non-invasive screening tests, where multiple biomarkers found in biological samples such as blood as well as feces, are being developed and evaluated. These typically specify a non-transparent algorithm, developed with machine learning, to provide a predictive dichotomous positive/negative result with a fixed associated clinical accuracy and colonoscopy workload. This will restrict use of new tests in jurisdictions where the accuracy and workload implications do not match the desired screening program outcomes. However, similar to flexible FIT positivity thresholds, it would be ideal if new tests also provide capacity for screening program providers to select the positivity threshold that delivers their desired screening outcomes in a feasible manner. How marketing, distribution and reimbursement of non-invasive tests are approved, funded and implemented varies widely across jurisdictions and must be taken into account.

S375 Real-World Adherence to Repeat Testing for Stool-Based Non-Invasive Colorectal Cancer Screening Tests Among Individuals With Average Risk

S375 Real-World Adherence to Repeat Testing for Stool-Based Non-Invasive Colorectal Cancer Screening Tests Among Individuals With Average Risk

S460 Non-Invasive Screening Tests for Colorectal Cancer: Analyzing the Performance of FIT and Multi-Target Stool DNA Test

S460 Non-Invasive Screening Tests for Colorectal Cancer: Analyzing the Performance of FIT and Multi-Target Stool DNA Test

Study association of urinary Club Cell Protein with air pollution-related pulmonary function compromised among children

BackgroundChildhood exposure to air pollution exacerbates respiratory conditions and even carries deleterious effects on lung functions in adulthood. It is desirable to establish a non-invasive screening test for children to predict early lung insult with air pollution exposure. The association between serum club cell protein (CC16) and obstructive airway diseases is known, but the same is not explored with air-pollution-related lung insult and pulmonary function test (PFT) parameters. AimTo investigate the association between urinary CC16 and PFT parameters in children exposed to differing levels of air pollution. MethodsThis cross-sectional study recruited 107 children from critically-polluted area (CPA) and 96 age-sex-matched children from non-polluted area (NPA). PFT and urinary CC16 were determined with standard techniques. Air quality parameters were estimated with adherence to National Ambient Air Quality Standards (NAAQS). ResultsCPA was observed with 2.5 times poorer Air-Quality-Index compared to NPA. Urinary CC16 levels of children were four-fold higher in CPA compared to NPA (p < 0.001). CPA children were significantly deprived in PFT parameters [FVC(L)-1.86 v/s 2.02, p = 0.01; FEV1(L/s)-1.71 v/s 1.86, p = 0.01 & PEFR(L/s)- 3.25 v/s 3.69, p < 0.001]. While adjusted for physiological parameters, urinary CC16 observed with significant negative association with PFT parameters (FVC: β = −0.02, p=0.03; FEV1: β = −0.03, p=0.001 & FEF25–75 %: β = −0.05, p=0.04). ConclusionThe significant decline in lung function parameters and elevated urinary CC16 levels among children in polluted areas underscore the need for further research to validate urinary CC16 as a reliable screening tool for respiratory health monitoring among children.

The Effect of Self-Reported Race on Noninvasive Prenatal Screening Test Characteristics.

Low fetal fraction (FF) on cell-free DNA (cfDNA)-based noninvasive prenatal screening (NIPS) is a common etiology for indeterminate results. As maternal Black race is implicated as a risk factor for low FF and more indeterminate results, we sought to evaluate this association. This was a single-institution, retrospective cohort study of cfDNA-based NIPS performed between May 2017 and May 2022 with complete clinical data abstraction. We compared FF, indeterminate rates, and total cfDNA concentration among self-reported Black, White, and Other groups from NIPS results from 2017 to 2022 with full clinical data abstraction. Using linear regression and interaction testing, we evaluated associations between self-reported race, FF, indeterminate rate, and total cfDNA concentration. In total, 1,591 participants met the inclusion criteria; 70.8% (n = 1,126) self-identified as White, 6.9% (n = 110) as Black, and 22.3% (n = 355) self-identified with another race. Mean FF was not different between the White, Black, or Other groups (11.8 vs. 11.2 vs. 11.7%, respectively, p = 0.52). This remained true after adjusting for body mass index (BMI), gestational age (GA) at draw, and fetal sex (all p > 0.17). Interaction testing for FF and total cfDNA by race with BMI, GA at draw, and fetal sex demonstrated no effect modification. In our population, maternal self-identified race, particularly Black race, does not affect FF. Biological plausibility for race-based differences on clinical tests requires ongoing thoughtful consideration. · NIPS is widely used to screen for fetal aneuploidy.. · FF is an important test metric, and low FF is associated with adverse outcomes, like aneuploidy.. · In existing studies, Black race is implicated as a risk factor for lower FF.. · Our study found no differences in FF between groups by self-reported race.. · Biological plausibility for race-based differences on clinical tests requires ongoing consideration..

Prospective Analysis of urINe LAM to Eliminate NTM Sputum Screening (PAINLESS) study: Rationale and trial design for testing urine lipoarabinomannan as a marker of NTM lung infection in cystic fibrosis.

Routine screening for nontuberculous mycobacterial (NTM) lung disease is dependent on sputum cultures. This is particularly challenging in the cystic fibrosis (CF) population due to reduced sputum production and low culture sensitivity. Biomarkers of infection that do not rely on sputum may lead to earlier diagnosis, but validation trials require a unique prospective design. The rationale of this trial is to investigate the utility of urine lipoarabinomannan (LAM) as a test to identify people with CF with a new positive NTM culture. We hypothesize that urine LAM is a sensitive, non-invasive screening test with a high negative predictive value to identify individuals with a relatively low risk of having positive NTM sputum culture. This is a prospective, single-center, non-randomized observational study in adults with CF, 3 years of negative NTM cultures, and no known history of NTM positive cultures. Patients are followed for two year-long observational periods with the primary endpoint being a positive NTM sputum culture within a year of a positive urine LAM result and a secondary endpoint of a positive NTM sputum culture within 3 years of a positive urine LAM result. Study implementation includes remote consent and sample collection to accommodate changes from the COVID-19 pandemic. This report describes the study design of an observational study aimed at using a urine biomarker to assist in the diagnosis of NTM lung infection in pwCF. If successful, urine LAM could be used as an adjunct to traditional sputum cultures for routine NTM screening.

Evolving trends in CT colonography: A 10-year analysis of use and associated factors

PurposeComputed tomographic colonography (CTC) is a non-invasive screening test for colorectal cancer (CRC) with high sensitivity and low risk of complications. We used a nationally representative sample of screening-eligible adults to examine trends in and factors associated with CTC use. MethodsWe examined CTC use among 58,058 adults in the National Health Interview Survey in 2010, 2015, 2018, 2019, and 2021. For each survey year, we estimated CTC use by sociodemographic and health factors. We used multivariable logistic regression to identify factors associated with CTC use. ResultsA total of 1.7 % adults reported receiving CTC across all survey years. CTC use was similar in 2010 (1.3 %), 2015 (0.8 %), 2018 (1.4 %), and 2019 (1.4 %) but increased in 2021 (3.5 %, p < 0.05). In multivariable analysis, survey year 2021 [vs. 2010, odds ratio (OR) 2.51, 95 % confidence interval (CI) 1.83–3.43], Hispanic (OR 1.73, 95 % CI 1.34–2.23), non-Hispanic Black (OR 2.07, 95 % CI 1.67–2.57), and household income <200 % federal poverty level (vs. >400 %, OR 1.25, 95 % CI 1.01–1.57) was associated with CTC use. Further, adults with a history of diabetes (OR 1.20, 95 % CI 1.01–1.45), chronic obstructive pulmonary disease (OR 1.58, 95 % CI 1.25–1.99), cancer (OR 1.29, 95 % CI 1.05–1.58), or past-year hospital admissions (OR 1.44, 95 % CI 1.18–1.78) were more likely to receive CTC. ConclusionCTC use remained low from 2010 to 2019 but increased in 2021. CTC use was more frequent among adults with chronic health conditions, minorities, and adults with lower income, and may help reduce disparities in CRC screening.

Serum proteome signatures associated with liver steatosis in adolescents with obesity.

Childhood obesity, a pressing global health issue, significantly increases the risk of metabolic complications, including metabolic dysfunction associated with steatotic liver disease (MASLD). Accurate non-invasive tests for early detection and screening of steatosis are crucial. In this study, we explored the serum proteome, identifying proteins as potential biomarkers for inclusion in non-invasive steatosis diagnosis tests. Fifty-nine obese adolescents underwent ultrasonography to assess steatosis. Serum samples were collected and analyzed by targeted proteomics with the Proximity Extension Assay technology. Clinical and biochemical parameters were evaluated, and correlations among them, the individuated markers, and steatosis were performed. Receiver operating characteristic (ROC) curves were used to determine the steatosis diagnostic performance of the identified candidates, the fatty liver index (FLI), and their combination in a logistic regression model. Significant differences were observed between subjects with and without steatosis in various clinical and biochemical parameters. Gender-related differences in the serum proteome were also noted. Five circulating proteins, including Cathepsin O (CTSO), Cadherin 2 (CDH2), and Prolyl endopeptidase (FAP), were identified as biomarkers for steatosis. CDH2, CTSO, Leukocyte Immunoglobulin Like Receptor A5 (LILRA5), BMI, waist circumference, HOMA-IR, and FLI, among others, significantly correlated with the steatosis degree. CDH2, FAP, and LDL combined in a logit model achieved a diagnostic performance with an AUC of 0.91 (95% CI 0.75-0.97, 100% sensitivity, 84% specificity). CDH2 and FAP combined with other clinical parameters, represent useful tools for accurate diagnosis of fatty liver, emphasizing the importance of integrating novel markers into diagnostic algorithms for MASLD.

Salivary metabolomic biomarkers for esophageal and gastric cancers by liquid chromatography-mass spectrometry.

Early detection of esophageal and gastric cancers is essential for patients' prognosis; however, optimal noninvasive screening tests are currently not available. Saliva is a biofluid that is readily available, allowing for frequent screening tests. Thus, we explored salivary diagnostic biomarkers for esophageal and gastric cancers using metabolomic analyses. Saliva samples were collected from patients with esophageal (n = 50) and gastric cancer (n = 63), and patients without cancer as controls (n = 20). Salivary metabolites were analyzed by liquid chromatography-mass spectrometry to identify salivary biomarkers. We also examined the metabolic profiles of gastric cancer tissues and compared them with the salivary biomarkers. The sensitivity of the diagnostic models based on salivary biomarkers was assessed by comparing it with that of serum tumor markers. Additionally, using postoperative saliva samples collected from patients with gastric cancer, we analyzed the changes in the biomarkers' concentrations before and after surgery. Cytosine was detected as a salivary biomarker for gastric cancer, and cytosine, 2-oxoglutarate, and arginine were detected as salivary biomarkers for esophageal cancer. Cytidine, a cytosine nucleotide, showed decreased concentrations in gastric cancer tissues. The sensitivity of the diagnostic models for esophageal and gastric cancers was 66.0% and 47.6%, respectively, while that of serum tumor markers was 40%. Salivary cytosine concentration increased significantly postoperatively relative to the preoperative value. In summary, we identified salivary biomarkers for esophageal and gastric cancers, which showed diagnostic sensitivity at least comparable to that of serum tumor markers. Salivary metabolomic tests could be promising screening tests for these types of cancer.

The Electrophysiological Evaluation of Small Fiber Neuropathy in Symptomatic Patients with Vitamin B12 Deficiency before and after Treatment

ABSTRACT Background: Small fiber neuropathy (SFN) leads to sensory and autonomic dysfunction by affecting small-diameter myelinated A-delta and unmyelinated C fibers, with vitamin B12 deficiency identified as one of its causes. Objectives: To achieve early diagnosis of SFN in patients with vitamin B12 deficiency and to illustrate the impact of vitamin B12 replacement therapy using noninvasive electrophysiological tests. Materials and Methods: Patients aged 18 to 65 with vitamin B12 deficiency experiencing neuropathic pain or autonomic symptoms were included. A control group consisted of asymptomatic, healthy volunteers with normal B12 levels. Neurological examinations, cutaneous silent period (CSP), sympathetic skin response (SSR), and cardiovascular autonomic tests (R-R interval variability during the Valsalva maneuver [RRIV-VM] and standing [RRIV-S]) were performed at admission and six months later. Patients received 1000 mcg cyanocobalamin intramuscularly daily for one week, weekly for one month, and monthly for three months. Results: The final analyses included 25 patients and 25 controls. At admission, patients had significantly longer CSP and SSR latencies compared to controls (P = 0.047, P &lt; 0.001) and shortened CSP durations (P = 0.043). The SSR amplitude was lower in patients but not significantly (P = 0.823). Post-treatment, CSP latency, CSP duration, and SSR latency significantly improved (P &lt; 0.001, P = 0.002, P &lt; 0.001). Positive symptoms and autonomic symptoms improved significantly after treatment (P = 0.039, P = 0.016). The number of patients with neuropathic pain significantly decreased (P = 0.008). Conclusion: CSP latency, CSP duration, and SSR latency are effective, non-invasive, and cost-effective screening tests for diagnosing SFN in individuals with B12 deficiency. These tests are also valuable for monitoring the progression of SFN following vitamin B12 replacement therapy. The study supports the use of these noninvasive electrophysiological tests to enhance early diagnosis and treatment efficacy in SFN associated with vitamin B12 deficiency.

Real-world multi-target stool DNA longitudinal adherence for colorectal cancer re-screening in a large, national population.

e15633 Background: Colorectal cancer (CRC) is the fourth most diagnosed cancer, as well as the second leading cause of cancer death in the United States – with an estimated 152,810 diagnoses and 53,010 fatal cases in 2024. Regular screening and early detection can reduce CRC incidence and improve overall survival; however, recent national survey data (2021) demonstrate that only 59% of the US screen-eligible population (≥ age 45) is up to date. Home-based, non-invasive CRC screening test options, such as the multi-target stool DNA (mt-sDNA) test, have the potential to improve patient outcomes and overcome CRC screening adherence barriers at multiple levels. Given that the recommended interval for mt-sDNA is three years, a better understanding of use in repeat users is warranted. We evaluated the effective rescreen rate of previous mt-sDNA test users. Methods: In this retrospective cohort study, we included patients between the ages of 45 and 75 years who were shipped an mt-sDNA test kit between January 1st – December 31st, 2023, and had previously completed mt-sDNA screening with a negative result &gt; 2.5 years prior. Our primary variable of interest was mt-sDNA completion rate on repeat testing, defined as kit receipt with a valid result within 120 days of the shipment date. Regression analysis was performed to determine baseline characteristics associated with repeat test completion rate. Results: During the analysis period, a total of 481,748 patients who met the inclusion criteria received an mt-sDNA kit. The majority of the cohort was female (61.4%) and between the ages of 65-75 years (50.9%). Overall repeat test completion rate was 83.6%, with the average time to kit return being 18.9 days. Completion rates were similar between males (83.8%) and females (83.6%), and patients receiving included navigation support via mobile phones demonstrated the shortest average time to kit return (18.7 days). Completion rates increased concordantly with patient age: 81.6%, (45-49 years), 82.2% (50-64 years), and 85% (65-75 years). For first-time rescreen participants (2nd lifetime mt-sDNA test), the completion rate was 83.1%. For second-time rescreen participants (3rd lifetime mt-sDNA test), the completion rate was even higher at 93.6%. Logistic regression analyses revealed that patients re-screening for a second-time were three times more likely to return the mt-sDNA kit for CRC screening (OR = 3.118; p &lt; 0.001). Conclusions: Data from this large, retrospective cohort study revealed that repeat CRC screening with the mt-sDNA test is associated with high adherence to triennial follow-up among participants. suggesting a high-level of perceived patient confidence in repeat performance of the mt-sDNA test. These novel data provide relevant insights regarding strong patient willingness to continue with home-based, non-invasive mt-sDNA testing over multiple cycles of average-risk CRC screening.

A blood-based screening test for colorectal cancer (CRC) using methylation sequencing.

e15089 Background: Diagnosis of CRC is biased towards later stages in India (3.8% Stage I, 16.7% Stage II, 50.7% Stage III, 28.8% Stage IV), and five-year survival at &lt; 40% is one of the lowest in the world. A blood-based non-invasive screening test for CRC using cell-free DNA (cfDNA) methylation sequencing is developed here from the blood of 212 controls and 67 treatment naive CRC patients from 21 sites across India and processed in Strand’s reference lab in Bangalore. Methods: Steps involved cfDNA extraction, NEB Enzymatic Methyl-Seq library preparation, Twist Human Methylome hybridisation capture, 2x150bp sequencing on NovaSeq 6000/X. Methylation + fragmentomic features were calculated for each target region. Samples were split randomly into a leave-in set of 170 controls + 53 cancers (I: 8, II 16, III: 23, IV: 6) and a leave-out set of 42 controls + 14 cancers, (I: 5, II: 4, III: 2, IV: 3) with 20 rounds of 4-fold cross-validation done on the leave-in set (random splits). Feature selection per fold was performed using the KS test without access to ¼ of the leave-in set and to the entire leave-out set. Gradient boosted trees with monotonic constraints reflecting the expected association of the scores with cancer were used to build “explainable” models. Test robustness was assessed using differentially methylated regions (DMRs) from other studies, and by assessing predictability using sample metadata alone. Results: At a 91% specificity level, the ensemble model had a median sensitivity of 62.5% for Stage I (95%CI 38%-86%), 87% for Stage II (95% CI 75%-95%), 87% for Stage III (95% CI 75%-95%) and 83.4% for Stage IV (95% CI 84%-100%) in cross-validation, and 60% for Stage I (95%CI 60%-80%), 100% for Stage II (95% CI 80%-100%), 100% for Stage III (95% CI 100%-100%) and 100% for Stage IV (95% CI 100%-100%) on the leave-out set. At a ~98% specificity level, the model had a median sensitivity of 37.5% for Stage I (95%CI 37%-50%), 69% for Stage II (95% CI 56%-75%), 69% for Stage III (95% CI 60%-84%) and 67% for Stage IV (95% CI 50%-84%) in cross-validation, and 40% for Stage I (95%CI 20%-60%), 75% for Stage II (95% CI 75%-100%), 100% for Stage III (95% CI 100%-100%) and 100% for Stage IV (95% CI 66%-100%) with a slight decrease in specificity to 95.2% on the leave-out set. Using DMRs derived from TCGA data and other publications, yielded a comparable (to our models) cross-validation area under the curve (AUC: 0.93-0.95). Cross-validation performance using only the sample metadata in table 1 and without access to the data was significantly poorer (AUC 0.75-0.81). Conclusions: cfDNA-based methylation profiles are consistent across studies and ethnicities, leading to robust and “explainable” CRC screening predictions. [Table: see text]

A novel, noninvasive, multimodal screening test for the early detection of precancerous lesions and colorectal cancers using an artificial intelligence–based algorithm.

3627 Background: Colorectal cancer (CRC) ranks as the second leading cause of cancer-related mortality worldwide, and its incidence is increasing in younger populations. Detection of early-stage CRC and its precursor lesions, such as advanced adenomas (AA), is crucial for successful treatment and reduces CRC-related mortality. Although non-invasive methods for early detection are available and increase screening compliance, their performance with respect to detection of advanced adenomas and early-stage cancers is limited. Here, we describe a novel and non-invasive stool-based approach combining diagnostic biomarkers with an algorithm generated by machine learning/artificial intelligence (ML/AI) resulting in significantly improved diagnostic performance for the detection of not only CRC, but especially precancerous lesions like AA. Methods: Data were generated from a combined cohort of stool samples collected at 10 clinical sites in Europe (COLOFUTURE study) and 21 clinical sites in the US (eAArly DETECT study). The evaluable study cohort consists of 690 subjects, including 78 CRC, 146 AA, 147 with non-advanced adenoma (AD) and 319 normal colonoscopy negative control (NC) subjects (49% female, 51% male, average age 61.8 years). Results were compared with colonoscopy and pathology findings to determine sensitivity and specificity for detection of early-stage CRC and AA vs. AD and NC. Nucleic acids were extracted from stabilized stool samples using a silica bead-based extraction method. Expression of mRNA biomarkers was analyzed utilizing Real-Time PCR. Human hemoglobin was quantified using FIT. The Emerge Quantitative Evolution ML/AI platform was leveraged to develop classifiers capable of distinguishing CRC and AA from AD and NC. Results: Applying the combined approach of non-invasive diagnostic testing with an AI/ML generated algorithm, the sensitivity for detection of CRC overall was 92.3%. In addition, this method enabled AA detection with a sensitivity of 82.2%. Specificity turned out to be 90.1 % (AD+NC). Conclusions: This innovative, non-invasive, multimodal screening strategy based on self-collected stool samples which combines mRNA expression patterns and FIT analysis with an AI/ML-generated algorithm represents a substantial improvement in the effectiveness of non-invasive CRC screening. Such improvements in usability and performance leading to reliable detection of early-stage CRC and precursor lesions, such as advanced adenomas, are required for wide-spread availability and adaption of non-invasive screening tests to accepted clinically relevant usage and to prevent the development of CRC effectively.

Artificial Intelligence based Non-Invasive Pre-Diagnostic Screening Test for Anaemia using Conjunctiva Digital Images

Artificial Intelligence based Non-Invasive Pre-Diagnostic Screening Test for Anaemia using Conjunctiva Digital Images

Raman hyperspectroscopy of saliva and machine learning for Sjögren’s disease diagnostics

Sjögren's disease is an autoimmune disorder affecting exocrine glands, causing dry eyes and mouth and other morbidities. Polypharmacy or a history of radiation to the head and neck can also lead to dry mouth. Sjogren's disease is often underdiagnosed due to its non-specific symptoms, limited awareness among healthcare professionals, and the complexity of diagnostic criteria, limiting the ability to provide therapy early. Current diagnostic methods suffer from limitations including the variation in individuals, the absence of a single diagnostic marker, and the low sensitivity and specificity, high cost, complexity, and invasiveness of current procedures. Here we utilized Raman hyperspectroscopy combined with machine learning to develop a novel screening test for Sjögren's disease. The method effectively distinguished Sjögren's disease patients from healthy controls and radiation patients. This technique shows potential for development of a single non-invasive, efficient, rapid, and inexpensive medical screening test for Sjögren's disease using a Raman hyper-spectral signature.

Post-Blink Blur Time-A Simple Test to Detect Dry Eye-Related Visual Disturbances.

Background: Dry eye disease (DED) stands out as one of the most common eye conditions encountered in clinical settings. This study aimed to determine the diagnostic ability and feasibility of post-blink blur time (PBBT) in detecting patients with DED symptoms. Methods: The study included 200 subjects, 100 with and 100 without DED symptoms defined by the Schein questionnaire, who underwent assessment of DED signs [visual acuity, PBBT, conjunctival hyperemia, lid-parallel conjunctival folds-LIPCOF, tear film break-up time-TBUT, fluorescein corneal staining, and meibum score]. Results: DED subjects had a lower PBBT than controls (p < 0.001), with subjective (6 (1-45) s vs. 8 (1-70) s) and objective (6 (2-33) s vs. 8 (2-50) s) PBBT measurements being similar between repeats. The correlations between subjective and objective PBBT measurements were significantly positive (R = 0.873, p < 0.001). Subjective PBBT was negatively related to the Schein questionnaire (R = -0.217, p = 0.002), conjunctival hyperemia (R = -0.105, p = 0.035), and corneal staining (R = -0.153, p = 0.031), while positively related to the TBUT (R = 0.382, p < 0.001) and meibum score (R = 0.106, p = 0.033). Logistic regression analysis showed DED symptoms were significantly associated with subjective PBBT (AOR 0.91, p = 0.001), TBUT (AOR 0.79, p < 0.001), meibum score (AOR 0.65, p = 0.008), LIPCOF (AOR 1.18, p = 0.002) and corneal staining (AOR 1.14, p = 0.028). Conclusions: Subjective self-reported PBBT is a reliable and non-invasive screening test for evaluating time-wise changes in visual acuity and detecting a tear film dysfunction.

Machine learning-based identification of colorectal advanced adenoma using clinical and laboratory data: a phase I exploratory study in accordance with updated World Endoscopy Organization guidelines for noninvasive colorectal cancer screening tests.

The recent World Endoscopy Organization (WEO) guidelines now recognize precursor lesions of colorectal cancer (CRC) as legitimate screening targets. However, an optimal screening method for detecting advanced adenoma (AA), a significant precursor lesion, remains elusive. We employed five machine learning methods, using clinical and laboratory data, to develop and validate a diagnostic model for identifying patients with AA (569 AAs vs. 3228 controls with normal colonoscopy). The best-performing model was selected based on sensitivity and specificity assessments. Its performance in recognizing adenoma-carcinoma sequence was evaluated in line with guidelines, and adjustable thresholds were established. For comparison, the Fecal Occult Blood Test (FOBT) was also selected. The XGBoost model demonstrated superior performance in identifying AA, with a sensitivity of 70.8% and a specificity of 83.4%. It successfully detected 42.7% of non-advanced adenoma (NAA) and 80.1% of CRC. The model-transformed risk assessment scale provided diagnostic performance at different positivity thresholds. Compared to FOBT, the XGBoost model better identified AA and NAA, however, was less effective in CRC. The XGBoost model, compared to FOBT, offers improved accuracy in identifying AA patients. While it may not meet the recommendations of some organizations, it provides value for individuals who are unable to use FOBT for various reasons.