Maximizing ATPG Diagnosis Resolution on Unique Single Failing Devices

Unique single failing device is common for customer returns and reliability failures. When the initial and iterative Automatic Test Pattern Generator (ATPG) could not provide a sufficient diagnostic resolution, it can become quite challenging for the analyst to determine the failure mechanism in an efficient and effective way. Fault isolation could be performed in combination with the diagnosis results but there are cases with mismatch between the results (location, fault type, suspect nets). When the diagnostic resolution is low, the probability for such mismatches are high. This paper proposes an approach to increase the diagnostic resolution by utilizing a high-resolution targeted pattern (HRT) and single shot logic (SSL) patterns. Two cases will be discussed in the paper to highlight this approach and show in detail how it was utilized on actual failing units.

The PATHFINDER Study: Assessment of the Implementation of an Investigational Multi-Cancer Early Detection Test into Clinical Practice

To examine the extent of the evaluation required to achieve diagnostic resolution and the test performance characteristics of a targeted methylation cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test, ~6200 participants ≥50 years with (cohort A) or without (cohort B) ≥1 of 3 additional specific cancer risk factors will be enrolled in PATHFINDER (NCT04241796), a prospective, longitudinal, interventional, multi-center study. Plasma cfDNA from blood samples will be analyzed to detect abnormally methylated DNA associated with cancer (i.e., cancer “signal”) and a cancer signal origin (i.e., tissue of origin). Participants with a “signal detected” will undergo further diagnostic evaluation per guiding physician discretion; those with a “signal not detected” will be advised to continue guideline-recommended screening. The primary objective will be to assess the number and types of subsequent diagnostic tests needed for diagnostic resolution. Based on microsimulations (using estimates of cancer incidence and dwell times) of the typical risk profiles of anticipated participants, the median (95% CI) number of participants with a “signal detected” result is expected to be 106 (87–128). Subsequent diagnostic evaluation is expected to detect 52 (39–67) cancers. The positive predictive value of the MCED test is expected to be 49% (39–58%). PATHFINDER will evaluate the integration of a cfDNA-based MCED test into existing clinical cancer diagnostic pathways. The study design of PATHFINDER is described here.

A prespecified interim analysis of the PATHFINDER study: Performance of a multicancer early detection test in support of clinical implementation.

3070 Background: A multi-cancer early detection (MCED) test that uses targeted methylation-based cfDNA technology to detect cancer and predict cancer signal origin (CSO) has potential to efficiently identify malignancies for which effective screening modalities do not exist. A previous version of a blood-based MCED test demonstrated favorable classification and test characteristics. Samples from the ongoing PATHFINDER study were reanalyzed in a prespecified interim analysis to evaluate performance of a more recent version of the test with an updated classifier (eg, updated CSO localization, hematological signal threshold) that is planned for clinical implementation as a general multi-cancer screening tool. Methods: PATHFINDER (NCT04241796) is an interventional, prospective study in which results (cancer signal detected/not detected and predicted CSO) using a previous version of the MCED test are returned to investigators, and those with a signal detected undergo further diagnostic testing. In this prespecified interim analysis, samples from those enrolled as of October 6, 2020 were reanalyzed with the more recent version of the MCED test (these results were not returned to investigators). The positive predictive value (PPV) for cancer detection, overall CSO accuracy, and concordance between the two test versions were assessed. Results: A total of 4011/4047 (99%) participants (pts) were analyzable (mean [SD] age 63.9 [8.7] years, 62% female, 92% white, 24% with prior cancer history, 39% ever smoker [4% current], 6% with genetic cancer predisposition). Cancer signal was detected in 0.95% (38/4011). A total of 27/38 also had signal detected by the previous version of the MCED test, including 19 who reached diagnostic resolution (13 with cancer diagnosis and 6 without); 11/38 were discordant positives. Nine different cancer types were detected in the 13 pts (2 stage I, 3 stage II, 2 stage III, and 3 stage IV); 1 had no AJCC stage expected, 1 metastatic recurrence and 1 stage evaluation underway. A conservative minimal PPV assuming all discordant positives are false positives, was 43.3% (13/30, 95% CI 27.4-60.8%) based on 19 pts with diagnostic resolution and 11 discordant positives. High negative percent agreement (PA) 99.7% (99.5-99.8%) between the two test versions was observed. Positive PA of 43.5% (95% CI, 31.9-55.9%) was consistent with the more stringent threshold for hematologic signal in the recent MCED version, as most discrepant cases had hematologic CSO with the previous MCED test. Among 13 detected cancers, accuracy of the top CSO prediction was 92.3% (12/13, 95% CI 66.7-99.6%). Conclusions: In this prespecified interim analysis, the more recent version of the MCED test detected cancers with high PPV and high accuracy of CSO prediction, supporting readiness for use in clinical practice. Full enrollment cohort data will be available at the meeting. Clinical trial information: NCT04241796.

Interim results of PATHFINDER, a clinical use study using a methylation-based multi-cancer early detection test.

3010 Background: PATHFINDER (NCT04241796) is an interventional, prospective study evaluating implementation of a blood-based multi-cancer early detection (MCED) test that uses targeted methylation-based cfDNA analysis to detect multiple cancer types and simultaneously predict cancer signal origin (CSO). We present a prespecified interim analysis of PATHFINDER evaluating an MCED test in a clinical setting. Methods: Participants (pts; ≥50y) were enrolled into 2 risk cohorts: non-elevated and elevated (smoking history, prior cancer [ > 3y post treatment], or genetic predisposition). MCED test results (cancer signal detected/not detected) were returned to investigators; pts with a signal detected also received a CSO prediction and underwent further diagnostic testing by their medical team. The primary objective was to assess the extent of diagnostic testing needed to achieve diagnostic resolution (eg, time to resolution, number/type of tests). Secondary endpoints included positive predictive value (PPV) and a measure of test satisfaction (following diagnostic resolution [signal detected] and post test [signal not detected]). Results: PATHFINDER consented 6796 pts before closing accrual on 12/4/20; as of October 6, 2020, 4086 consented, 4047 enrolled, and 4033 analyzable pts were included in the interim analysis (62.4% female, 92.1% white). Two study-related adverse events (anxiety of mild severity) were reported. Cancer signal was detected in 1.5% (62/4033) of pts; 40/62 reached diagnostic resolution to date. Kaplan-Meier estimate of median time to resolution was 78 (95% CI, 54-151) days. Among 40 pts that reached diagnostic resolution, ≥1 imaging test was performed in 93% (37/40); ≥1 invasive procedure was performed in 72% (13/18) versus 18% (4/22) of pts with diagnostic resolution of cancer versus no cancer, respectively. Based on results to date, PPV was 45% (95% CI, 30.7-60.2%; 18/40). Of 18 cancer diagnoses, 11 were solid tumors (3 stage IV, 6 stages I-III, 1 metastatic recurrence, 1 missing stage), and 7 were hematologic malignancies (1 stage IV, 4 stages I-III, 2 without AJCC stage). Accuracy of the top CSO prediction in true positives was 82.4% (95% CI, 59.0-93.8%; 14/17). Most pts were satisfied with the test (43.7% extremely satisfied, 30.7% very satisfied, 14.6% satisfied). Signal detection rate and test satisfaction were similar in the 2 risk cohorts; PPV tended to be higher in the elevated risk cohort, as expected. Conclusions: An interim analysis of this return of results study demonstrated promising MCED test results. Of 40 pts achieving diagnostic resolution, nearly half had a diagnostic workup confirming cancer; CSO was predicted with high accuracy for detected cancers. Taken together with the rarity of adverse events and high test satisfaction, these results support the feasibility of clinical implementation. Full enrollment cohort data will be available at the meeting. Clinical trial information: NCT04241796.

A Descriptive Analysis for a Collaborative Work Process: A Complex Real Medical Case in the Radiological Field

Collaborative acts occur daily in every human activity. In the case of medicine, and particularly in the diagnostic decision process, these acts are very frequent and occur naturally. It is very important to properly understand how these collaborative acts are developed in order to provide tools that facilitate and support them. In this article, we describe this collaborative work process in the framework of a complex real medical case in the radiological field. Usually, complex cases require several specialists. In this work, we have analyzed the intervention of several specialists and the exchange and interaction of different reasoning strategies among specialists, while considering their temporal dimension. Two types of collaboration are presented in the case analysis (1) exchange between specialists from different specialties and (2) exchange between specialists from the same specialty. The method of analysis follows five steps: (1) Case synopsis, (2) Temporal representation of the case, (3) Analysis of the general decision in the case, (4) Analysis of the reasoning in the medical case using the different strategies, and (5) Analysis of radiological collaboration. We have presented different reasoning strategies, data, hypotheses and complementary tests from different sources in the diagnostic resolution process and we have shown that collaboration is present during the entire process. The temporality and the intervention of different specialists is shown using a graphical representation. We have focused special attention on radiological collaboration, and have shown how a radiological diagnosis is achieved. We have discussed different elements present in the collaboration process. Our study has produced meta-knowledge derived from these exchanges that is of value in the context of artificial intelligence progress, in particular for the comprehension of collaborative medical work.

Multicenter Evaluation of the Clinical Performance and the Neutralizing Antibody Activity Prediction Properties of ten high throughput serological assays used in Clinical Laboratories.

As the COVID-19 pandemic second wave is emerging, it is of the upmost importance to screen the population immunity in order to keep track of infected individuals. Consequently, SARS-CoV-2 immunoassays with high specificity and positive predictive values are needed to obtain an accurate epidemiological picture. As more data accumulate about the immune responses and the kinetics of neutralizing antibody (nAb) production in SARS-CoV-2 infected individuals, new applications are forecasted for serological assays such as nAb activity prediction in convalescent plasma from recovered patients. This multicenter study, involving six hospital centres, determined the baseline clinical performances, reproducibility and nAb level correlations of ten commercially available immunoassays. In addition, three lateral flow chromatography assays were evaluated as these devices can be used in logistically challenged area. All assays were evaluated using the same patient panels in duplicate thus enabling accurate comparison of the tests. Seven immunoassays examined in this study were shown to have excellent specificity (98 to 100%) and good to excellent positive predictive values (82 to 100%) when used in a low (5%) seroprevalence setting. We observed sensitivity values as low as 74% and as high as 95% at ≥15 days post symptom onset. The determination of optimized cut-off values through ROC curves analyses had a significant impact on the diagnostic resolution of several enzyme immunoassays by increasing the sensitivity significantly without a large trade-off in specificity. We found that Spike-based immunoassays seems to be better correlates of nAb activity. Finally, the results reported here will add up to the general knowledge of the inter-laboratory reproducibility of clinical performance parameters of immunoassays and provide new evidence about nAb activity prediction.