Multi-cancer Detection Research Articles

Aberrant fragmentomic features of circulating cell-free mitochondrial DNA as novel biomarkers for multi-cancer detection.

Fragmentomic features of circulating cell free mitochondrial DNA (ccf-mtDNA) including fragmentation profile, 5' end base preference and motif diversity are poorly understood. Here, we generated ccf-mtDNA sequencing data of 1607 plasma samples using capture-based next generation sequencing. We firstly found that fragmentomic features of ccf-mtDNA were remarkably different from those of circulating cell free nuclear DNA. Furthermore, region-specific fragmentomic features of ccf-mtDNA were observed, which was associated with protein binding, base composition and special structure of mitochondrial DNA. When comparing to non-cancer controls, six types of cancer patients exhibited aberrant fragmentomic features. Then, cancer detection models were built based on the fragmentomic features. Both internal and external validation cohorts demonstrated the excellent capacity of our model in distinguishing cancer patients from non-cancer control, with all area under curve higher than 0.9322. The overall accuracy of tissue-of-origin was 89.24% and 87.92% for six cancer types in two validation cohort, respectively. Altogether, our study comprehensively describes cancer-specific fragmentomic features of ccf-mtDNA and provides a proof-of-principle for the ccf-mtDNA fragmentomics-based multi-cancer detection and tissue-of-origin classification.

Perceptions of Multicancer Detection Tests Among Primary Care Physicians and Laypersons: A Qualitative Study.

Multicancer detection tests (MCDs) are blood-based tests designed to detect multiple cancer types. It is currently unclear whether these cancer screening tests improve mortality. To understand awareness of MCDs among providers and patients, as well as explore how they perceive the benefits, harms, and acceptability of MCDs, we have undertaken a focus group study in primary care physicians (PCPs) and laypersons to explore knowledge, attitudes, and expectations of cancer screening using MCDs. We conducted six focus groups with 45 PCP participants and 12 focus groups with 80 layperson participants. Participants were identified via a consumer research firm and found eligible following the completion of a screener survey. Moderators used a semi-structured guide containing open-ended questions and prompts to facilitate the discussion. Recordings were transcribed and coded line by line using a codebook developed based on questions and emerging discussion concepts, and emergent themes were identified. Both PCP and layperson participants felt the that benefits of MCDs included ease of use and potential ability to detect cancers early. However, they felt that additional data is needed to overcome some of the concerns related to MCDs. PCP participants expressed concerns related to lack of practice guidelines, cost of diagnostic follow-ups, privacy and insurance issues, fear/anxiety related to confirmation of MCD results, and malpractice liability related to perceived false negative test results. Layperson participants expressed concerns related to costs, insurance coverage, and privacy, as well as anxiety over the confirmation of a positive test result. There is a major need for more rigorous data regarding MCDs to inform the development of guidelines for use as cancer screening tools.

Design of randomized controlled trials to estimate cancer-mortality reductions from multicancer detection screening.

Determining whether screening with multicancer detection (MCD) tests saves lives requires randomized controlled trials (RCTs). To inform RCT design, we estimated cancer-mortality outcomes from hypothetical MCD RCTs. We used the Hu-Zelen model, previously used to plan the NLST, to estimate mortality reductions, sample-size, and power for 9 cancers for different RCT design parameters and MCD test parameters. Our base-case RCT with 5 yearly screens and 100,000 people ages 60-74 in each arm, who also undergo standard-of-care screens, has 87-89% power to detect an 9-10% mortality reduction (NNS = 578-724) over 7-9 years. The majority of prevented deaths were from lung-cancers (base-case (64-66%) and all sensitivity analyses), 8-10% from colorectal-cancer, and 26% from the other 7-cancers, mostly from stomach/ovary/esophagus (due to excellent stage-1 survival) and less from liver/pancreas (poor stage-1 survival) or head/neck-cancer/lymphoma (excellent stage-4 survival). There was limited power for mortality reductions at most individual cancer sites. Base-case findings were sensitive to test sensitivity, stage-shifts, and mean sojourn times in the preclinical state (especially for lung-cancer), but 90% power could be recovered by recruiting a substantially higher risk population. Large-scale MCD RCTs would have 89% power to detect a ∼10% cancer-mortality reduction over a relatively short 7-9 year timeframe from trial entry. The estimated NNS for MCD RCTs compares favorably to mammographic screening. Most prevented cancer-deaths in a well-powered MCD RCT would likely be from lung-cancer. Non-lung/CRC cancer sites could be a meaningful proportion of prevented cancer-deaths but power is insufficient to isolate non-lung-cancer mortality reductions.

Noninvasive multi-cancer detection using blood-based cell-free microRNAs.

Patients diagnosed with early-stage cancers have a substantially higher chance of survival than those with late-stage diseases. However, the option for early cancer screening is limited, with most cancer types lacking an effective screening tool. Here we report a miRNA-based blood test for multi-cancer early detection based on examination of serum microRNA microarray data from cancer patients and controls. First, a large multi-cancer training set that included 1,408 patients across 7 cancer types and 1,408 age- and gender-matched non-cancer controls was used to develop a 4-microRNA diagnostic model using 10-fold cross-validation. In three independent validation sets comprising a total of 4,875 cancer patients across 13 cancer types and 3,722 non-cancer participants, the 4-microRNA model achieved greater than 90% sensitivity for 9 cancer types (lung, biliary tract, bladder, colorectal, esophageal, gastric, glioma, pancreatic, and prostate cancers) and 75-84% sensitivity for 3 cancer types (sarcoma, liver, and ovarian cancer), while maintaining greater than 99% specificity. The sensitivity remained to be > 99% for patients with stage 1 lung cancer. Our study provided novel evidence to support the development of an inexpensive and accurate miRNA-based blood test for multi-cancer early detection.

Increasing power in screening trials by testing control-arm specimens: application to multicancer detection screening.

Cancer screening trials have required large sample sizes and long time-horizons to demonstrate cancer mortality reductions, the primary goal of cancer screening. We examine assumptions and potential power gains from exploiting information from testing control-arm specimens, which we call the "intended effect" (IE) analysis that we explain in detail herein. The IE analysis is particularly suited to tests that can be conducted on stored specimens in the control arm, such as stored blood for multicancer detection (MCD) tests. We simulated hypothetical MCD screening trials to compare power and sample size for the standard vs IE analysis. Under two assumptions that we detail herein, we projected the IE analysis for 3 existing screening trials (National Lung Screening Trial [NLST], Minnesota Colon Cancer Control Study [MINN-FOBT-A], and Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial-colorectal component [PLCO-CRC]). Compared with the standard analysis for the 3 existing trials, the IE design could have reduced cancer-specific mortality P values 6-fold (NLST), 33-fold (MINN-FOBT-A), or 260 000-fold (PLCO-CRC) or, alternately, reduced sample size (90% power) by 25% (NLST), 47% (MINN-FOBT-A), or 63% (PLCO-CRC). For potential MCD trial designs requiring 100 000 subjects per arm to achieve 90% power for multicancer mortality for the standard analysis, the IE analysis achieves 90% power for only 37 500-50 000 per arm, depending on assumptions concerning control-arm test-positives. Testing stored specimens in the control arm of screening trials to conduct the IE analysis could substantially increase power to reduce sample size or accelerate trials and could provide particularly strong power gains for MCD tests.

Primary care physicians and laypersons' perceptions of multicancer detection clinical trial designs.

The National Cancer Institute Cancer Screening Research Network is launching a pilot study (Vanguard) to determine feasibility of successful completion of a clinical trial of multicancer detection tests. This focus group study reports perceptions of primary care physicians and laypersons of different clinical trial designs and willingness to participate in a multicancer detection clinical trial. We undertook 14 focus groups with 88 laypersons and 6 focus groups with 45 primary care physicians. Participants were shown graphics of clinical trial designs and asked for their reactions. Focus group recordings were transcribed verbatim, and thematic analysis of the transcripts were conducted to identify emergent themes. Primary care physician and layperson participants recognized the importance of conducting clinical trials to determine the clinical utility of multicancer detection tests. Primary care physicians expressed reluctance to participate in trials because of workload burden, and laypersons expressed hesitancy about enrolling in the control group. Primary care physicians and laypersons expressed concern about a study design in which multicancer detection test results would not be returned to the control group (intended effect), but they respectively indicated a willingness to refer patients to, or participate in, a multicancer detection test clinical trial given transparent and clear communication on collection and use of biospecimens and data, particularly if a multicancer detection test would eventually be run and results eventually returned. This study yielded important insights to guide trial design in planning prospective evaluation of multicancer detection testing. Maintaining transparency and trust while possibly withholding multicancer detection test results to maximize trial feasibility and efficiency is of particular concern.

Lexicon for blood-based early detection and screening: BLOODPAC consensus document.

In the United States, 2.0 million new cancer cases and around 600,000 cancer deaths are estimated to occur in 2024. Early detection gives cancer patients the best chance for treatment success. Currently, cancer screening in the general population is recommended for a limited set of cancers; as a result, most cancer types are not regularly screened. Thus, in recent years, we have seen a wave of novel, non-invasive, single- and multi-cancer detection tests (SCD and MCD), promising detection of cancer signals prior to the onset of symptoms and/or clinical diagnosis. To accelerate the development, access, and adoption of these tests, the Blood Profiling Atlas in Cancer (BLOODPAC) Consortium, a collaborative infrastructure for developing standards and best practices, established the Early Detection & Screening (ED&S) Working Group. The early detection space is in need of consensus around definitions for SCD and MCD tests that harmonize terminology across diverse stakeholders, thereby reducing communication barriers and ultimately advancing the discipline. To this end, the ED&S Working Group compiled a lexicon of terms, chosen based on perceived importance, frequency of use, lack of clarity, and unique challenges in the context of SCD and MCD tests. This lexicon was submitted to the FDA for their feedback, which was incorporated. In this work, we present the first installment of the lexicon, consisting of 14 primary terms, that will be part of an online dictionary and provide a foundation for future projects of BLOODPAC's ED&S Working Group.

Methylation-Associated Nucleosomal Patterns of Cell-Free DNA in Cancer Patients and Pregnant Women.

Cell-free DNA (cfDNA) analysis offers an attractive noninvasive means of detecting and monitoring diseases. cfDNA cleavage patterns within a short range (e.g., 11 nucleotides) have been reported to correlate with cytosine-phosphate-guanine (CpG) methylation, allowing fragmentomics-based methylation analysis (FRAGMA). Here, we adopted FRAGMA to the extended region harboring multiple nucleosomes, termed FRAGMAXR. We profiled cfDNA nucleosomal patterns over the genomic regions from -800 to 800 bp surrounding differentially methylated CpG sites, harboring approximately 8 nucleosomes, referred to as CpG-associated cfDNA nucleosomal patterns. Such nucleosomal patterns were analyzed by FRAGMAXR in cancer patients and pregnant women. We identified distinct cfDNA nucleosomal patterns around differentially methylated CpG sites. Compared with subjects without cancer, patients with hepatocellular carcinoma (HCC) showed reduced amplitude of nucleosomal patterns, with a gradual decrease over tumor stages. Nucleosomal patterns associated with differentially methylated CpG sites could be used to train a machine learning model, resulting in the detection of HCC patients with an area under the receiver operating characteristic curve of 0.93. We further demonstrated the feasibility of multicancer detection using a dataset comprising lung, breast, and ovarian cancers. The tissue-of-origin analysis of plasma cfDNA from pregnant women and cancer patients revealed that the placental DNA and tumoral DNA contributions deduced by FRAGMAXR correlated well with values measured using genetic variants (Pearson r: 0.85 and 0.94, respectively). CpG-associated cfDNA nucleosomal patterns of cfDNA molecules are influenced by DNA methylation and might be useful for biomarker developments for cancer liquid biopsy and noninvasive prenatal testing.

Plasma ofCS-modified CD44 predicts the survival of patients with lung cancer.

Plasma levels of oncofetal chondroitin sulfate (ofCS)-modified CD44 have emerged as a promising biomarker for multi-cancer detection. Here, we explored its potential to predict the survival of patients with lung cancer. A prospective observational cohort was conducted involving 274 newly diagnosed patients with lung cancer at the Sun Yat-sen University Cancer Center from 2013 to 2015. The plasma levels of ofCS-modified CD44 were measured, and Cox regression analysis was performed to assess the association between plasma-modified CD44 levels and overall survival (OS) as well as other prognostic outcomes. Prognostic nomograms were constructed based on plasma ofCS-modified CD44 levels to predict survival outcomes for patients with lung cancer. Patients with high expression ofCS-modified CD44 exhibited significantly worse outcomes in terms of OS (HR = 1.61, 95%CI = 1.13-2.29, p = 0.009) and progression-free survival (PFS). These findings were consistent across various analyses. The concordance index of the prognostic nomogram for predicting OS in both the training set and validation set were 0.723 and 0.737, respectively. Additionally, time-dependent receiver operating characteristic (ROC) curves showed that the nomogram could serve as a useful tool for predicting OS in patients with lung cancer. Plasma ofCS-modified CD44 may serve as an independent prognosis marker for patients with lung cancer. Further validation of its predictive value could enhance prognostic assessment and guide personalized treatment strategies for patients with lung cancer.

IMPRESS: Improved methylation profiling using restriction enzymes and smMIP sequencing, combined with a new biomarker panel, creating a multi-cancer detection assay

BackgroundDespite the worldwide progress in cancer diagnostics, more sensitive diagnostic biomarkers are needed. The methylome has been extensively investigated in the last decades, but a low-cost, bisulfite-free detection method for multiplex analysis is still lacking.MethodsWe developed a methylation detection technique called IMPRESS, which combines methylation-sensitive restriction enzymes and single-molecule Molecular Inversion Probes. We used this technique for the development of a multi-cancer detection assay for eight of the most lethal cancer types worldwide. We selected 1791 CpG sites that can distinguish tumor from normal tissue based on DNA methylation. These sites were analysed with IMPRESS in 35 blood, 111 tumor and 114 normal samples. Finally, a classifier model was built.ResultsWe present the successful development of IMPRESS and validated it with ddPCR. The final classifier model discriminating tumor from normal samples was built with 358 CpG target sites and reached a sensitivity of 0.95 and a specificity of 0.91. Moreover, we provide data that highlight IMPRESS’s potential for liquid biopsies.ConclusionsWe successfully created an innovative DNA methylation detection technique. By combining this method with a new multi-cancer biomarker panel, we developed a sensitive and specific multi-cancer assay, with potential use in liquid biopsies.

I-Biomarker CaDx: A circulating miRNA-based multi-cancer detection test with generative and explainable AI for colorectal cancer.

64 Background: Colorectal cancer (CRC), the second most deadly cancer, underscores the critical need for early detection to significantly improve treatment outcomes and survival rates. Colonoscopy, flexible sigmoidoscopy, and the fecal immunochemical tests (FIT), often fail to capture early disease, significantly decreasing the survival chance. Circulating miRNA is a promising non-invasive biomarker for various cancers, including CRC. The i-Biomarker CaDx (patent pending) is an innovative multi-cancer early detection and diagnosis platform, covering 32 cancer types with an impressive accuracy rate of 99-100%. This study focuses on the effectiveness of i-Biomarker CaDx for CRC, employing significant data collection and leveraging insights from Generative AI (GenAI) and Explainable Artificial Intelligence (XAI). Methods: We collected various available datasets (e.g. GSE106817, etc.) encompassing 305 colorectal cancer patients and a matching number of healthy controls. Microarray was employed to profile circulating miRNAs. We used various classification paradigms, e.g., decision trees, neural networks, etc. Hyperparameter optimization was conducted, and the best-performing classifiers were amalgamated in the final model, weighted by their respective efficacies. We assessed i-Biomarker CaDx's performance through cross-validation and independent test sets. The XAI provided detailed insights into miRNA variations associated with personalized diagnostic. GenAI integrated the test into the screening and early detection best practice workflows and performs Functional Analysis. Results: i-Biomarker CaDx shows exceptional diagnostic accuracy of 99-100%, surpassing conventional colorectal cancer diagnostic methods like colonoscopy, flexible sigmoidoscopy, and FIT. It can also be used for personalized treatment response monitoring. I-Biomarker effectively deciphers intricate miRNA relationships relevant to colorectal cancer using XAI. Thus, our analyses shed light on miRNA patterns and their associations with colorectal cancer, enhancing the understanding of the underlying molecular complexities of the disease. It goes further by explaining the personalized cellular and molecular mechanisms involved, and it will be integrated into the corresponding medical workflows. Conclusions: Our AI-powered multi-cancer early diagnostic platform demonstrates outstanding performance in detecting CRC, surpassing traditional diagnostic methods like colonoscopy, flexible sigmoidoscopy, and FIT. XAI allows for in-depth exploration of miRNA alterations and their impact on CRC, enriching our interpretations at both the population and individual levels. These findings underscore the substantial potential of i-Biomarker CaDx as a transformative, non-invasive diagnostic tool for CRC.

Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA

Aberrant DNA methylation patterns have been used for cancer detection. However, DNA hemi-methylation, present at about 10% CpG dinucleotides, has been less well studied. Here we show that a majority of differentially hemi-methylated regions (DHMRs) in liver tumor DNA or plasma cells free (cf) DNA do not overlap with differentially methylated regions (DMRs) of the same samples, indicating that DHMRs could serve as independent biomarkers. Furthermore, we analyzed the cfDNA methylomes of 215 samples from individuals with liver or brain cancer and individuals without cancer (controls), and trained machine learning models using DMRs, DHMRs or both. The models incorporated with both DMRs and DHMRs show a superior performance compared to models trained with DMRs or DHMRs, with AUROC being 0.978, 0.990, and 0.983 in distinguishing control, liver and brain cancer, respectively, in a validation cohort. This study supports the potential of utilizing both DMRs and DHMRs for multi-cancer detection.

Understanding the Landscape of Multi-Cancer Detection Tests: The Current Data and Clinical Considerations.

Multi-cancer detection (MCD) tests are blood-based assays that screen for multiple cancers concurrently and offer a promising approach to improve early cancer detection and screening uptake. To date, there have been two prospective interventional studies evaluating MCD tests as a screening tool in human subjects. No MCD tests are currently approved by the FDA, but there is one commercially available MCD test. Ongoing trials continue to assess the efficacy, safety, and cost implications of MCD tests. In this review, we discuss the performance of CancerSEEK and Galleri, two leading MCD platforms, and discuss the clinical consideration for the broader application of this new technology.

TOTEM: a multi-cancer detection and localization approach using circulating tumor DNA methylation markers

BackgroundDetection of cancer and identification of tumor origin at an early stage improve the survival and prognosis of patients. Herein, we proposed a plasma cfDNA-based approach called TOTEM to detect and trace the cancer signal origin (CSO) through methylation markers.MethodsWe performed enzymatic conversion-based targeted methylation sequencing on plasma cfDNA samples collected from a clinical cohort of 500 healthy controls and 733 cancer patients with seven types of cancer (breast, colorectum, esophagus, stomach, liver, lung, and pancreas) and randomly divided these samples into a training cohort and a testing cohort. An independent validation cohort of 143 healthy controls, 79 liver cancer patients and 100 stomach cancer patients were recruited to validate the generalizability of our approach.ResultsA total of 57 multi-cancer diagnostic markers and 873 CSO markers were selected for model development. The binary diagnostic model achieved an area under the curve (AUC) of 0.907, 0.908 and 0.868 in the training, testing and independent validation cohorts, respectively. With a training specificity of 98%, the specificities in the testing and independent validation cohorts were 100% and 98.6%, respectively. Overall sensitivity across all cancer stages was 65.5%, 67.3% and 55.9% in the training, testing and independent validation cohorts, respectively. Early-stage (I and II) sensitivity was 50.3% and 45.7% in the training and testing cohorts, respectively. For cancer patients correctly identified by the binary classifier, the top 1 and top 2 CSO accuracies were 77.7% and 86.5% in the testing cohort (n = 148) and 76.0% and 84.0% in the independent validation cohort (n = 100). Notably, performance was maintained with only 21 diagnostic and 214 CSO markers, achieving a training AUC of 0.865, a testing AUC of 0.866, and an integrated top 2 accuracy of 83.1% in the testing cohort.ConclusionsTOTEM demonstrates promising potential for accurate multi-cancer detection and localization by profiling plasma methylation markers. The real-world clinical performance of our approach needs to be investigated in a much larger prospective cohort.

Efficient risk-based collection of biospecimens in cohort studies: Designing a prospective study of diagnostic performance for multicancer detection tests.

In cohort studies, it can be infeasible to collect specimens on an entire cohort. For example, to estimate sensitivity of multiple Multi-Cancer Detection (MCD) assays, we desire an extra 80mL of cell-free DNA (cfDNA) blood, but this much extra blood is too expensive for us to collect on everyone. We propose a novel epidemiologic study design that efficiently oversamples those at highest baseline disease risk from whom to collect specimens, to increase the number of future cases with cfDNA blood collection. The variance reduction ratio from our risk-based subsample versus a simple random (sub)sample (SRS) depends primarily on the ratio of risk model sensitivity to the fraction of the cohort selected for specimen collection subject to constraining the risk model specificity. In a simulation where we chose 34% of Prostate, Lung, Colorectal, and Ovarian Screening Trial cohort at highest risk of lung cancer for cfDNA blood collection, we could enrich the number of lung cancers 2.42-fold and the standard deviation of lung-cancer MCD sensitivity was 31-33% reduced versus SRS. Risk-based collection of specimens on a subsample of the cohort could be a feasible and efficient approach to collecting extra specimens for molecular epidemiology.

Cost-effectiveness of targeted vs. multi-cancer blood tests for colorectal cancer.

e15526 Background: Recent research suggested that current blood tests are not cost-effective for colorectal cancer (CRC) screening in patients declining other options, i.e., compared to not screening those patients.(1) The findings were from a new decision-analytic model evaluating a multi-cancer detection (MCD) test. Relative to this MCD test, emerging “targeted” CRC blood tests have higher suggested sensitivity for CRC precursors and lower specificity for subjects without any adenomas or CRC. We examine the cost-effectiveness of these emerging tests. Methods: An established CISNET model was replicated, validated, and then used to evaluate blood testing from age 45 to age 75 years, at 1, 2 or 3-year intervals. An MCD test (Galleri®) with 99.5% specificity, 0.5% advanced adenoma (AA) sensitivity, and 82.0% CRC sensitivity (99.5%, 0.5%, 82%) was compared to two hypothetical targeted CRC tests: a low-sensitivity blood test (lsBT) just meeting U.S. national coverage criteria (90%, 10%, 74%), and a high-sensitivity blood test (hsBT) with performance assumptions based on published data (90%, 20%, 90%). Galleri costs $949 per test; lsBT and hsBT costs were varied ($100-$1500). Outcomes included the estimated mortality reduction, and the discounted quality-adjusted life-years (QALY) gained, costs of screening, follow-up colonoscopy and treatment, and costs/QALY gained vs. no screening. Results: Estimated lifetime CRC incidence and mortality without screening were 85.9 and 32.9 per 1000, respectively. Triennial screening with Galleri reduced estimated CRC mortality by 15.6%, yielded 26.9 QALYs gained per 1000, and cost $191,135/QALY gained. Annual screening increased benefit to 28.9% mortality reduction and 46.6 QALYs gained, at $300,254/QALY gained. In contrast, at $1000 per test, lsBT every 1-3 years reduced mortality by 50.2-76.4%, yielded 71.0-109.5 QALYs gained, and cost $51,330-$67,420/QALY gained. hsBT testing further improved outcomes to 60.8-80.9% mortality reduction, 88.1-119.6 QALY gained, and $35,519-$58,125/QALY gained. Costs per QALY gained were lower for lsBT and hsBT vs. Galleri irrespective of the assumed unit costs, and never exceeded $82,902 for triennial testing. Conclusions: Emerging targeted blood tests for CRC can be cost-effective for screening and could be important in reaching underserved populations, once available. Targeted tests and MCD tests differ meaningfully in their accuracy, clinical interpretation, and use, and should not be treated as a similar type of screening test.

Perceptions of non-disclosure of results in clinical trial designs for multicancer detection tests.

10546 Background: Multi-cancer detection tests (MCDs) are blood-based tests designed to detect multiple cancers. The National Cancer Institute (NCI) is planning a pilot study to ascertain the feasibility of recruitment and the necessary infrastructure, clinical workflow, and diagnostic pathways for conducting a large clinical trial to assess whether cancer screening using MCDs reduces cancer mortality. In preparation for these activities, the NCI conducted a qualitative focus group study with primary care physicians (PCPs) and laypersons to explore the acceptability of alternative MCD trial designs, including the disclosure vs. non-disclosure of MCD test results to study participants. Methods: Focus groups were conducted with convenience samples of PCPs (6 groups, N=45) and laypersons (4 groups, N=88) by a consumer research firm. Interviews used both open-ended questions and specific prompts to explore participants’ perceptions of alternative clinical trial designs. Interviews were audio-recorded and transcribed, and qualitative thematic analysis of interview transcripts was conducted to identify emergent themes. Results: In general, PCPs and laypersons reported a willingness to refer or participate in an MCD trial regardless of design, with the understanding that clear and transparent information would be provided in the consent process. However, both groups expressed concern with a trial design in which patients in the control arm would not receive their MCD test results—a design that would allow a marked reduction in sample size and time necessary to assess a mortality endpoint. PCPs noted that although this design might be ethically acceptable due to current clinical equipoise about MCD testing, they expressed concern about mistrust among patients and medical-legal liability. Laypersons had difficulty understanding the rationale for non-disclosure of MCD test results during a trial, and concerns about the ethics of non-disclosure. Some participants felt more comfortable if return of value with other information was included as part of routine study procedures. Participants were more comfortable with an alternative design involving delayed testing of stored blood samples from the control group after trial completion. PCPs also expressed concern about increased workloads if their patients enrolled. Conclusions: PCPs and laypersons had generally positive reactions to a trial to investigate diagnostic performance, pathways, and outcomes of MCDs. Concerns about study designs involving non-disclosure of results might be managed through return of value strategies, careful education, and clear communication of the benefits and risks of MCDs.

Economic analysis of combined multi-cancer detection blood test and usual care.

e23055 Background: A previous multi-cancer detection blood test (MCDBT) in six prevalent and deadly cancers including colorectal, esophageal, liver, lung, ovarian, and pancreatic cancers, has been reported to decrease late-stage incidence and increase 5-year survival rate. However, the economic cost-effectiveness of integrating the MCDBT with usual care and the factors influencing it have not been investigated. Methods: An interception model was utilized to estimate the stage distribution at the time of cancer diagnosis, while a decision-tree model was developed to assess the clinical and economic outcomes of annual MCDBT for individuals aged 50 to 79 in the United States. The performance metrics for the MCDBT were based on the findings of a previous study called THUNDER. The incidence data were derived from the Surveillance, Epidemiology, and End Results Program (SEER), and the associated costs were obtained from SEER-Medicare. Other input data was estimated based on information available in the published literature. Results: In addition to the usual care, the integration of the MCDBT resulted in a shift of 27.9% in cancer cases from stage III-IV to stage I-II, which led to a decrease in per-cancer treatment cost by $5971 and an increase in quality-adjusted life-years by 0.10 per cancer case. The major factors that influenced the incremental cost-effectiveness ratio (ICER) included price, incidence, specificity, and sensitivity. The MCDBT with a price less than $800 showed cost-effectiveness with an ICER below three times the per capita GDP of the United States in the average-risk population. In a high-risk population with the incidence two-fold higher than the average-risk population, the ICER decreased by 58.3%. When compared the influence of specificity and sensitivity on the ICER of the MCDBT, a 5% increase in specificity resulted a decrease in ICER by 48.8%, while a 5% increase in sensitivity only reduced the ICER by 12.7%, suggesting the importance of high specificity in MCDBT. Conclusions: The MCDBT with a price less than $800 showed cost-effectiveness in the detection of colorectal, esophageal, liver, lung, ovarian, and pancreatic cancers. Price, incidence of the intended-use population, specificity and sensitivity were the major factors that influenced the cost-effectiveness.

Assessment of plasma cell-free DNA fragmentation for multi-cancer early detection: An independent clinical validation study.

e15037 Background: Cell-free DNA (cfDNA) in the circulation has gained significant attention due to its potential applications for non-invasive early cancer detection. Fragmentomics of cfDNA is emerging as a promising field of biomarker research, exhibiting the capability to sensitively detect multiple cancer types. In previous retrospective research, we developed an approach called PatternWGS for comprehensive analysis of cfDNA fragmentation patterns and presented a multi-cancer detection model. In this study, we aim to evaluate the performance of PatternWGS in an independent validation cohort including lung, breast, colorectal, liver, and gastric cancers from a new clinical center. Methods: Participants with confirmed diagnosis of lung, breast, colorectal or liver cancer were enrolled in the cancer group. Non-cancer participants without known presence of malignancies were recruited from the same clinical center. Plasma samples from patients with lung (n=47), breast (n=19), colorectal (n=14), liver (n=8) and gastric (n=6) cancers, along with 101 non-cancer individuals were collected in this study. cfDNA was isolated from plasma and stored within a month prior to the whole genome sequencing. The characteristics of cfDNA fragmentation integrating fragment size profiles, motif patterns, genomic coverage distributions were utilized to evaluate the performance for cancer signal detection. In addition, the performance of estimated cfDNA tumor fraction, using copy number aberrations (ichorCNA), was compared with our approach. Results: 94 patients with one of five types of cancers and 101 non-cancer controls were prospectively enrolled between July 2023 and November 2023. Among the cancer group, 64% were at early stages (Stage I: 48%, Stage II: 16%). A significantly higher proportion of shorter fragments was observed in cancer group, and the degree increased with increasing cancer stage. Overall sensitivity across cancer types and stages was 72.3%, and the specificity for non-cancer controls was 80%. As expected, the sensitivity of cancer detection is higher in late-stage patients compared to those in the early-stages (61% in stage I, 80% in stage II, 84.6% in stage III, and 91.7% in stage IV). The sensitivity of detecting lung (72% had stage I cancer), breast, colorectal, liver, and gastric cancers reached 57.4%, 84.2%, 85.7%, 87.5% and 100% respectively. The detection performance using cfDNA tumor fraction by ichorCNA demonstrated a relatively low overall sensitivity of 28.7% (24.6% for stage I-II, 44% for stage III-IV). Conclusions: This independent clinical validation study, which focused on exploring plasma cfDNA fragmentation, demonstrated ideal performance in early-stage cancer detection. The cfDNA fragmentation-based approach exhibited a superior sensitivity in detecting early cancer signals compared with copy number aberrations-based approach.

Increasing power in screening trials by testing control-arm specimens: application to multicancer detection screening.

Cancer screening trials have required large sample sizes and long time-horizons to demonstrate cancer mortality reductions, the primary goal of cancer screening. We examine assumptions and potential power gains from exploiting information from testing control-arm specimens, which we call the "intended effect" (IE) analysis that we explain in detail herein. The IE analysis is particularly suited to tests that can be conducted on stored specimens in the control arm, such as stored blood for multicancer detection (MCD) tests. We simulated hypothetical MCD screening trials to compare power and sample size for the standard vs IE analysis. Under two assumptions that we detail herein, we projected the IE analysis for 3 existing screening trials (National Lung Screening Trial [NLST], Minnesota Colon Cancer Control Study [MINN-FOBT-A], and Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial-colorectal component [PLCO-CRC]). Compared with the standard analysis for the 3 existing trials, the IE design could have reduced cancer-specific mortality P values 5-fold (NLST), 33-fold (MINN-FOBT-A), or 14 160-fold (PLCO-CRC) or, alternately, reduced sample size (90% power) by 26% (NLST), 48% (MINN-FOBT-A), or 59% (PLCO-CRC). For potential MCD trial designs requiring 100 000 subjects per arm to achieve 90% power for multicancer mortality for the standard analysis, the IE analysis achieves 90% power for only 37 500-50 000 per arm, depending on assumptions concerning control-arm test-positives. Testing stored specimens in the control arm of screening trials to conduct the IE analysis could substantially increase power to reduce sample size or accelerate trials and could provide particularly strong power gains for MCD tests.