Grail, Inc. · NASDAQ:GRAL
Grail — Technical Presentation (June 2023)
24 slides from Grail's technical presentation, June 2023
Slide 1: Large-scale observational prospective cohort study of a multi-cancer early detection (MCED) test
Large-scale observational prospective cohort study of a multi-cancer early detection (MCED) test in symptomatic patients referred for cancer investigation. SYMPLIFY Dr Brian D Nicholson, Associate Professor Nuffield Department of Primary Care Health Sciences, University of Oxford, UK. The copyright
Slide 2: Routes to Cancer Diagnosis
Routes to Cancer Diagnosis 100 Stage Percentage (%) 75 Stage I Stage II 50 Stage III 25 Stage IV Unknown 0 Rapid Cancer Emergency Screening GP Referral Other Referral Presentation Routes 6% 40% 26% 19% 9% GP, general practitioner. Symptomatic Primary Care Presentation https://www.cancerdata.nhs.uk/c
Slide 3: Majority of Patients Diagnosed With Cancer Present With Symptoms
Majority of Patients Diagnosed With Cancer Present With Symptoms Red Flag Symptoms Nonspecific Signs and Symptoms Cough, Haemoptysis Unexplained weight loss Dysphagia Abdominal pain Rectal bleeding, Haematuria Fatigue or exhaustion Breast lump Fever The copyright for the presentation slides remains
Slide 4: Urgent Cancer Pathways Based on National Guidelines
Urgent Cancer Pathways Based on National Guidelines Cancer Pathways and Sites • Cervical • Vaginal Gynaecological • Endometrial • Vulval • Ovarian • Anus • Rectum Lower Gastrointestinal • Colon • Gallbladder • Oesophago- Upper Gastrointestinal • Liver gastric • Pancreas Lung • Lung Rapid Diagnostic
Slide 5: Symptoms by Pathway
Symptoms by Pathway Cancer Pathways and Sites Symptoms • Cervical • Vaginal • Abdominal mass Gynaecological • Endometrial • Vulval • Change in bowel habit • Ovarian • Iron deficiency anaemia • Positive Fecal Immunochemical Test • Anus • Rectum • Rectal bleeding Lower Gastrointestinal • Colon • Weigh
Slide 6: Symptoms by Pathway
Symptoms by Pathway Cancer Pathways and Sites Symptoms • Cervical • Vaginal • Dysphagia Gynaecological • Endometrial • Vulval • Weight loss and dyspepsia • Ovarian • Weight loss and reflux • Weight loss and upper abdominal pain • Anus • Rectum Lower Gastrointestinal • Colon • Gallbladder • Oesophago
Slide 7: Symptoms by Pathway
Symptoms by Pathway Cancer Pathways and Sites Symptoms • Cervical • Vaginal • Appetite loss Gynaecological • Endometrial • Vulval • Fatigue • Ovarian • GP “gut feeling” • Nausea • Anus • Rectum • Pain Lower Gastrointestinal • Colon • Unexplained laboratory test results • Weight loss • Gallbladder •
Slide 8: Most Common Symptoms Overall
Most Common Symptoms Overall Cancer Pathways and Sites Most Common Symptoms • Cervical • Vaginal • Abdominal pain Gynaecological • Endometrial • Vulval • Anaemia • Ovarian • Appetite loss • Bloating • Anus • Rectum • Change in bowel habit Lower Gastrointestinal • Colon • Cough • Dyspepsia • Gallblad
Slide 9: An MCED Test Developed for Asymptomatic Population
An MCED Test Developed for Asymptomatic 9 Population MCED testing uses a targeted methylation, next-generation sequencing (NGS)-based assay to: • Detect and analyze cfDNA in the bloodstream • Deploy machine learning to detect a cancer signal • Predict the likely cancer signal origin (CSO) Cancer sig
Slide 10: SYMPLIFY Study Design
10 SYMPLIFY Study Design • Prospective observational cohort study • 44 hospital centres in England and Wales • 6,240 patients in 5 months • Symptomatic patients referred to one of five Cancer Pathways by their Family Doctor • Each participant consented to: • An additional blood draw • Follow-up in N
Slide 11: Participants Baseline Demographics
Participants Baseline Demographics 5,461 participants reached diagnostic resolution and had an evaluable MCED test 1446 2202 1021 299 493 Referral Pathway Gynaecological Lower GI Upper GI Lung RDC GI, gastrointestinal; MCED, multi-cancer early detection test; RDC, rapid diagnostic centre. The copyri
Slide 12: Participants Baseline Demographics
Participants Baseline Demographics 5,461 participants reached diagnostic resolution and had an evaluable MCED test Sex Distribution Age Distribution Overall Gynae Lower GI Lung RDC Upper GI 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% GI, gastrointestinal; MCED, multi-cancer early detection test;
Slide 13: Cancers Diagnosed by Cancer Pathway
Cancers Diagnosed by Cancer Pathway 368/5461 (6.7%) 54/1446 (3.7%) 143/2202 (6.5%) 89/299 (29.8%) 36/493 (7.3%) Other: breast (7), mesothelioma (6), anus (5), kidney (5), liver & bile duct (4), cervix (4), cancer of unknown primary (3), urothelial (3), vaginal 46/1021 (4.5%) (2), bladder (2), bone a
Slide 14: Primary Objective: To evaluate the performance of a MCED test for the detection of invasive cancer
Primary Objective: To evaluate the performance of a MCED test for the detection of invasive cancer. 323 244 Cases for which MCED test detected a cancer signal In whom cancer was diagnosed Sensitivity (%) Specificity (%) PPV (%) NPV (%) MCED, multi-cancer early detection test; NPV, negative predictiv
Slide 15: Primary Objective: To evaluate the performance of a MCED test for the detection of invasive cancer
Primary Objective: To evaluate the performance of a MCED test for the detection of invasive cancer. Post-test probability for CSD negative Pre-test probability Post-test probability for CSD positive CSD, cancer signal detected; MCED, multi-cancer early detection test. The copyright for the presentat
Slide 16: Secondary Objective: To evaluate the performance of a MCED test by cancer stage and site
16 Secondary Objective: To evaluate the performance of a MCED test by cancer stage and site. The copyright for the presentation slides remains with the authors/presenter. Permission must be obtained for reuse.
Slide 17: Diagnostic Accuracy of Cancer Signal Detected
17 Diagnostic Accuracy of Cancer Signal Detected Cancer Referral Pathways Sensitivity (%) Specificity (%) PPV (%) NPV (%) Overall Gynae Lower GI Lung RDC Upper GI GI, gastrointestinal; RDC, rapid diagnostic centre. The copyright for the presentation slides remains with the authors/presenter. Permiss
Slide 18: Cancer Risk Following Cancer Signal Detected Result
18 Cancer Risk Following Cancer Signal Detected Result Cancer Referral Pathways Overall Gynae Lower GI Post-test probability for CSD negative Pre-test probability Lung Post-test probability for CSD positive RDC Upper GI CSD, cancer signal detected, GI, gastrointestinal; RDC, rapid diagnostic centre.
Slide 19: Cancer Risk Following Cancer Signal Detected Result
19 Cancer Risk Following Cancer Signal Detected Result Symptoms Secondary care referred cancer pre-test probability Post-test probability for CSD negative Pre-test probability Post-test probability for CSD positive CSD, cancer signal detected. The copyright for the presentation slides remains with t
Slide 20: Cancer Risk Following Cancer Signal Detected Result
20 Cancer Risk Following Cancer Signal Detected Result Symptoms Primary care pre-referral cancer pre-test probability Post-test probability for CSD negative Pre-test probability Post-test probability for CSD positive CSD, cancer signal detected. The copyright for the presentation slides remains with
Slide 21: Accuracy of Predicted Cancer Signal Origin
Accuracy of Predicted Cancer Signal Origin CSD - Uterus Thyroid Prostate Plasma Predicted Cancer Signal Origin Panc/GB Ovary Oes/Sto NET Myeloid Melanoma Lymphoid Lung Liver/BD Kidney H&N Colorectal Cervix Breast Bone & ST Blad/Uro Anus B l a us Ly Lung Ov to Co ervix My ma rus ro Pro sma Th te BD e
Slide 22: Concluding Points
22 Concluding Points • Large-scale rapid studies of MCED tests in symptomatic patients are feasible in routine clinical practice. • The current MCED test showed increased sensitivity for cancer detection with increasing cancer stage, with variation in accuracy by referral pathway, and for individual
Slide 23: Implications
23 Implications • Once the algorithm is optimised for NPV in symptomatic patients using our data it should have greater utility to inform decisions about cancer investigation. • Testing symptomatic patients with lower pre-test probabilities for cancer in primary care before referral could permit bot
Slide 24: Acknowledgements
24 Acknowledgements Thank you! All participants: for consenting and taking part. • Study Team: Chief Investigator: Professor Mark Middleton; Oxford University: Jason Oke, Pradeep S Virdee, Sharon Tonner, Monika Vargova, Lazarina Engonidou, Ly-Mee Yu, Clare Freestone, Sarah Pearson, FD Richard Hobbs,