Blood-based tests for multicancer early detection (PATHFINDER): a prospective cohort study.

BACKGROUND: Multicancer early detection (MCED) blood tests can detect a cancer signal from circulating cell-free DNA (cfDNA). PATHFINDER was a prospective cohort study investigating the feasibility of MCED testing for cancer screening. METHODS: In this prospective cohort study done in oncology and primary care outpatient clinics at seven US health networks, a convenience sample of adults aged 50 years or older without signs or symptoms of cancer consented to MCED testing. We collected blood, analysed cfDNA, and returned results to participants' doctors. If a methylation signature indicative of cancer was detected, predicted cancer signal origin(s) informed diagnostic assessment. The primary outcome was time to, and extent of, diagnostic testing required to confirm the presence or absence of cancer. This trial is registered at ClinicalTrials.gov, NCT04241796, and is completed. FINDINGS: Between Dec 12, 2019, and Dec 4, 2020, we recruited 6662 participants. 4204 (63·5%) of 6621 participants with analysable results were women, 2417 (36·5%) were men, and 6071 (91·7%) were White. A cancer signal was detected in 92 (1·4%) of 6621 participants with analysable results. 35 (38%) participants were diagnosed with cancer (true positives) and 57 (62%) had no cancer diagnosis (false positives). Excluding two participants whose diagnostic assessments began before MCED test results were reported, median time to diagnostic resolution was 79 days (IQR 37-219): 57 days (33-143) in true-positive and 162 days (44-248) in false-positive participants. Most participants had both laboratory tests (26 [79%] of 33 with true-positive results and 50 [88%] of 57 with false-positive results) and imaging (30 [91%] of 33 with true-positive results and 53 [93%] of 57 with false-positive results). Fewer procedures were done in participants with false-positive results (17 [30%] of 57) than true-positive results (27 [82%] of 33) and few had surgery (one with a false-positive result and three with a true-positive result). INTERPRETATION: This study supports the feasibility of MCED screening for cancer and underscores the need for further research investigating the test's clinical utility. FUNDING: GRAIL.

Characteristics of second breast events among women treated with breast-conserving surgery for DCIS in the community.

We examined the clinical/pathologic features of ipsilateral second breast cancers (IP-SBCs) following breast-conserving surgery (BCS) for DCIS among community-treated patients and ascertained the degree of correlation between the features of index DCIS and IP-SBC events. From a Cancer Research Network cohort of DCIS patients diagnosed 1990-2001 and treated with BCS, we identified women who subsequently developed an ipsilateral DCIS or invasive breast cancer. All index DCIS tumors underwent expert pathology review. Pathologic characteristics of IP-SBCs were abstracted from available medical records. Logistic regression was used to examine associations between pathologic characteristics and identify factors associated with invasive versus non-invasive IP-SBC. Of 1969 DCIS patients, 182 developed an IP-SBC within a median of 38 months (range 6-160). IP-SBCs were slightly more commonly non-invasive (53 %) versus invasive (47 %). Of invasive IP-SBCs, 31 % were high grade, 67 % were <20 mm, 74 % were estrogen receptor positive, 7 % were HER2 positive, and 16 % were node positive. Of non-invasive IP-SBCs, 33 % were high grade. Comparing index DCIS and IP-SBC specimens, there was moderate-high correlation for HR status and grade. Among patients with IP-SBCs, those who were younger and whose index DCIS tumors were HR negative had shorter intervals (within 3 years) between index and IP-SBC diagnoses. No index DCIS feature was statistically significantly associated with an IP-SBC that was invasive versus non-invasive. Understanding the characteristics of SBCs and identifying correlations between these and index DCIS events could influence treatment choices for DCIS, and may help patients and providers develop treatment paradigms for SBCs.

An ED pilot intervention to facilitate outpatient acute care for cancer patients.

INTRODUCTION: Unplanned hospitalizations are common in patients with cancer, and most hospitalizations originate in the emergency department (ED). METHODS: We implemented an ED-based pilot intervention designed to reduce hospitalizations among patients with solid tumors. The intervention, piloted at a single academic medical center, involved a medical oncologist embedded in the ED during evening hours. We used a quasiexperimental preimplementation/postimplementation study design to evaluate the proportion of ED visits that resulted in inpatient hospital admission, before and after pilot implementation. General estimating equations were used to evaluate the association between the intervention and hospital admission. RESULTS: There were 390 ED visits by eligible cancer patients in the preintervention period and 418 visits in the intervention period. During the intervention period, 158 (38%) of 418 ED visits were identified by the embedded oncologist during the evening intervention shift. The proportion of ED visits leading to hospitalization was 70% vs 69% in the preintervention and intervention periods (odds ratio, 0.93 [95% confidence interval, 0.69-1.24]; P= .62). There were no differences between periods in ED length of stay or subsequent use of acute care. Among patients with initial ED presentation during the operating hours of the intervention, the proportion of ED visits leading to hospitalization was 77% vs 67% in the preintervention and intervention periods (odds ratio, 0.62 [0.36-1.08]; P= .08). CONCLUSION: Embedding an oncologist in the ED of an academic medical center did not significantly reduce hospital admissions. Novel approaches are needed to strengthen outpatient acute care for patients with cancer.

Validating billing/encounter codes as indicators of lung, colorectal, breast, and prostate cancer recurrence using 2 large contemporary cohorts.

BACKGROUND: A substantial proportion of cancer-related mortality is attributable to recurrent, not de novo metastatic disease, yet we know relatively little about these patients. To fill this gap, investigators often use administrative codes for secondary malignant neoplasm or chemotherapy to identify recurrent cases in population-based datasets. However, these algorithms have not been validated in large, contemporary, routine care cohorts. OBJECTIVE: To evaluate the validity of secondary malignant neoplasm and chemotherapy codes as indicators of recurrence after definitive local therapy for stage I-III lung, colorectal, breast, and prostate cancer. RESEARCH DESIGN, SUBJECTS, AND MEASURES: We assessed the sensitivity, specificity, and positive predictive value (PPV) of these codes 14 and 60 months after diagnosis using 2 administrative datasets linked with gold-standard recurrence status information: CanCORS/Medicare (diagnoses 2003-2005) and HMO/Cancer Research Network (diagnoses 2000-2005). RESULTS: We identified 929 CanCORS/Medicare patients and 5298 HMO/CRN patients. Sensitivity, specificity, and PPV ranged widely depending on which codes were included and the type of cancer. For patients with lung, colorectal, and breast cancer, the combination of secondary malignant neoplasm and chemotherapy codes was the most sensitive (75%-85%); no code-set was highly sensitive and highly specific. For prostate cancer, no code-set offered even moderate sensitivity (≤ 19%). CONCLUSIONS: Secondary malignant neoplasm and chemotherapy codes could not identify recurrent cancer without some risk of misclassification. Findings based on existing algorithms should be interpreted with caution. More work is needed to develop a valid algorithm that can be used to characterize outcomes and define patient cohorts for comparative effectiveness research studies.

Contribution of H. pylori and smoking trends to US incidence of intestinal-type noncardia gastric adenocarcinoma: a microsimulation model.

BACKGROUND: Although gastric cancer has declined dramatically in the US, the disease remains the second leading cause of cancer mortality worldwide. A better understanding of reasons for the decline can provide important insights into effective preventive strategies. We sought to estimate the contribution of risk factor trends on past and future intestinal-type noncardia gastric adenocarcinoma (NCGA) incidence. METHODS AND FINDINGS: We developed a population-based microsimulation model of intestinal-type NCGA and calibrated it to US epidemiologic data on precancerous lesions and cancer. The model explicitly incorporated the impact of Helicobacter pylori and smoking on disease natural history, for which birth cohort-specific trends were derived from the National Health and Nutrition Examination Survey (NHANES) and National Health Interview Survey (NHIS). Between 1978 and 2008, the model estimated that intestinal-type NCGA incidence declined 60% from 11.0 to 4.4 per 100,000 men, <3% discrepancy from national statistics. H. pylori and smoking trends combined accounted for 47% (range = 30%-58%) of the observed decline. With no tobacco control, incidence would have declined only 56%, suggesting that lower smoking initiation and higher cessation rates observed after the 1960s accelerated the relative decline in cancer incidence by 7% (range = 0%-21%). With continued risk factor trends, incidence is projected to decline an additional 47% between 2008 and 2040, the majority of which will be attributable to H. pylori and smoking (81%; range = 61%-100%). Limitations include assuming all other risk factors influenced gastric carcinogenesis as one factor and restricting the analysis to men. CONCLUSIONS: Trends in modifiable risk factors explain a significant proportion of the decline of intestinal-type NCGA incidence in the US, and are projected to continue. Although past tobacco control efforts have hastened the decline, full benefits will take decades to be realized, and further discouragement of smoking and reduction of H. pylori should be priorities for gastric cancer control efforts.

Comparison of Oncologist and Model Estimates of Risk for Hospitalization During Systemic Therapy for Advanced Cancer.

PURPOSE: A validated risk model with inputs of pretreatment sodium and albumin can identify patients at risk for hospitalization during cancer treatment. We evaluated how the model compares with risk estimates from treating oncologists. METHODS: We evaluated the 30-day risk of hospitalization or death in patients starting palliative-intent systemic therapy for solid tumor malignancy. For each patient, we prospectively recorded categorical estimates of 30-day hospitalization risk (bottom third, middle third, top third) generated by a treating oncologist and by the two-variable model; a third hybrid risk estimate represented a composite of the oncologist and model risk assessments. We analyzed the agreement of oncologist and model-based risk estimates and compared discrimination, sensitivity, and specificity of each risk assessment method. RESULTS: We collected oncologist, model, and hybrid estimates of hospitalization risk for 120 patients. The 30-day rate of hospitalization or death was 20%. There was minimal agreement between oncologist and model risk estimates (weighted kappa = 0.27). The c-statistic (a measure of discrimination) was 0.69 (95% CI, 0.57 to 0.81) for the clinician assessment, 0.77 for the model assessment (CI, 0.67 to 0.86; P = .24 compared with the oncologist assessment), and 0.79 for the hybrid assessment (CI, 0.69 to 0.90; P = .007 compared with the oncologist assessment). Sensitivity and specificity of the high-risk categorization did not differ significantly between the oncologist and model assessments; the hybrid assessment was significantly more sensitive (P = .02) and less specific (P = .03) than the oncologist assessment. CONCLUSION: A model with inputs of pretreatment sodium and albumin improves oncologists' predictions of hospitalization risk during cancer treatment.

Framework for integrating electronic patient-reported data in routine cancer care: an Oncology Intake Questionnaire.

Objective: As part of ongoing implementation of electronic patient-reported outcome tools at the Dana-Farber Cancer Institute, here we describe the development of the electronic New Patient Intake Questionnaire. Materials and Methods: The original New Patient Intake Questionnaire includes a review of symptoms, oncology history, family history, health behaviors, health and social status, health literacy and numeracy, which was modified for integration into the EHR using content determination, build and configuration, implementation, analytics, and interventions. The engagement of key stakeholders, including patients, clinical staff, and providers, throughout the development and deployment of the electronic Questionnaire was crucial to producing a successful tool. Continual modifications based on input of stakeholders (such as mode of tool deployment) were made to ensure the utility and usability of the tool for both patients and providers. Results: Implementation of the EHR-integrated electronic New Patient Intake Questionnaire improved collection of the PRD by increasing questionnaire accessibility for patients, while also providing all available data to clinicians and researchers. Careful consideration of the content and configuration of the questionnaire allowed for a successful, institute-wide implementation of the tool. Discussion: This effort demonstrates the feasibility of implementation of a system-wide electronic questionnaire, emphasizing the importance of iterative refinement to create a tool that is both patient-centric and usable for clinicians. Conclusions: The electronic New Patient Intake Questionnaire allows for systematic collection of the PRD, which should benefit cancer care outcomes through innovative care delivery and healthcare interventions.

Generating Real-World Tumor Burden Endpoints from Electronic Health Record Data: Comparison of RECIST, Radiology-Anchored, and Clinician-Anchored Approaches for Abstracting Real-World Progression in Non-Small Cell Lung Cancer.

INTRODUCTION: Real-world evidence derived from electronic health records (EHRs) is increasingly recognized as a supplement to evidence generated from traditional clinical trials. In oncology, tumor-based Response Evaluation Criteria in Solid Tumors (RECIST) endpoints are standard clinical trial metrics. The best approach for collecting similar endpoints from EHRs remains unknown. We evaluated the feasibility of a RECIST-based methodology to assess EHR-derived real-world progression (rwP) and explored non-RECIST-based approaches. METHODS: In this retrospective study, cohorts were randomly selected from Flatiron Health's database of de-identified patient-level EHR data in advanced non-small cell lung cancer. A RECIST-based approach tested for feasibility (N = 26). Three non-RECIST approaches were tested for feasibility, reliability, and validity (N = 200): (1) radiology-anchored, (2) clinician-anchored, and (3) combined. Qualitative and quantitative methods were used. RESULTS: A RECIST-based approach was not feasible: cancer progression could be ascertained for 23% (6/26 patients). Radiology- and clinician-anchored approaches identified at least one rwP event for 87% (173/200 patients). rwP dates matched 90% of the time. In 72% of patients (124/173), the first clinician-anchored rwP event was accompanied by a downstream event (e.g., treatment change); the association was slightly lower for the radiology-anchored approach (67%; 121/180). Median overall survival (OS) was 17 months [95% confidence interval (CI) 14, 19]. Median real-world progression-free survival (rwPFS) was 5.5 months (95% CI 4.6, 6.3) and 4.9 months (95% CI 4.2, 5.6) for clinician-anchored and radiology-anchored approaches, respectively. Correlations between rwPFS and OS were similar across approaches (Spearman's rho 0.65-0.66). Abstractors preferred the clinician-anchored approach as it provided more comprehensive context. CONCLUSIONS: RECIST cannot adequately assess cancer progression in EHR-derived data because of missing data and lack of clarity in radiology reports. We found a clinician-anchored approach supported by radiology report data to be the optimal, and most practical, method for characterizing tumor-based endpoints from EHR-sourced data. FUNDING: Flatiron Health Inc., which is an independent subsidiary of the Roche group.