A Proposal to Improve the Early Diagnosis of Symptomatic Cancers in the United States

Predicting the Future by Studying the Past for Patients With Cancer Diagnosed in the Emergency Department

In the article that accompanies this editorial, Kapadia et al. developed a digital quality measure to identify emergency presentations of incident cancers, a measure they found to associated with both antecedent missed opportunities for diagnosis and subsequent 1-year all-cause mortality. Their work highlights the need for a cancer control continuum that includes, not only improved early detection, but also improved symptom recognition, expedited diagnostic work-up, and increased downstream support, including multilevel interventions focused on care continuity and symptom management for these patients with emergency presentations of cancer to improve cancer outcomes.

Development and Implementation of a Digital Quality Measure of Emergency Cancer Diagnosis

PURPOSE

Missed and delayed cancer diagnoses are common, harmful, and often preventable. Automated measures of quality of cancer diagnosis are lacking but could identify gaps and guide interventions. We developed and implemented a digital quality measure (dQM) of cancer emergency presentation (EP) using electronic health record databases of two health systems and characterized the measure's association with missed opportunities for diagnosis (MODs) and mortality.

METHODS

On the basis of literature and expert input, we defined EP as a new cancer diagnosis within 30 days after emergency department or inpatient visit. We identified EPs for lung cancer and colorectal cancer (CRC) in the Department of Veterans Affairs (VA) and Geisinger from 2016 to 2020. We validated measure accuracy and identified preceding MODs through standardized chart review of 100 records per cancer per health system. Using VA's longitudinal encounter and mortality data, we applied logistic regression to assess EP's association with 1-year mortality, adjusting for cancer stage and demographics.

RESULTS

Among 38,565 and 2,914 patients with lung cancer and 14,674 and 1,649 patients with CRCs at VA and Geisinger, respectively, our dQM identified EPs in 20.9% and 9.4% of lung cancers, and 22.4% and 7.5% of CRCs. Chart reviews revealed high positive predictive values for EPs across sites and cancer types (72%-90%), and a substantial percent represented MODs (48.8%-84.9%). EP was associated with significantly higher odds of 1-year mortality for lung cancer and CRC (adjusted odds ratio, 1.78 and 1.83, respectively, 95% CI, 1.63 to 1.86 and 1.61 to 2.07).

CONCLUSION

A dQM for cancer EP was strongly associated with both mortality and MODs. The findings suggest a promising automated approach to measuring quality of cancer diagnosis in US health systems.

Nonspecific Signs and/or Symptoms of Cancer: A Retrospective, Observational Analysis from a Secondary Care, US Community Oncology Dataset

To help determine the unmet need for improved diagnostic tools to evaluate patients with nonspecific signs and/or symptoms (NSSS) and suspicion of cancer, we examined patient characteristics, diagnostic journey, and cancer incidence of patients with NSSS within The US Oncology Network (The Network), a secondary care community oncology setting. This retrospective, observational cohort study included patients aged ≥40 years with ≥1 NSSS in their problem list at their first visit within The Network (the index date) between 1 January 2016 and 31 December 2020. Patients were followed longitudinally with electronic health record data for initial cancer diagnosis, new noncancer diagnosis, death, end of study observation period, or 12 months, whichever occurred first. Of 103,984 patients eligible for inclusion, 96,722 presented with only 1 NSSS at index date; 6537/103,984 (6.3%) were diagnosed with 1 primary cancer within 12 months after the index date; 3825/6537 (58.5%) with hematologic malignancy, and 2712/6537 (41.5%) with solid tumor. Among patients diagnosed with cancer (n = 6774), the median time to cancer diagnosis after their first visit within The Network was 5.13 weeks. This study provides a real-world perspective on cancer incidence in patients with NSSS referred to a secondary care setting and highlights the unmet need for improved diagnostic tools to improve cancer outcomes.

Circulating tumor DNA (ctDNA): can it be used as a pan-cancer early detection test?

Circulating tumor DNA (ctDNA, DNA shed by cancer cells) is emerging as one of the most transformative cancer biomarkers discovered to-date. Although potentially useful at all the phases of cancer detection and patient management, one of its most exciting possibilities is as a relatively noninvasive pan-cancer screening test. Preliminary findings with ctDNA tests such as Galleri or CancerSEEK suggest that they have high specificity (> 99.0%) for malignancy. Their sensitivity varies depending on the type of cancer and stage of disease but it is generally low in patients with stage I disease. A major advantage of ctDNA over existing screening strategies is the potential ability to detect multiple cancer types in a single test. A limitation of most studies published to-date is that they are predominantly case-control investigations that were carried out in patients with a previous diagnosis of malignancy and that used apparently healthy subjects as controls. Consequently, the reported sensitivities, specificities and positive predictive values might be lower if the tests are used for screening in asymptomatic populations, that is, in the population where these tests are likely be employed. To demonstrate clinical utility in an asymptomatic population, these tests must be shown to reduce cancer mortality without causing excessive overdiagnosis in a large randomized prospective randomized trial. Such trials are currently ongoing for Galleri and CancerSEEK.

Red Flag Signs and Symptoms for Patients With Early-Onset Colorectal Cancer: A Systematic Review and Meta-Analysis

Importance

Early-onset colorectal cancer (EOCRC), defined as a diagnosis at younger than age 50 years, is increasing, and so-called red flag signs and symptoms among these individuals are often missed, leading to diagnostic delays. Improved recognition of presenting signs and symptoms associated with EOCRC could facilitate more timely diagnosis and impact clinical outcomes.

Objective

To report the frequency of presenting red flag signs and symptoms among individuals with EOCRC, to examine their association with EOCRC risk, and to measure variation in time to diagnosis from sign or symptom presentation.

Data Sources

PubMed/MEDLINE, Embase, CINAHL, and Web of Science were searched from database inception through May 2023.

Study Selection

Studies that reported on sign and symptom presentation or time from sign and symptom presentation to diagnosis for patients younger than age 50 years diagnosed with nonhereditary CRC were included.

Data Extraction and Synthesis

Data extraction and quality assessment were performed independently in duplicate for all included studies using Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guidelines. Joanna Briggs Institute Critical Appraisal tools were used to measure risk of bias. Data on frequency of signs and symptoms were pooled using a random-effects model.

Main Outcomes and Measures

Outcomes of interest were pooled proportions of signs and symptoms in patients with EOCRC, estimates for association of signs and symptoms with EOCRC risk, and time from sign or symptom presentation to EOCRC diagnosis.

Results

Of the 12 859 unique articles initially retrieved, 81 studies with 24 908 126 patients younger than 50 years were included. The most common presenting signs and symptoms, reported by 78 included studies, were hematochezia (pooled prevalence, 45% [95% CI, 40%-50%]), abdominal pain (pooled prevalence, 40% [95% CI, 35%-45%]), and altered bowel habits (pooled prevalence, 27% [95% CI, 22%-33%]). Hematochezia (estimate range, 5.2-54.0), abdominal pain (estimate range, 1.3-6.0), and anemia (estimate range, 2.1-10.8) were associated with higher EOCRC likelihood. Time from signs and symptoms presentation to EOCRC diagnosis was a mean (range) of 6.4 (1.8-13.7) months (23 studies) and a median (range) of 4 (2.0-8.7) months (16 studies).

Conclusions and Relevance

In this systematic review and meta-analysis of patients with EOCRC, nearly half of individuals presented with hematochezia and abdominal pain and one-quarter with altered bowel habits. Hematochezia was associated with at least 5-fold increased EOCRC risk. Delays in diagnosis of 4 to 6 months were common. These findings highlight the need to identify concerning EOCRC signs and symptoms and complete timely diagnostic workup, particularly for individuals without an alternative diagnosis or sign or symptom resolution.

The presenting symptom signatures of incident cancer: evidence from the English 2018 National Cancer Diagnosis Audit

BACKGROUND

Understanding relationships between presenting symptoms and subsequently diagnosed cancers can inform symptom awareness campaigns and investigation strategies.

METHODS

We used English National Cancer Diagnosis Audit 2018 data for 55,122 newly diagnosed patients, and examined the relative frequency of presenting symptoms by cancer site, and of cancer sites by presenting symptom.

RESULTS

Among 38 cancer sites (16 cancer groups), three classes were apparent: cancers with a dominant single presenting symptom (e.g. melanoma); cancers with diverse presenting symptoms (e.g. pancreatic); and cancers that are often asymptomatically detected (e.g. chronic lymphocytic leukaemia). Among 83 symptoms (13 symptom groups), two classes were apparent: symptoms chiefly relating to cancers of the same body system (e.g. certain respiratory symptoms mostly relating to respiratory cancers); and symptoms with a diverse cancer site case-mix (e.g. fatigue). The cancer site case-mix of certain symptoms varied by sex.

CONCLUSION

We detailed associations between presenting symptoms and cancer sites in a large, representative population-based sample of cancer patients. The findings can guide choice of symptoms for inclusion in awareness campaigns, and diagnostic investigation strategies post-presentation when cancer is suspected. They can inform the updating of clinical practice recommendations for specialist referral encompassing a broader range of cancer sites per symptom.

Phenotypes and rates of cancer-relevant symptoms and tests in the year before cancer diagnosis in UK Biobank and CPRD Gold

Early diagnosis of cancer relies on accurate assessment of cancer risk in patients presenting with symptoms, when screening is not appropriate. But recorded symptoms in cancer patients pre-diagnosis may vary between different sources of electronic health records (EHRs), either genuinely or due to differential completeness of symptom recording. To assess possible differences, we analysed primary care EHRs in the year pre-diagnosis of cancer in UK Biobank and Clinical Practice Research Datalink (CPRD) populations linked to cancer registry data. We developed harmonised phenotypes in Read v2 and CTV3 coding systems for 21 symptoms and eight blood tests relevant to cancer diagnosis. Among 22,601 CPRD and 11,594 UK Biobank cancer patients, 54% and 36%, respectively, had at least one consultation for possible cancer symptoms recorded in the year before their diagnosis. Adjusted comparisons between datasets were made using multivariable Poisson models, comparing rates of symptoms/tests in CPRD against expected rates if cancer site-age-sex-deprivation associations were the same as in UK Biobank. UK Biobank cancer patients compared with those in CPRD had lower rates of consultation for possible cancer symptoms [RR: 0.61 (0.59-0.63)], and lower rates for any primary care consultation [RR: 0.86 (95%CI 0.85-0.87)]. Differences were larger for 'non-alarm' symptoms [RR: 0.54 (0.52-0.56)], and smaller for 'alarm' symptoms [RR: 0.80 (0.76-0.84)] and blood tests [RR: 0.93 (0.90-0.95)]. In the CPRD cohort, approximately representative of the UK population, half of cancer patients had recorded symptoms in the year before diagnosis. The frequency of non-specific presenting symptoms recorded in the year pre-diagnosis of cancer was substantially lower among UK Biobank participants. The degree to which results based on highly selected biobank cohorts are generalisable needs to be examined in disease-specific contexts.

Performance of a Cell-Free DNA-Based Multi-cancer Detection Test in Individuals Presenting With Symptoms Suspicious for Cancers

PURPOSE

A multi-cancer detection test using a targeted methylation assay and machine learning classifiers was validated and optimized for screening in prospective, case-controlled Circulating Cell-free Genome Atlas (ClinicalTrials.gov identifier: NCT02889978) substudy 3. Here, we report test performance in a subgroup of participants with symptoms suspicious for cancer to assess the test's ability to potentially facilitate efficient diagnostic evaluation in symptomatic individuals.

METHODS

We evaluated test performance (sensitivity, specificity, and accuracy of cancer signal origin [CSO] prediction accuracy) in participants with clinically presenting cancers (CPCs) and noncancer with underlying medical conditions and among two subgroups (65 years and older and GI cancers). Overall survival (OS) of participants who had a cancer signal detected/not detected was compared with SEER-based expected survival.

RESULTS

A total of 2,036 cancer and 1,472 noncancer participants were included. Specificity was high in all noncancer participants (99.5% [95% CI, 98.4 to 99.8]). In participants with CPCs, the overall sensitivity was 64.3% (95% CI, 62.2 to 66.4) and the overall accuracy of CSO prediction in true positives was 90.3%. For GI cancers, the overall sensitivity was 84.1% (95% CI, 80.6 to 87.1). In participants 65 years and older, test performance was similar to that of all participants. Individuals with cancers not detected had a significantly better OS than that expected from SEER (P < .01).

CONCLUSION

This test detected a cancer signal with high specificity and CSO prediction accuracy and moderate sensitivity in symptomatic individuals, with especially high performance in participants with GI cancers. The survival analysis implied that the cancers not detected were less clinically aggressive than cancers detected by the test, providing prognostic insights to physicians. This multi-cancer detection test could facilitate efficient workup and stratify cancer risk in symptomatic individuals.

Time duration and health care resource use during cancer diagnoses in the United States: A large claims database analysis

BACKGROUND: Cancer diagnostic pathways are highly variable and not clearly established in the United States, which can lead to a diagnosis process that takes more time and exposes patients to invasive or unnecessary procedures, delays in treatment, worsening patient outcomes, and elevated health care resource utilization (HRU) and health care system costs. OBJECTIVE: To investigate current trends in time to diagnosis and diagnostic-related HRU preceding the patient's cancer diagnosis across all cancer types in the United States. METHODS: A retrospective claims analysis was conducted on patients newly diagnosed with cancer identified from 2018-2019 using Optum's de-identified Clinformatics Data Mart database, which includes Medicare Advantage and commercially insured members. Patients were identified using International Classification of Diseases, Tenth Revision codes and were required to have at least 2 outpatient visits at least 30 days apart or at least 1 inpatient cancer visit without prior cancer claims. The first diagnostic test was identified based on an algorithm of a 60-day gap between diagnostic tests prior to diagnosis. The index date was defined as the first diagnostic test date or an office visit less than 4 weeks prior to the first diagnostic test date. Patient characteristics, time to diagnosis, and HRU were descriptively analyzed for all patients and by cancer type. RESULTS: Among the 458,818 patients newly diagnosed with cancer included in this analysis, the mean age was 70.6 years, approximately half were female, and most were White people (65.0%) with Medicare Advantage coverage (74.0%). Patients with cancer had an overall mean (SD) time to diagnosis of 156.2 (164.9) days and 15.4% of patients waited longer than 180 days before a cancer diagnosis. High heterogeneity among cancer types was observed, with a mean time to diagnosis ranging from 121.6 days (bladder cancer) to 229.0 days (multiple myeloma). Imaging resource use during the diagnostic pathway was high for radiology (60.7%), computerized tomography (50.8%), magnetic resonance imaging (48.6%), and ultrasound (42.6%). A total of 69.3% of patients had endoscopy without biopsy, 36.5% had endoscopy with biopsy, 62.5% had other biopsies, and most patients did general urine and serum tests (91.3%) and nongenetic cancer-specific laboratory tests (84.3%). Resource use was highly varied by cancer type but tended to increase with a longer time to diagnosis. CONCLUSIONS: The proportion of patients experiencing a diagnostic process of longer than 180 days is clinically and economically meaningful. Diagnostic-related HRU was significant and highly variable, highlighting the inefficiencies in the cancer diagnostic process in the United States and the need for policies, guidelines, or medical interventions to streamline cancer diagnostic pathways to optimize patient outcomes and reduce health care system burden. DISCLOSURES: Dr Cong is an employee of Grail, LLC, which supported this study. Drs Gitlin and McGarvey are employees of BluePath Solutions, and Ms Shivaprakash was an employee of BluePath Solutions, which received financial support from Grail, LLC, for study-related research activities. This study was sponsored by Grail, LLC, a subsidiary of Illumina Inc. currently held separate from Illumina Inc. under the terms of the Interim Measures Order of the European Commission dated October 29, 2021. The sponsor had no role in the collection, management, and analysis of the data. The sponsor contributed to study design and data interpretation.

Symptoms and signs of lung cancer prior to diagnosis: case-control study using electronic health records from ambulatory care within a large US-based tertiary care centre

OBJECTIVE

Lung cancer is the most common cause of cancer-related death in the USA. While most patients are diagnosed following symptomatic presentation, no studies have compared symptoms and physical examination signs at or prior to diagnosis from electronic health records (EHRs) in the USA. We aimed to identify symptoms and signs in patients prior to diagnosis in EHR data.

DESIGN

Case-control study.

SETTING

Ambulatory care clinics at a large tertiary care academic health centre in the USA.

PARTICIPANTS, OUTCOMES

We studied 698 primary lung cancer cases in adults diagnosed between 1 January 2012 and 31 December 2019, and 6841 controls matched by age, sex, smoking status and type of clinic. Coded and free-text data from the EHR were extracted from 2 years prior to diagnosis date for cases and index date for controls. Univariate and multivariable conditional logistic regression were used to identify symptoms and signs associated with lung cancer at time of diagnosis, and 1, 3, 6 and 12 months before the diagnosis/index dates.

RESULTS

Eleven symptoms and signs recorded during the study period were associated with a significantly higher chance of being a lung cancer case in multivariable analyses. Of these, seven were significantly associated with lung cancer 6 months prior to diagnosis: haemoptysis (OR 3.2, 95% CI 1.9 to 5.3), cough (OR 3.1, 95% CI 2.4 to 4.0), chest crackles or wheeze (OR 3.1, 95% CI 2.3 to 4.1), bone pain (OR 2.7, 95% CI 2.1 to 3.6), back pain (OR 2.5, 95% CI 1.9 to 3.2), weight loss (OR 2.1, 95% CI 1.5 to 2.8) and fatigue (OR 1.6, 95% CI 1.3 to 2.1).

CONCLUSIONS

Patients diagnosed with lung cancer appear to have symptoms and signs recorded in the EHR that distinguish them from similar matched patients in ambulatory care, often 6 months or more before diagnosis. These findings suggest opportunities to improve the diagnostic process for lung cancer.

How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States

The diagnosis of lung cancer in ambulatory settings is often challenging due to non-specific clinical presentation, but there are currently no clinical quality measures (CQMs) in the United States used to identify areas for practice improvement in diagnosis. We describe the pre-diagnostic time intervals among a retrospective cohort of 711 patients identified with primary lung cancer from 2012-2019 from ambulatory care clinics in Seattle, Washington USA. Electronic health record data were extracted for two years prior to diagnosis, and Natural Language Processing (NLP) applied to identify symptoms/signs from free text clinical fields. Time points were defined for initial symptomatic presentation, chest imaging, specialist consultation, diagnostic confirmation, and treatment initiation. Median and interquartile ranges (IQR) were calculated for intervals spanning these time points. The mean age of the cohort was 67.3 years, 54.1% had Stage III or IV disease and the majority were diagnosed after clinical presentation (94.5%) rather than screening (5.5%). Median intervals from first recorded symptoms/signs to diagnosis was 570 days (IQR 273-691), from chest CT or chest X-ray imaging to diagnosis 43 days (IQR 11-240), specialist consultation to diagnosis 72 days (IQR 13-456), and from diagnosis to treatment initiation 7 days (IQR 0-36). Symptoms/signs associated with lung cancer can be identified over a year prior to diagnosis using NLP, highlighting the need for CQMs to improve timeliness of diagnosis.

Measured weight loss as a precursor to cancer diagnosis: retrospective cohort analysis of 43 302 primary care patients

BACKGROUND

Unexpected weight loss is a presenting feature of cancer in primary care. Data from primary care are lacking to quantify how much weight loss over what period should trigger further investigation for cancer. This research aimed to quantify cancer diagnosis rates associated with measured weight change in people attending primary care.

METHODS

Retrospective cohort study of primary care electronic health records data linked to the Surveillance, Epidemiology, and End Results cancer registry (Integrated healthcare delivery system in Washington State, United States). Multivariable Cox regression incorporating time varying covariates using splines to model non-linear associations (age, percentage weight change, and weight change interval). Fifty thousand randomly selected patients aged 40 years and over followed for up to 9 years (1 January 2006 to 31 December 2014). Outcome measures are hazard ratios (95% confidence intervals) to quantify the association between percentage weight change and cancer diagnosis for all cancers combined, individual cancer sites and stages; percentage risk of cancer diagnosis within 6 months of the end of each weight change episode; and the positive predictive value for cancer diagnosis.

RESULTS

There were 43 302 included in the analysis after exclusions. Over 287 858 patient-years of follow-up, including 24 272 (56.1%) females, 23 980 (55.4%) aged 40 to 59 years, 15 113 (34.9%) 60 to 79 years, and 4209 (9.7%) aged 80 years and over. Adjusted hazard ratios (95% confidence interval) for cancer diagnosis in a 60 years old ranged from 1.04 (1.02 to 1.05, P < 0.001) for 1% weight loss to 1.44 (1.23 to 1.68, P < 0.001) for 10%. An independent linear association was observed between percentage weight loss and increasing cancer risk. The absolute risk of cancer diagnosis increased with increasing age (up to 85 years) and as the weight change measurement interval decreased (<1 year). The positive predictive value for a cancer diagnosis within 1 year of ≥5% measured weight loss in a 60 to 69 years old was 3.41% (1.57% to 6.37%) in men and 3.47% (1.68% to 6.29%) in women. The risk of cancer diagnosis was significantly increased for pancreatic, myeloma, gastro-oesophageal, colorectal, breast, stage II and IV cancers.

CONCLUSIONS

Weight loss is a sign of undiagnosed cancer regardless of the interval over which it occurs. Guidelines should resist giving an arbitrary cut-off for the interval of weight loss and focus on the percentage of weight loss and the patient's age. Future studies should focus on the association between diagnostic evaluation of weight change and risk of cancer mortality.

Conceptual Framework to Guide Early Diagnosis Programs for Symptomatic Cancer as Part of Global Cancer Control

Diagnosing cancer earlier can enable timely treatment and optimize outcomes. Worldwide, national cancer control plans increasingly encompass early diagnosis programs for symptomatic patients, commonly comprising awareness campaigns to encourage prompt help-seeking for possible cancer symptoms and health system policies to support prompt diagnostic assessment and access to treatment. By their nature, early diagnosis programs involve complex public health interventions aiming to address unmet health needs by acting on patient, clinical, and system factors. However, there is uncertainty regarding how to optimize the design and evaluation of such interventions. We propose that decisions about early diagnosis programs should consider four interrelated components: first, the conduct of a needs assessment (based on cancer-site-specific statistics) to identify the cancers that may benefit most from early diagnosis in the target population; second, the consideration of symptom epidemiology to inform prioritization within an intervention; third, the identification of factors influencing prompt help-seeking at individual and system level to support the design and evaluation of interventions; and finally, the evaluation of factors influencing the health systems' capacity to promptly assess patients. This conceptual framework can be used by public health researchers and policy makers to identify the greatest evidence gaps and guide the design and evaluation of local early diagnosis programs as part of broader cancer control strategies.