Joshua J. Ofman, MD, MSHS

Cancer is soon to become the world’s leading killer. Despite significant advances in therapeutics and guideline-recommended tests that screen for 5 cancer types—a single cancer at a time—cancer kills nearly 1700 of our loved ones every day in the United States.

 The fact remains that even today, the majority of cancers still lack screening tests and are therefore detected too late and often not impacted by available therapies, leading to poor patient outcomes.

in developing novel therapeutics, these mortality numbers are simply unacceptable. As such, we believe the best chance at reducing cancer mortality is to increase focus on cancer prevention and early detection. Because age is an established risk factor for many malignancies, there may be a misperception that cancer is a disease of the elderly; however, cancer strikes all age groups.

Cancer is a disease that strikes great fear in many individuals, but it is also a disease of interest and concern for the self-insured and employers. Employers have a bigger stake in the health of their employees, employees’ families, and employee productivity than any other entity or institution in our society. As they balance strategies to optimize the health of their employees and beneficiaries while constraining growth in health care costs, employers find cancer represents a substantial challenge. This complexity relates to many factors, including a dearth of data on quality of care, as well as a lack of price transparency. These factors are magnified by the fact that the term “cancer” translates into hundreds of specific clinical scenarios, compared with hypertension or diabetes, with each having an extensive array of services needed to support employees and their families when faced with a cancer diagnosis.

Cancer is among the top diagnoses in terms of the number of claims and the total cost of treatment. In 2018 alone, there were 12 claims over $3 million, and 4 were driven by cancer-related treatments.

 Additionally, cancer was the most common million-dollar claim category for ages 40 to 59.

 Out-of-pocket costs for cancer treatments, including surgical procedures, radiation treatment, and chemotherapy totaled a whopping $5.6 billion in the United States in 2018.

 Not surprisingly, for the past several years, cancer has continually topped the list as both the number 1 and number 2 highest-cost claim conditions, accounting for 26.8% and $936.3 million of the total stop-loss reimbursements.

“Financial toxicity, ” which refers to the negative impact of rising out-of-pocket costs on patients’ physical and financial well-being, is well documented across numerous cancer diagnoses. Prospects to mitigate these cost pressures are bleak in that overall cancer costs continue to rise. The US expenditure on cancer-related health care is projected to increase from $183 billion in 2015 to $246 billion in 2030—an increase of 34%. These high costs are paid by people with cancer as well as their families, employers, insurance companies, and taxpayer-funded public programs like Medicare and Medicaid.

The direct costs of cancer care can be superseded by the indirect costs resulting from lost productivity.

 Estimates suggest that indirect costs represent the greatest proportion of total cancer costs to an employer in certain clinical circumstances, largely due to short-term and long-term disability.

 Cancer also contributes significantly to early retirement and premature death.

We have made great strides in the development of cancer therapeutics, particularly with specialty pharmaceuticals, but this has led to a parallel increase in cost. Notably, within the top 20 highest-cost injectable drugs, 71% of the spending was related to medications used to treat cancer. Furthermore, all of the top 5 highest-cost injectable drugs and 8 of the top 10 were drugs most commonly used in cancer treatment.

 Employers have expressed a substantial interest in better understanding how to improve the quality and reduce the cost of treatment once a diagnosis is made.

 This prompts us to ask: What if cancer diagnoses were made early enough to have treatments lead to superior patient-centered outcomes and more efficient health care spending?

Early detection of cancer can undoubtedly save lives, yet most cancers are diagnosed too late. It is well recognized that cancers diagnosed at earlier stages have dramatically better 5-year cancer-specific survival than cancers diagnosed after distant metastases.

 Even so, screening is currently recommended for only 5 types of cancers in the Unites States: breast, colorectal, cervical, lung (for high-risk individuals only), and prostate (on an individualized basis). Due to the lack of screening programs for other cancers, they are typically identified at advanced stages when outcomes are poor. Thus, these cancers without currently available screening tests account for about 71% of US cancer deaths among those aged 50 to 79 years old.

There is a misconception that we don’t screen for these cancers because treatments are unavailable. However, a review of evidence-based practice guidelines and peer-reviewed literature shows that nearly all early cancers have effective treatments, including watchful waiting for some non-aggressive malignancies such as early prostate cancers.

A paradigm shift in early detection of cancer is needed to impact the outcomes in patients’ lives. So, what if we were to transition from screening for individual cancers to screening individuals for all possible cancers? This could dramatically improve overall cancer detection, or the Cancer Detection Rate (CDR), in a population.

CDR is the overall number of cancers detected out of the total number of expected cancers in a monitored population. In the United States, for example, there will be an estimated 1.2 million cases of cancer in adults between the ages of 50 to 79 this year; mammography is expected to detect 114,000 of those 1.2 million cancers, yielding a CDR of approximately 9%. A combination of all 5 single-cancer screening tests will yield a CDR of only approximately 16%.

Although this is a notable accomplishment, it will not suffice by itself to bend the cancer mortality curve or address the public health crisis posed by cancer.

Rapid and significant advancement in genomic technologies shows great promise to develop a solution for the inability to diagnose a greater proportion of cancer cases. There are several novel multi-cancer early detection (MCED) tests nearing commercial availability.

 These MCED tests use sophisticated technologies to identify signals of early cancer in blood and can detect a variety of cancers, many of which are potentially lethal and currently have no recommended screening tests. The ease and convenience of cancer detection via a single blood draw is an important added advantage that could help achieve better compliance than existing single-cancer screening tests. Still, the goal is not to have an MCED test replace the current cancer screening paradigm, but rather to complement existing single-cancer screening tests.

An MCED test could easily be integrated during preventive care visits or routine blood tests, which approximately 70% of Americans aged 50-79 undergo at least annually.

 If everyone received an annual MCED blood test in addition to current screening tests, we could potentially increase the CDR to 50%. Notably, this could include detection of some of the deadliest cancers, such as pancreatic, stomach, and lung cancers, which all currently have 5-year survival rates of less than 50%.

Why is MCED such a groundbreaking idea? Because it is simply not feasible to spend billions of dollars over decades to develop and test new screening approaches for each individual cancer. An MCED test could increase CDRs, and yield low false-positive rates which could translate into tremendous benefits for the population. Used alone, MCED tests may still miss some cancers, but some detection is better than no detection.

From an employer’s perspective, stage of disease at diagnosis is an important predictor of clinical outcome and treatment cost, because treatment of advanced-stage cancer is often more intensive than earlier-stage cancer. MCED tests have the potential to reduce per-case resource utilization for cancer management by shifting cancer treatment to earlier stages when fewer resources are needed and cost of treatment is lower. Indeed, 2 to 4 stage I patients could potentially be treated for the same cost as treating 1 stage IV patient (GRAIL, Inc; unpublished data on file). Additionally, early detection of cancers leads to fewer disability claims and less frequent early departure from the workforce.

In conclusion, it is safe to say that the burden of cancer, both clinically and economically, is immense. While we are making advances in developing novel therapeutics, cancer screening or early detection technologies have not innovated at the same pace thus far, leading to unacceptable cancer mortality numbers. The development of MCED tests could help alleviate this crisis, because these tests could lead to early detection when patient outcomes are more favorable, and they could substantially increase the CDR when compared to the current strategy of single-cancer screening tests. The forthcoming commercial availability of MCED tests could potentially translate to an important value proposition for patients, employers, and payers due to their potential to improve patient-centered outcomes, and the use of MCED tests could lower direct and indirect costs associated with each case diagnosed.

Joshua J. Ofman, MD, MSHS is the chief medical officer and head of external affairs at GRAIL Inc. Azra Raza, MD is the Chan Soon-Shiong professor of medicine and director of the Myelodisplastic Syndrome (MDS) Center at Columbia University in New York, and author of “The First Cell: And the Human Costs of Pursuing Cancer to the Last.” A. Mark Fendrick, MD, is director of the University of Michigan Center for Value-Based Insurance Design.

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Articles

Multicancer early detection technology could help reduce cancer mortality compared to the current strategy of single-cancer screening tests. 

Novel Multicancer Early Detection Technology––Potential Value to Employers and the Workforce

Novel Multicancer Early Detection Technology—Potential Value to Employers and the Workforce

Few diagnoses strike more fear than cancer. My family members have personally been touched by both fatal cancer and early cancer caught at a curable stage, as well as a “scare” that fortunately turned out to be benign. I know the fear of cancer that keeps people up at night. Despite treatment advances, cancer still takes an overwhelming human toll: It is the second leading cause of death globally. Why? In large part, because we diagnose most cancers too late. Today, screening is only recommended by the US Preventive Services Task Force (USPSTF) for colon, breast, lung (in smokers), and cervical cancers. Most other cancer diagnoses are made when signs or symptoms appear, often when cancer has already metastasized.

Indeed, the 5-year cancer-specific survival is nearly 325% better among those diagnosed with localized disease than with distant metastases. Moreover,

 treatment of metastatic cancer is up to 2 times more costly than for nonmetastatic cancer.

 Even a modest 1% reduction in cancer mortality is projected to deliver $695 billion in economic value to society.

By projecting current USPSTF screening recommendations onto the US population aged 50 to 79 years at historical compliance rates, approximately 9 million positive tests would be generated and 151,000 cancers detected—a true-positive to false-positive ratio of 1:60. The high false-positive rates and detection of potentially nonlethal cancers (overdiagnosis) are some of the reasons that recommendations differ and debate continues.

We are at an unprecedented time, when the genomic revolution is driving insights into cancer biology, detection, prognosis, and management. New treatments are agnostic to tumor type, focusing on specific mutations shared by different cancers. Advances in next-generation sequencing and machine learning have enabled detection and sequencing of highly specific cancer-derived DNA signals in blood. Identification of methylation patterns in DNA has been shown to be a superior mechanism for cancer signal detection than looking for mutations or somatic copy number alterations.

What if we could leverage this transformational technology and add to current screening with a blood test that could detect multiple deadly cancers, with a combined false-positive rate of less than 1%? Such a test could detect 3 times more cancers (~460,000) and do so much more efficiently, with a true-positive to false-positive ratio of only 1:2.4.

How do we get there? Recent reports of blood-based approaches show that detecting multiple cancers is possible at high specificity.

 To get these to the clinic, it will be important for stakeholders—policy makers, payers, healthcare providers, and patients&mdash;to shift their thinking around what is possible and to help ensure that there are mechanisms in place to provide access to this innovative technology to detect cancer early, when treatments are most effective.

This approach has the potential to address an enormous unmet medical need. There remains work to do to understand how a blood-based approach to early detection will work in actual practice and to evaluate patient and provider acceptance. But the promise is clear: Detecting cancer at earlier stages should translate into improved outcomes, reduced harms from unnecessary work-ups, and potentially lower costs—which could allow everyone to sleep better at night.

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From the Editorial Board: Joshua J. Ofman, MD, MSHS

To systematically evaluate and synthesize publishedevidence regarding the effect of disease management programs forpatients with diabetes mellitus on processes and outcomes of care.

Systematic literature review and meta-analysis.

Computerized databases were searchedfor English-language controlled studies assessing the effect of diabetesdisease management programs published from 1987 to 2001.Two reviewers extracted study data using a structured abstractionform. Pooled estimates of program effects on glycated hemoglobinwere calculated using an empirical Bayes model.

The pooled estimate of program effects on glycatedhemoglobin was a 0.5-percentage point reduction (95% confidenceinterval, 0.3 to 0.6 percentage points), a modest but significantimprovement. Evidence also supports program benefits inimproving screening for retinopathy and foot lesions.

Diabetes disease management programs canimprove glycemic control to a modest extent and can increasescreening for retinopathy and foot complications. Further effortswill be required to create more effective disease management programsfor patients with diabetes mellitus.

Diabetes mellitus creates a significant clinical andeconomic burden on society.

For 1998, directand indirect costs of diabetes mellitus and itscomplications are estimated at $98.2 billion in theUnited States.

Standards of care for diabetes mellitushave been broadly disseminated since the 1980s

in thebelief that improved processes of care can improvepatient outcomes,

but primary care providers havebeen slow to implement patient care guidelines and&#160;recommendations.

Several barriers to guideline adherenceand implementation have been identified,

including the perception that type 2 diabetes mellitus isnot serious, that aggressive treatment cannot forestallcomplications,

that guidelines are not flexibleenough to be useful in patient care,

and that patientswith diabetes mellitus are unwilling to make neededlifestyle changes.

Given their numbers and economic effect, improvingcare for patients with diabetes mellitus has become apriority for health plans, payers, and patients. The numberand complexity of services required to manage suchpatients in accord with accepted guidelines have madediabetes mellitus the target of multiple disease managementefforts, as well as targeted efforts involving professionaleducation and case management.

Other reviews have addressed the effectiveness ofprofessional education and structure of care

in improving patient outcomes. Theobjective of this study is to systematically evaluate thepublished literature on the effectiveness of diabetes diseasemanagement programs—defined as structured,multifaceted, systematic approaches to care—onglycemic control and other relevant outcomes.

team, patient care planning, primary nursing care,

case management, critical pathways, primary health

care, continuity of patient care, guidelines, practice

guidelines, disease management, comprehensive

A systematic review of the medical literature wasperformed with the assistance of an expert librarian,using the computerized bibliographic databases MEDLINE,HealthSTAR, and Cochrane Database of SystematicReviews to identify assessments of diseasemanagement programs in different areas. English-languagestudies published between January 1987 andJune 2001 were identified and reviewed, with the 1987date reflecting the approximate beginning of widespreadinterest in disease management. Search terms includedthe following Medical Subject Headings: 

Ahand search of bibliographies from relevant articles andreviews was also conducted, and the opinions fromexpert physicians and researchers in the field weresolicited to identify other references.

We defined disease management according to a previouslypublished definition used by Ellrodt et al.

Programs that used a systematic approach to care andincluded more than 1 intervention component (anappendix listing the classification of interventions isavailable from the authors upon request) were consideredas using disease management. Trials of pharmacologicalagents were excluded. A systematic approach tocare was defined as inclusion of any of the followingcomponents: guidelines, protocols, algorithms, careplans, or systematic patient or provider education programs.Unstructured professional education and casemanagement programs were not included.

Specific inclusion and exclusion criteria were developedfor reviewing titles, abstracts, and articles. Tworeviewers (KK, EB) trained in health services researchand in the principles of critical appraisal independentlyreviewed a 10% sample of randomly selected studies,with any discrepancies resolved by consensus. Theremaining studies were distributed among reviewersonly when a sufficient level of agreement was achieved(&#954;>0.7).

Titles were rejected if they did not deal with adultpatients or were reviews, case reports, editorials, letters,or meeting abstracts. Abstracts were rejected if they didnot report any objective measurements of disease management,referred to clinical trials comparing singlepharmacological agents or diagnostic procedures, or didnot use a systematic approach to care. Studies wererejected if they lacked sufficient information to measurethe effect of an intervention on at least 1 outcome ofinterest and its variance. To measure the effect of agiven intervention, studies should have used an experimentalor quasi-experimental study design meeting thecriteria established by the Cochrane Effective Practiceand Organization of Care Group and should haveincluded an appropriate comparison group. Acceptabledesigns included randomized clinical trials and controlledbefore-and-after studies (studies with a parallelnonrandomized comparison group, with baseline andfollow-up assessments of both groups).

From the pool of accepted disease managementassessments, those aimed at the management of diabetesmellitus were selected. Study information was abstractedfrom the accepted articles using a standardized dataabstraction form and included the following: studydesign, setting, intervention strategies, and outcomesof interest. All components of the disease managementintervention were identified using classifications basedon definitions taken from the Cochrane Collaborationfor providers, patients, and organizations.

Outcomesfrom the following 12 domains were collected: glycatedhemoglobin (GHb) levels, serum lipids (low-densitylipoprotein [LDL] cholesterol, high-density lipoprotein[HDL] cholesterol, and total cholesterol), systolic bloodpressure, hospital admissions, mean number of GHbtests per patient, screening for retinopathy, screening fornephropathy, foot screening, foot self-care, patientknowledge, self-reported health status, and patient satisfaction.If a study reported outcome measures at multipletime points for a single domain, results from thelongest follow-up were used. If the serum LDL cholesterollevel was reported, it was used instead of the totalcholesterol level. Systolic blood pressure was abstractedas it is a better predictor of cardiovascular events thandiastolic blood pressure.

One observation per outcomewas abstracted for each intervention arm, so studiesevaluating more than 1 intervention could contributemore than 1 observation per program.

To account for baseline differences in GHb levelsbetween groups, the mean changes over baseline werecompared. Given the fact that certain data elementsmay not be provided in the identified studies, we createda list of assumptions a priori to facilitate the meta-analysis.In the 3 instances in which baseline meanswere not reported, the assumption that the treatmentand control group baseline means were equal was used.Variances of changes were rarely reported. In thoseinstances lacking reported variances, the variance ofthe change was assumed to be equal to one half of thesum of the variances of the baseline and follow-up measures.In the absence of baseline variances, it wasassumed that baseline variances in the treatment andcontrol groups were equal to the follow-up variance inthe control group.

A test for homogeneity was performed using the &#967;

test. The more conservative random-effects method(the empirical Bayes method proposed by Hedges andOlkin

) was used to pool the estimated program effectson GHb levels.

Results are reported as the pooled differencesin change in GHb level in treated versus controlsubjects. Although there are subtle differencesbetween the various species of GHb, all refer to anddescribe the modification of hemoglobin by a sugar(ie, glucose).

As part of an exploratory data analysis, funnel plotswere constructed by plotting each program's estimatedeffect on change in GHb against the inverse of its variance to assess potential publication bias.

to determine if adjustmentsfor publication bias were warranted and, if so, to adjustthe estimates. Stata 8 (StataCorp LP, College Station,Tex) was used to perform this analysis.

The initial search strategy identified 16 917 references.A total of 2963 titles were accepted for furtherscreening, and 581 abstracts met inclusion criteria.Eighty-five percent (n = 493) of the accepted abstractsfailed to meet inclusion criteria when the articles werereviewed. Bibliographic hand searches and expert consultationyielded an additional 53 articles for review, ofwhich 16 were accepted. Twenty-four studies

Of 24 studies meeting our inclusion criteria, 19 studieswere randomized clinical trials and 5 studies

were nonrandomized controlled studies.Five

of 19 randomized trials used a clusterrandomization scheme for treatment allocation. Theaggregate sample size for the 24 studies was 6421patients, and the total number of patients studied ineach report ranged from 38 to 1939. More than half(15/24) of the studies were conducted in the UnitedStates, 4 were carried out in the United Kingdom, andthe remaining 5 were conducted in Israel, Argentina,Austria, and the Netherlands. Study duration rangedfrom 3 months

while the duration ofthe disease management intervention ranged from severaldays

Key characteristics of identifiedstudies are available from the author.

Most (20/24) studies were funded by research grantsprovided by governmental offices, academia, or researchfoundations. Four studies

received additional supportfrom pharmaceutical companies. Four studies

assessed disease management costs in relation to a primarycare or health maintenance organization setting,while cost per patient

were assessed in 2 studies each. Differentinterventions were used, ranging from patient educationsessions to centrally administered provider remindersto integrated multidisciplinary team approaches.

contributing 24 observationsand involving 3720 patients, were included inthe meta-analysis to evaluate the effect of disease managementon GHb level. Of these 24 treatment-controlcomparisons, 9 (38%)

reported statisticallysignificant differences favoring the treatmentgroup. The rest showed no significant differences; inone

of those studies, a treatment arm experienced anincrease in GHb level relative to the comparison arm.Significant heterogeneity in results was confirmed bythe results of our test for homogeneity (

<.001).Overall, the pooled result (using a random-effectsmodel) showed that disease management programsresulted in a statistically significant reduction in GHblevel (mean reduction, 0.5 percentage point; 95% confidenceinterval [CI], 0.3 to 0.6 percentage points). Wealso calculated results based on geographic location (USvs non-US studies). The mean reduction in GHb levelfor US observations (n = 16) was 0.6 percentage point(95% CI, 0.4 to 0.9 percentage points), while the meanreduction for non-US observations (n = 8) was 0.32 percentagepoint (95% CI, 0.01 to 0.54 percentage points).However, the small number of trials in countries outsidethe United States limits conclusions.

Programs associated with the greatest estimatedchanges in GHb levels include 1 program involving pharmacistscounseling patients and medication adjustment

and 2 programs involving combined physicianand patient interventions.

Small sample size limitsgeneralizations with regard to effects of different types ofprograms. A study by Vinicor et al,

including arms withstructured physician education alone and in combinationwith patient education, demonstrated improvedresults with the combination program. The 

is aforest plot displaying estimated program effects on GHb.

involving 958 patients, assessedthe effect of disease management on the frequency ofglycemic monitoring (

). These measured themean number of GHb tests per patient, percentage ofpatients who had a GHb test, and mean number of self-monitoredblood glucose levels. Two studies

reportedsignificant increases in the frequency of GHb testsperformed in intervention patients. A third study

showed no change in the percentage of patients whoreceived at least 1 GHb test. The study by Piette et al,

involving 292 subjects, found that program patientswere more likely to perform home glucose monitoringthan control patients.

with 708 patients, investigatedthe effect of disease management on the frequency ofretinal examinations (Table 1). Two studies

evaluatedthe mean number of retinal examinations performedper patient, while the third study

examined the percentageof patients receiving an ophthalmologic examination.Two studies

showed a small but statisticallysignificant improvement in the frequency of retinalexaminations. One study

reported that a slightly higherproportion of patients in the intervention groupreceived an eye examination.

involving 447 patients, assessedprogram effects on screening for nephropathy (Table 1).One study

reported that slightly more patients in theintervention group were screened for nephropathy.Another study

showed that the mean number ofscreening tests for nephropathy was similar in the interventionand control groups. The last study

demonstrateda statistically significant decrease in serumcreatinine levels in the intervention patients.

involving 1912 patients, examinedthe effects on the frequency of foot screening(Table 1). Of these, 2 studies

evaluated the percentageof patients receiving foot examinations, whileanother study

evaluated the mean number of footexaminations performed per patient. All 3 studiesshowed that programs increased the number of footexaminations performed, with the study by Naji et al

demonstrating a statistically significant improvementwith disease management.

with 547 patients evaluated the proportionof patients referred to a podiatrist. One study

showed an increase in referrals from primary carephysicians to a podiatrist, while the other study

reported fewer referrals in intervention patients.

with 817 patients, evaluatedpatient foot self-care (Table 1). One study

found thatthe control group patients examined their feet significantlymore frequently than those in the treatmentgroup. Another study

showed that patients in theintervention group examined their feet more often thanthose in the control group. The third study

reportedthat intervention patients practiced more appropriatefoot care behaviors compared with control patients.This difference was statistically significant.

(7 observations), with 1239patients, assessed program effects on systolic blood pressure(

). Control group patients from the Vinicorstudy were accounted for once to avoid double counting.

Of these 7 assessments, 5 reported a decrease insystolic blood pressure in the treatment group.

However, only 1 of these yielded a statistically significantreduction.

Two showed a slight improvement in thecontrol group relative to the intervention group, but the resultswere not statistically significant.

Joshua J. Ofman, MD, MSHS

Articles

Novel Multicancer Early Detection Technology––Potential Value to Employers and the Workforce

Novel Multicancer Early Detection Technology—Potential Value to Employers and the Workforce

From the Editorial Board: Joshua J. Ofman, MD, MSHS

A Systematic Review of Diabetes Disease Management Programs