Managed Care Updates: April 2022

Further Analysis Needed to Incorporate Liquid Biopsy in Community Setting

Potential benefits of incorporating liquid biopsy into community-
based oncology practices include early signal-based therapeutic matching, referral to appropriate signal-based clinical trials, and improved survival outcomes, according to retrospective study findings published in The Oncologist. This study was conducted using charts from 178 patients receiving care for advanced solid malignancies at Cancer Center of Wichita, Kansas, and a liquid-based assay was used to evaluate these malignancies between December 2018 and December 2019. Liquid biopsy has a favorable utility profile in that it is less invasive vs tissue-based biopsy, and next-generation sequencing of circulating tumor DNA has higher sensitivity, they highlighted.

There was a follow-up at 1 year to evaluate treatment assignment and survival. Study end points included progression-free survival (PFS) in cases of lung, breast, and colorectal cancer and overall survival (OS) in patients with lung, breast, and colorectal cancer.

“Liquid biopsy testing offers a significant potential in selecting signal-matched therapies for advanced solid malignancies,” the authors wrote. “The feasibility of liquid biopsy testing in a community-based oncology practice, and its impact on selecting signal-matched therapies, and subsequent survival effects have not previously been reported.”

Among the 178 patients tested, 98% tested had a new diagnosis, advanced cancer, or recurrent disease with not enough tissue for testing. The remaining 2% were tested following first-line treatment failure. Most patients also had stage IIIB disease and above, the mean age at diagnosis was 65 years, and the most common cancers were lung (50.56%), breast (17.42%), and colon (7.87%).

Seventy-nine percent of the study cohort (n = 140) tested positive for mutations, with these individuals subdivided into patients with actionable mutations with an FDA-approved targeted treatment (n = 32), actionable mutations with an FDA approval used off-label (n = 73), and unactionable mutations (n = 35).

Overall, 481 genetic alterations were identified, with the mean per liquid biopsy being 3.1 (2.14). The highest average per test were seen among colon cancer (4.36), breast cancer (2.97), prostate cancer (2.73), and lung cancer (2.59). The 3 cancers with the most detected somatic mutations overall were lung, breast, and colon, respectively.

Of the 481 total alterations, 95% were actionable. Within this group, the most common altered genes were TP53 (32.17%), PIK3CA (8.53%), EGFR (7.66%), and KRAS (7.22%).

Ninety-five percent of those who tested positive for mutations were candidates for targeted treatment (n = 135), with most receiving an unmatched therapy. Further, for those designated candidates for FDA-approved treatments, only half received a targeted treatment, close to 7% received a treatment off-label, and 10% were referred to signal-based clinical trials. The most common reason for not receiving a signal-matched treatment among participants with 1 or more actionable mutations was treatment availability.

Following a subanalysis of survival rates at 1 year seen among patients with lung, breast, or colon cancer who received a matched therapy following liquid biopsy and those who did not, the following results were seen:

• The matched group had more patients with breast cancer vs the unmatched group: 27.3% vs 15.9%
• Fewer patients with lung cancer and colorectal cancer were seen in the matched vs unmatched group: 63.6% vs 72.7% and 9.1% vs 11.4%, respectively
• Median overall survival (mOS) was 13 (range, 11.4-14.6) months
  The matched vs the unmatched cohort had a longer mOS (15 vs 13 months) and PFS (12 vs 5 months).
• Statistically significant differences were not seen in either OS or PFS among the patients who received matched treatment and had higher or lower matching scores (ie, the higher the score, the better the treatment match, according to the authors).

The study authors highlight that their findings are important because their patients were tested up front for alterations, prior to treatment, vs having already undergone several lines of treatment, and the results echo previous research. In addition, their data bear out that combining matched therapies for use in patients with several actionable mutations is a potential treatment pathway. “Other studies have also suggested that treatment with single-agent matched therapy resulted in significantly lower response rates compared [with] combination therapy,” the authors wrote.

Still, large prospective controlled clinical trials are needed to confirm their findings and to investigate whether providing community-based liquid biopsy testing facilitates betterment of quality of life, early cancer detection, disease monitoring, and cost benefits compared with tissue-based biopsy. 

Reference
Choucair K, Mattar BI, Truong QV, et al. Liquid biopsy-based precision therapy in patients with advanced solid tumors: a real-world experience from a community-based oncology practice. The Oncologist. 2022; 10.1093/oncolo/oyac007. doi:10.1093/oncolo/oyac007


Study on Types of Pain in MM Reveals Communication Inadequacies Between Physicians, Patients

In addition to experiencing bone pain, patients with multiple myeloma (MM) were found to experience multiple types of pain, including significant physical, social, and emotional pain, signaling that there is a disconnect between health care providers and patients in how pain symptoms and severity are reported and managed.

The study findings, which were published in Pain Management, found discordance in the communication between patients and physicians, leading to many physicians underestimating or underreporting pain symptoms and severity among their patients, showing that improved pain communication between parties is needed.

“Strategies to reduce the burden of bone pain, including patient education surrounding bone health, lifestyle changes, physical activities as prevention techniques, and supplements and medications to support bone health and prevent bone complications, should also be implemented, as well as optimizing professional qualification of the treatment physician,” the investigators wrote.

Despite knowing pain management is integral to cancer care and that patients with MM experience a high-symptom burden, undertreatment of pain is common. Some of the reasons that patients’ pain goes undertreated can include patients and physicians lacking knowledge or understanding about pain, a physician may fail to understand the impact of pain on patients with cancer, and potential poor communication between physicians and patients. Additionally, a patient may be reluctant to admit they are in pain, and there is a lack of published studies on the different aspects of pain that affect people with cancer.

Between November 20, 2017, and February 1, 2018, the investigators collected data from the Adelphi Multiple Myeloma Disease-Specific Programme patient-level database, which contained information from surveys that were conducted during routine in-person appointments in Germany and Italy. For eligibility, patients had to be 18 years or older, have symptomatic MM, and have received either first-line or second-line MM therapy. A detailed questionnaire was completed by a treating physician for each patient.

In total, 330 patients were included, 62.7% of whom were women and 65.5% were retired. The mean age of the cohort was 68 years. The median time since receiving an MM diagnosis was 0.97 years. Overall, 277 had clinically important physical pain, with 73 reporting no physical pain, 161 reporting mild pain, 81 experiencing moderate pain, and 15 patients having severe pain. Most of the cohort (87.6%) said they had experienced bone pain during the 7 days prior to the survey.

The investigators said there was a low level of agreement between patient and physician responses regarding bone pain and bone pain symptoms. Approximately half of physicians were found to have underestimated the severity of bone pain that their patients experienced, and not all patients who experienced bone pain had their symptoms recorded by a physician.
Of the 327 patients who responded about emotional pain, 58% said they experienced clinically important emotional pain. Among the 329 patients who gave responses about social pain, 74 reported clinically important social pain. Emotional and social pain became progressively worse with increasing MM severity.

“Simply relying on the physical aspect of pain may not adequately reflect the true severity and impact of pain in clinical practice. Our findings suggest that a comprehensive assessment of pain must consider not [only] physical symptoms but also other dimensions, including social and emotional factors, relating to burden of disease and quality of life,” the investigators said. The investigators also suggested physicians adopt a more holistic approach to pain identification and management, where providers ask open-ended questions to consider all aspects of pain to reduce symptoms and improve quality of life.

The study had some limitations, including that the proportion of patients with severe pain was small. Additionally, collecting data during consultations prevented the authors from making conclusions on causal relationships. “As health care evolves and patient-physician consultations shift from face-to-face clinics to virtual consultations, it is even more important that communication on pain and symptom burdens of disease are effective, and the patient voice is captured accurately,” the investigators said. 

Reference
Quinn B, Ludwig H, Bailey A, et al. Physical, emotional and social pain communication by patients diagnosed and living with multiple myeloma. Pain Manag. 2022;12(1):59-74. doi:10.2217/pmt-2021-0013

Possibility of Breast Cancer Overdiagnosis Should Inform Mammography Decisions

Although their findings of breast cancer overdiagnosis from annual or biennial mammography were not as high as previous studies, the authors of a new study published online in Annals of Internal Medicine caution their findings also indicate need for increased collaborative decision-making on this screening method.

For their study, they defined overdiagnosis as, “mammographic detection of cancer that would not become clinically relevant in the woman’s remaining lifetime.” They also placed blame on variations in overdiagnosis definitions, study settings, and estimation methods for the 0% to 54% estimate in overdiagnosis range found.

“Knowledge about overdiagnosis is critical for supporting shared decision-making, as recommended by the United States Preventive Services Task Force and the American Cancer Society,” they wrote. “However, the risk for breast cancer overdiagnosis in contemporary screening programs remains uncertain.”

Their data on 35,986 women of ages 50 to 74 years (12.1% Black, 19.0% Asian, and 64.4% White), who underwent 1 or more screening mammograms from 2000 to 2018 at a Breast Cancer Surveillance Consortium (BCSC) facility, showed 82,677 total mammograms (mean, 2.3 [range, 1-17]) and a 0.87% breast cancer diagnosis rate (n = 718 cancer diagnoses; 79.0% invasive; 21.0% in situ). For those cases determined to be preclinical cancers (those that have not produced symptoms or signs of cancer), 4.5% (95% CI, 0.1%-14.8%) were nonprogressive.

The authors’ lead-time estimation method incorporated progressive and nonprogressive cancer probability, and their final model consisted of age-dependent incidence of preclinical disease, sensitivity of screening examinations to detect a preclinical cancer, chance of a preclinical cancer to be nonprogressive, and time from onset of progressive preclinical disease to detection with clinical symptoms or signs. Study inclusion was prohibited based on mammography or breast cancer history before a first BCSC-based mammogram, and the final date of follow-up was first breast cancer, death, 2009 for 2 BCSC registries, 2018, and lack of attendance at a BCSC facility.
In addition, when considering contributions from biennial screening, an overall 15.4% (95% CI, 9.4%-26.5%) were characterized as being overdiagnosed. Of this group, 6.1% (95% CI, 0.2%-20.1%; 40% overall) were determined to be indolent, or slow-growing, preclinical cancers. The remaining 9.3% (95% CI, 5.5%-13.5%; 60% overall) were progressive preclinical cancers, or “cancer that would not have progressed to clinical cancer before death from a breast cancer–unrelated cause,” the authors wrote.

According to their findings, the study authors posit that for women aged 50 to 74 years who undergo a screening mammography every other year, among those with cancer diagnosed, just over 14% of those cases constitute an overdiagnosis. The rate of overdiagnosis was also shown to almost double among the age range analyzed: 11.5% (95% CI, 3.8%-28.3%) to 23.6% (95% CI, 17.7%-31.9%) from ages 50 to 74 years, respectively.
Further, according to screening round (first or last mammogram, respectively), detected progressive and nonprogressive preclinical cancers influenced the total predicted overdiagnosis rate differently:

• Nonprogressive cancer: 8.4% (95% CI, 0.3%-26.4%) to 5.5% (95% CI, 0.2%-17.0%)
• Progressive cancer: 3.1% (95% CI, 1.6%-5.1%) to 18.1% (95% CI, 11.9%-24.5%)

The authors note that their findings on overdiagnosis are both higher than previous modeling studies because of differences in screening practices, diagnostic practices, and modeling assumptions, and lower than excess-incident studies because they are “prone to overestimation.”

An accompanying editorial noted the ongoing controversy surrounding breast cancer overdiagnosis and proposed several solutions, including the following:

• Prediction models must be more accurate to influence treatment decisions
• Screening technologies must improve to reduce the risks of overdiagnosis and missing breast cancer already missed by mammography
• Screening mammograms could be more effective if they are part of individualized (by risks and preferences) multipronged strategies for cancer risk reduction

Still, the authors of the present study believe their results are strong because of the several sensitivity analyses they conducted. Their Bayesian modeling approach showed lack of influence on their predictions from model structure and prior distribution variations and accounted for parameter uncertainty, respectively. Because of this, they hope their findings will contribute to a more informed mammography screening process.

“We hope our findings will bring the field closer to a consensus estimate and facilitate decision-making about mammography screening,” they said. “Our estimates of the frequency and age dependence of overdiagnosis can be provided along with information about false-positive rates to balance estimates of mammography screening benefits as part of a process of shared and informed decision-making.” 

Reference
Ryser MD, Lange J, Inoue LYT, et al. Estimation of breast cancer overdiagnosis in a U.S. breast screening cohort. Ann Intern Med. 2022; 10.7326/M21-3577. doi:10.7326/M21-3577

Study Evaluates Impact of AE Severity on Health State Utility for CAR T Treatment in LBCL

With multiple chimeric antigen receptor (CAR) T-cell therapies available, understanding the health state utilities associated with toxicities of treatment can provide a way to compare the value of these treatments. As may be expected, more severe adverse events (AEs) are associated with greater disutility, or utility decrease, in large B-cell lymphoma (LBCL), according to a study published in PharmacoEconomics – Open.

Two important toxicities associated with CAR T-cell therapies are cytokine release syndrome (CRS) and neurological events (NEs). Both can become severe and require intensive treatments. Rates of severe CRS have ranged from 2% to 22% in clinical trials for various CAR T-cell therapies, and rates of NEs have ranged from 10% to 28%.

“As more CAR T-cell treatments are introduced, cost-utility analyses (CUAs) can be used to examine their value and inform decision-making on health care resource allocation,” the authors said. Health state utilities, which are valued to 0 (dead) and 1 (full health), are factored into CUAs to calculate quality-adjusted life-years. “Because the CAR T-cell therapies differ in the rates of CRS and NEs, a CUA comparing these treatments should incorporate utility differences associated with these [AEs].”

The investigators estimated health state utilities associated with CAR T-cell therapy toxicities using health state vignettes based on literature review, AE reports from a trial, and clinician input.

A total of 6 health states were developed, describing a year in the life of a patient with LBCL who experienced various AEs after CAR T-cell therapy and prior to recovery.

Health state A: no AEs
Health state B: grade 1 CRS
Health state C: grade 2 CRS
Health state D: grade 3/4 CRS
Health state E: grade 1/2 NE
Health state F: grade 3/4 NE

The clinician reports of the typical patient experience of each AE and the published literature of AE reports from a clinical trial were used to maximize the representativeness of these health state vignettes. A pilot study tested the time trade-off methods with a sample of the general population. The EQ-5D-5L, which comprises 5 dimensions to describe and value health, was administered to characterize the health status of the sample population.
A total of 366 potential participants were reached but only 218 interviews were included in the analysis, with 113 patients from London and 105 patients from Edinburgh. Although age, sex, marital status, and education level were similar between the 2 groups, the Edinburgh group had a higher rate of White patients and a lower rate of patients employed full time.
Depression, anxiety, diabetes, arthritis, and hypertension were the most common medical and mental health conditions, but 43.6% reported no health conditions. None of the participants reported having a diagnosis of LBCL, but 9 said they knew someone with LBCL. Another 5 participants were diagnosed with another type of lymphoma, and 57 knew someone with another type of lymphoma. The results of the EQ-5D-5L found few issues with mobility, self-care, usual activities, pain/discomfort, and anxiety/depression.

In the study, the participants ranked the health states in order of preference, with health state A (no AEs) ranked as most preferable by all participants, health state D (grade 3/4 CRS), and health state F (grade 3/4 NE) ranked as least preferable. Mean rankings from most preferred to least were A, B, E, C, F, and D. Mean utility scores ranked from most preferred to least were A (0.73), B (0.71), E (0.69), C (0.68), F (0.55), and D (0.50).

“Grade 3/4 AEs [described in health states D and F] had substantially larger disutilities than the less-severe AEs [described in health states B, C, and E],” the authors wrote. These are life-threatening events that require longer hospitalization and possibly intensive treatments, such as mechanical ventilation.

Participants were most willing to trade time in perfect health to avoid living in health state D (89.0%), followed by F (86.7%), C, E (78.9%), B (75.2%), and A (72.0%). “Most participants perceived all health states as better than dead,” they noted. The Edinburgh group has consistently lower utility scores for health states B through F, but there was no significant difference in the utility for health state A.

The limitation of this kind of study is that the scores represent the general population and not the experience of the actual patients. “The rates and severity of the AEs represented in the health states can differ across the CAR T-cell treatments. By incorporating disutility of these AEs, CUAs can more accurately and comprehensively model the differences among available treatments for LBCL,” the authors said. 

Reference
Howell TA, Matza LS, Jun MP, Garcia J, Powers A, Maloney DG. Health state utilities for adverse events associated with chimeric antigen receptor T-cell therapy in large B-cell lymphoma. Pharmacoecon Open. 2022;10.1007/s41669-021-00316-0. doi:10.1007/s41669-021-00316-0