Real-World Insights on Biomarker Testing Patterns and Implications for mNSCLC Therapy Selection

This supplement was supported by AstraZeneca.

ABSTRACT

Background: Biomarker testing is essential for guiding first-line treatment decisions in metastatic non–small cell lung cancer (mNSCLC). Despite guideline recommendations, real-world testing patterns remain variable and may contribute to disparities in outcomes.

Objectives: This study examined real-world biomarker testing patterns and their associations with first-line treatment selection, clinical characteristics, and sociodemographic factors in patients with newly diagnosed mNSCLC.

Methods: Using the Healthcare Integrated Research Database, we identified adults diagnosed with mNSCLC between January 2019 and July 2022 with continuous health plan enrollment. Patients were categorized by the type of biomarker testing they received within 90 days of diagnosis; eligible patients had: (1) no biomarker testing, (2) immunohistochemistry (IHC) only, (3) testing of fewer than 5 genes (<5GT) plus IHC, or (4) testing of at least 5 genes (≥5GT) plus IHC. Multivariable analyses assessed associations between testing, treatment patterns, and social determinants of health.

Results: Among 5611 eligible patients, 7.8% had no biomarker testing, 54.0% had IHC only, 13.2% had <5GT plus IHC, and 25.0% had ≥5GT plus IHC. Overall, 61.8% of patients did not receive guideline-concordant testing. More comprehensive biomarker testing was associated with a higher likelihood of receiving targeted therapy or immunotherapy and a lower use of chemotherapy alone. Testing and treatment patterns varied significantly by socioeconomic status, race/ethnicity, insurance type, and geographic region. Patients in higher socioeconomic quartiles, with commercial insurance, or residing in the western US were more likely to receive targeted therapies.

Conclusions: Most patients with mNSCLC did not undergo comprehensive biomarker testing, leading to potential missed opportunities for precision therapy. Disparities in testing and treatment underscore the need for expanded access to molecular diagnostics, payer support for comprehensive testing (including liquid biopsy), and alignment with national guidelines to improve outcomes and advance equitable cancer care.

Am J Manag Care. 2026;32:S27-S37

For author information and disclosures, see end of text.

Introduction

Lung cancer is second only to skin cancer as the most common malignancy in the United States; about 87% of these cases involve a histology of non–small cell lung cancer (NSCLC).1 In 2017, 44.1% of patients with NSCLC had metastatic disease at diagnosis. From 2010 to 2017, the 5-year survival estimate among patients with metastatic NSCLC (mNSCLC) was 5.8%.2

Effective targeted therapy choices for mNSCLC in patients with actionable mutations in EGFR, ALK, KRAS, ROS1, BRAF, NTRK1/2/3, MET exon 14 skipping, RET, ERBB2 (HER2), or NRG1, and those with HER2 or HGFR(c-Met)/MET protein overexpression have grown in recent years.3,4 Biomarker testing plays a critical role in identifying actionable mutations, guiding therapy choices, and improving lung cancer outcomes.3-5

Biomarker testing, however, poses such challenges as higher costs for comprehensive testing,6 uneven coverage of biomarker testing by health insurance plans,7 and prior authorization requirements,8 which can delay access to tests. Further, some providers may benefit from additional biomarker support, including which markers to test for and how to interpret results for optimal first-line treatment aligned to guidelines.9 Finally, turnaround times for test resultscan further delay treatment and prompt providers to reconsider the benefits of testing.7

Biomarker Testing in Current Guidelines

Over the last several years, clinical practice guidelines for NSCLC issued by National Comprehensive Cancer Network (NCCN®) have highlighted the importance of testing for gene alterations before selecting treatment.3-5 From August 2018 through December 24, 2025, NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) specifically recommended that patients with nonsquamous mNSCLC (adenocarcinoma, large cell carcinoma, or NSCLC not otherwise specified) be tested for EGFR and BRAF mutations, ALK and ROS1 rearrangements, and PD-L1 expression (Table 1).3-5 Patients with nonsquamous NSCLC represent 70.6% of individuals with NSCLC.2

As the list of available therapies has grown, NCCN has recommended testing for more alterations. As of December 24, 2025, testing for alterations in KRAS, NTRK1, NTRK2, NTRK3, MET exon 14 skipping, RET, ERBB2 (HER2), or NRG1, and for HER2 or HGFR(c-Met)/MET protein overexpression, is also recommended for patients with nonsquamous mNSCLC.3,4

Since August 2018, NCCN has maintained testing for EGFR and ALK alterations as Category 1 recommendations. These are based upon high-level evidence (≥1 randomized phase 3 trials or high-quality, robust meta-analyses) and represent uniform NCCN consensus (≥85% support of the Panel) that the intervention is appropriate.3-5 During this time, NCCN has also recommended immunohistochemistry (IHC) testing for PD-L1 and recognized IHC testing for ALK alteration.3,4

In August 2018, NCCN noted the availability of a companion diagnostic next-generation sequencing (NGS) test to screen for all the alterations for which NCCN recommended testing (ie, in EGFR, BRAF, ALK, and ROS1).3 NGS constitutes a multigene, panel-based approach to identify actionable genetic mutations and biomarkers that can guide treatment decisions.10 However, NCCN added that not all NGS platforms can screen for all recommended alterations; moreover, although multiplex polymerase chain reaction (PCR) tests can detect multiple point mutations (including mutations in EGFR and BRAF), PCR tests must be coupled with fluorescence in situ hybridization (FISH) to detect ROS1 and ALK rearrangements.3 Hence, patients receiving no biomarker testing or only IHC testing from August 2018 through December 24, 2025, would not have been tested for EGFR, ROS1, or BRAF alterations; along with patients receiving no IHC testing, they would not have received all testing recommended by NCCN.

Objectives

The primary objective of this study was to examine how real-world biomarker testing patterns (defined as the proportions of patients with varying levels of biomarker testing, ranging from no testing to more comprehensive testing) relate to first-line mNSCLC treatment selection. The secondary objectives were to identify overall biomarker testing patterns within 90 days of mNSCLC diagnosis and to assess sociodemographic and clinical characteristics by testing pattern.

Methods

The Healthcare (formerly Healthcore) Integrated Research Database (HIRD), a proprietary database curated and maintained by Carelon Research, was used. The HIRD contains information for more than 88 million patients who have been enrolled in commercial and Medicare health plans offered or managed by Anthem (now Elevance/Carelon). The HIRD population is representative of the US Census population in terms of sex, age, and geographic region of residence; representativeness for race/ethnicity is more limited.11 Additional information about the HIRD—including data contents, quality, and provenance—has been previously published. It includes data from health plans in 33 states in the US, with individual members located throughout all 50 states.12 All patients represented in the HIRD were insured and had access to genetic testing during the study period.

Selection Criteria

Patients with at least 2 medical claims for a lung cancer diagnosis (International Classification of Diseases, Tenth Revision, Clinical Modification [ICD-10-CM] codes beginning C34) at least 30 days apart from January 1, 2019, to July 31, 2022 (the patient identification period) were identified. To be included in the study, patients had at least 1 medical claim for metastatic disease (ICD-10-CM codes beginning with C77, C78, C79, or C80) within 60 days after the initial lung cancer diagnosis. The earlier of the lung cancer diagnosis or the metastatic disease diagnosis date was set as the index date.

Further inclusion criteria included having continuous medical and pharmacy health plan enrollment at least 6 months before and at least 6 months after the index date (unless a patient died during that interval) and being 18 years or older on the index date.

Exclusion criteria included having 2 or more claims with 3-digit same diagnosis codes for other primary cancers on distinct dates during the 6 months before the index date and having a diagnosis of lung cancer or metastasis during this baseline period. The latter criterion aimed to maximize the likelihood that the study population represented patients with newly diagnosed mNSCLC.

An updated case-finding algorithm designed by Turner et al13 was applied to patients meeting these criteria; cases not validated to be NSCLC by this method were omitted.

Test Types, Testing Categories, and Baseline Demographics

The following test types were defined: an IHC test (representing an unspecified biomarker test but excluding EGFR, ROS1, and BRAF alterations), a test of a single gene or fewer than 5 genes (< 5GT), and a test of at least 5 genes (≥ 5GT). CPT codes corresponding to these test types (Figure S1) were identified by prior literature and clinical expert review. Codes for single-gene tests specified target genes. Not all codes for multigene tests specified target genes.

Investigators assessed the biomarker testing combinations during the 90-day postindex period and grouped patients into 4 distinct cohorts: (1) no biomarker testing, (2) IHC only, (3) <5GT plus IHC, and (4) ≥5GT plus IHC.

Using these categories, the demographics of included patients were assessed.

Outcomes

Testing and First-Line Treatment

The first claim for NSCLC treatment identified after the index date was defined as the first treatment. The first-line therapy or regimen prescribed or administered within 30 days of the first treatment was categorized as: targeted therapy (including monotherapy or combination therapy), immunotherapy (IO) only, chemotherapy only, IO plus chemotherapy, or no evidence of therapy.

Percentages of patients with claims for each treatment category were assessed for each testing cohort. Multinomial logistic regression analyses were performed to determine by testing cohort the odds of receiving a given therapy.

Testing and Social Determinants of Health

Patients were classified by the 4 biomarker testing cohorts. Baseline demographic and clinical characteristics were also evaluated, in addition to social determinants of health (SDOH). The SDOH measure incorporates individual-level race and ethnicity information derived from enrollment data, self-attestations, electronic health record (EHR) data, and algorithm-derived imputations (using name and geography) obtained from the HIRD; urbanicity data from the National Center for Health Statistics (NCHS); and socioeconomic status (SES) index based on 7 factors describing a patient’s community at the census block group level (ie, unemployment rate, poverty rate, median household income, median home value, proportion not having a high school degree, proportion with a college degree, proportion of households that average ≥ 1 person per room) drawn from the 2019 American Community Survey (ACS) via 9-digit zip code linkage. The SES index score was reported in quartiles, with a 4 indicating a patient is in the top 25% of the SES index score and a 1 indicating a patient is in the bottom 25% of the SES index score.

Treatment and Sociodemographic Factors

Multinomial logistic regression analyses were also performed to explore the association of sociodemographic characteristics with the odds of receiving specific therapies.

Significance was defined as a P value of less than .05.

Results

Figure 1 illustrates the number of eligible patients at each selection point.13 Briefly, among 40,322 patients with at least 2 medical claims for a lung cancer diagnosis 30 days apart during the patient identification period, 5611 met all selection criteria.

Patients had a mean (SD) age of 64.5 (9.95) years, were evenly divided between male (49.8%) and female (50.2%), mostly carried commercial medical insurance (67.1%), and resided in the following regions of the United States: Northeast (15%), Midwest (34.6%), South (32.3%), and West (16.8%) (Table 2).

During the 90-day postindex period, few patients (7.8%) had no evidence of biomarker testing. Most patients (54.0%) had IHC tests only, 13.2% had < 5GT plus IHC, and 25.0% had ≥ 5GT plus IHC.

Biomarker Testing: Clinical and Demographic Patterns

Patients’ clinical characteristics on the index date are summarized by biomarker testing cohort in Table 3.14 The rates of chronic pulmonary disease for the groups with no biomarker testing, IHC only, < 5GT plus IHC, and ≥ 5GT plus IHC were 30.1%, 32.1%, 23.5%, and 25.4%, respectively. Rates of atherosclerotic cardiovascular disease (ASCVD) were 27.1%, 27%, 23%, and 23.8%, respectively, and for obesity were 15%, 15.2%, 13.2%, and 13.6%.

Biomarker testing trends by SDOH characteristics are summarized in Figure 2. From the overall population, 5117 patients (91.2%) lived in areas with ACS SES index data.

Descriptively, biomarker testing patterns were broadly similar across race/ethnicity, SES, and urbanicity. Within each studied population, IHC-only testing was most common, ≥5GT plus IHC testing occurred in approximately one quarter of patients, <5GT plus IHC accounted for about 12% to 15% of testing (≈11%–17% by race/ethnicity), and no biomarker testing was uncommon (~5%–10%) (no hypothesis testing performed; denominators vary by stratum). Among patients with race/ethnicity recorded (n=4524), ≥5GT plus IHC testing occurred in 25.4% of White patients, 19.7% of Black patients, 29.9% of Hispanic/Latino patients, 30.4% of Asian patients, and 26.9% of patients identified as other race. By residential location (n=5162), <5GT plus IHC testing occurred in 25.9% of patients in urban areas, 24.5% of those in suburban areas, and 22.4% of patients in rural areas. These differences represent descriptive trends only.

Treatment Outcomes and Associations

Percentages of patients with claims for each treatment category by testing group are summarized in Figure 3. Overall, most patients received either chemotherapy only (37%) or IO plus chemotherapy combination therapies (37%). Among those with no biomarker test (n = 439) or IHC testing only (n = 3028), chemotherapy only was the most common treatment (42% in both groups), followed by IO plus chemotherapy combinations (32% and 37%, respectively) and targeted therapies (12% and 11%). Among 2728 patients initiating IO only, 1624 (59.5%) had no evidence of EGFR biomarker testing (among other biomarkers not included in IHC diagnostics).

Rates of chemotherapy-only treatment were lower, and rates of targeted therapy were higher, among patients who received more comprehensive biomarker testing. In the groups receiving < 5GT plus IHC (n=742) and ≥ 5GT plus IHC (n = 1402), respective rates of chemotherapy only were 33% and 29% and of targeted therapies were 18% for both.

Multivariate Associations: Testing and Treatment

Relative to IHC-only testing, the odds of receiving each therapy by biomarker testing cohort are summarized in Figure 4. Compared with patients who received IHC only, patients with ≥ 5GT plus IHC had 52% higher odds of receiving IO plus chemotherapy (vs chemotherapy only) (95% CI, 29%-78%; P < .001). Patients with < 5GT only or ≥ 5GT plus IHC had, respectively, 102% (95% CI, 55%-162%) and 97% (95% CI, 56%-147%) higher odds of receiving IO only (vs chemotherapy only) (P < .001 for both). Finally, patients with < 5GT only or ≥ 5GT plus IHC had, respectively, 66% (95% CI, 26%-120%) and 166% (95% CI, 112%-235%) higher odds of receiving targeted therapy (vs chemotherapy only) (P < .001 for both).

Multivariate Associations: Sociodemographic Factors and Treatment

The odds of receiving a given therapy by sex, age, insurance type, SES level, and other factors are summarized in Table 4.14 Patients residing in the highest socioeconomic neighborhoods had 67% (95% CI, 25%-124%; P < .001) higher odds of receiving targeted therapy (vs chemotherapy only) than did those residing in the lowest socioeconomic neighborhoods, highlighting treatment disparities by SES, despite all patients having health insurance. Non-White patients were 52% (95% CI, 24%-87%, P < .001) more likely than White patients to receive targeted therapy rather than chemotherapy only. Compared with patients having Medicare Advantage plans, commercially insured members had 113% (95% CI, 58%-187%, P < .001) higher odds of receiving targeted therapy vs chemotherapy only. Compared to patients in the Northeast, those residing in the West had 108% (95% CI, 52%-184%, P < .001) higher odds of receiving targeted therapy rather than chemotherapy only, indicating some regional practice variation. Finally, compared to those with no indication of smoking, current or former smokers had lower odds of receiving IO plus chemotherapy (OR, 0.81 [95% CI, 0.71-0.93]), IO only (OR, 0.64 [95% CI, 0.53-0.78]), or targeted therapies (OR, 0.26 [95% CI, 0.2-0.32]) vs chemotherapy alone (P < .001 for all).

Discussion

In this study, despite having insurance, 61.8% of patients with mNSCLC did not receive biomarker testing aligning with NCCN guidance for nonsquamous NSCLC within 90 days of initial diagnosis.3,4 This included 7.8% of patients who received no biomarker testing and 54.0% who received IHC testing only; EGFR, ROS1, or BRAF alterations would not have been detected in these patients.3,4 In a retrospective analysis of tissue samples from 9450 patients with NSCLC that were received by a US-based reference laboratory and tested for PD-L1 and several genomic biomarkers, 1785 patients (18.9%) tested positive for EGFR, ROS1, or BRAF alterations.15 Given this prevalence and previously observed proportions of patients with NSCLC with nonsquamous disease,2 as many as 8.2% of patients in our study may have had actionable biomarkers that were not targeted due to inadequate testing. Additionally, 59.5% of patients initiating IO only had no evidence of EGFR biomarker testing. Previously, Lisberg et al reported that patients with an EGFR mutation and PD-L1 expression of at least 1% who initiated IO only had an objective response rate of 0%,16 underscoring the lack of efficacy of IO therapy in patients with EGFR-mutated disease and reinforcing the clinical importance of biomarker-informed treatment decisions.

Role of Clinical and Demographic Factors in Biomarker Testing

This study’s findings suggest that clinical and demographic factors may have contributed to biomarker testing disparities. Higher rates of chronic pulmonary disease, ASCVD, and obesity were seen in the groups with low or no biomarker testing than in the groups with more comprehensive biomarker testing.

In assessing trends, although biomarker testing cohorts were broadly similar across strata, we observed modest but consistent gradients among patients with more comprehensive gene testing (≥5GT plus IHC). Specifically, there were lower proportions among Black patients and those in rural/suburban areas, and higher proportions in the highest SES quartile and in urban settings. Although not tested for statistical significance, these descriptive differences suggest potential inequities in access to or uptake of comprehensive testing. Further investigation is warranted to target quality-improvement efforts, even in an insured population.

Treatment Patterns

More comprehensive biomarker testing was also associated with use of targeted therapy. Compared with patients who received IHC testing only, patients who received more comprehensive biomarker testing (≥ 5GT plus IHC) were significantly more likely to receive IO plus chemotherapy, IO, or targeted therapy rather than chemotherapy alone.

The study’s findings suggest that sociodemographic factors may have contributed to treatment disparities. Patients residing in the highest socioeconomic neighborhoods, having commercial insurance coverage, or living in the West had greater odds of receiving targeted therapy (rather than chemotherapy alone) than did patients residing in the lowest socioeconomic neighborhoods, having Medicare coverage, or living in the Northeast, respectively. Although significantly higher odds were reported for non-Whites vs Whites in receiving targeted therapy, race/ethnic heterogeneity in receipt of first-line treatment warrants further investigation, given the small sample size in some of the non-White groups in this study.

Clinical Implications of Biomarker Testing Gaps

For patients with mNSCLC, such as those observed in this study, biomarker testing gaps have been associated with negative treatment outcomes. Results of an EHR-based study of 21,572 US patients with nonsquamous advanced NSCLC or mNSCLC demonstrated that patients who never underwent biomarker testing had a 30% higher adjusted risk of death compared to those who had ever been tested (HR, 1.30; 95% CI, 1.24-1.37). Similarly, individuals who did not receive biomarker testing before or when starting first-line therapy faced a 12% increased adjusted risk of death relative to those who did (HR, 1.12; 95% CI, 1.08-1.16). Among patients with actionable biomarkers, those who did not receive first-line treatment that aligned with clinical guidelines experienced a 25% greater adjusted risk of death compared to those who did (HR, 1.25; 95% CI, 1.13-1.39).17

Economic Considerations and Policy Recommendations

Insufficient biomarker testing in mNSCLC is linked to higher health care costs. A 2022 cost-effectiveness analysis using a Markov model compared liquid biopsy plus tissue testing with tissue testing alone in patients with treatment-naive, incurable, stage IIIB or stage IV nonsquamous NSCLC who had a smoking history of up to 10 pack-years. Investigators used data from the VALUE trial (NCT03576937), which included 146 patients being treated at Canadian cancer centers, to estimate the impact on the Canadian health care system over 2 years.18

Actionable biomarker mutations were identified by liquid biopsy plus tissue testing in 68.5% of patients and in 52.7% of patients who only received tissue testing, yielding $3065 (95% CI, $2195-$3945) (2022 Canadian dollars [CAD$]) in average incremental cost savings per patient and a quality-adjusted life-year gain of 0.02 (95% CI, 0.01-0.02). The cost savings associated with liquid biopsy plus tissue testing were primarily driven by improved identification of actionable genomic alterations and targeted therapy utilization, and were most pronounced as the cost of chemotherapy rose in modeled scenarios.18

In NSCLC, payer coverage of liquid biopsy testing is recommended with tissue testing to enhance the speed and breadth of biomarker profiling. Challenges persist in NSCLC regarding tissue adequacy, quality, and turnaround time for test results. One key barrier to using tissue to obtain biomarker testing results arises when minimally invasive sampling methods yield insufficient material for comprehensive biomarker and histologic analyses.7 NGS testing can overcome constraints of needing several or larger tissue samples for single-gene tests. Additionally, liquid biopsy is less invasive than tissue testing, is potentially more acceptable to the patient, does not incur the cost and complication risks associated with biopsy, and detects malignant tissue throughout the body by assessing DNA shed into plasma.19

Most payers favor providers’ increased alignment with guideline recommendations for biomarker testing in NSCLC. Education of pulmonologists and other providers, along with standardized biomarker testing practices, may increase biomarker testing rates.7 Multidisciplinary teams are needed to identify and treat mNSCLC early, including the use of comprehensive biomarker testing aligned to clinical guidelines.20

Limitations

This study was subject to several limitations that have been seen elsewhere in the study of mNSCLC testing and treatment.21 Among these was the use of claims data to approximate patient population, testing, and testing rates. Use of ICD-10-CM codes beginning with C77 may have inadvertently included patients with stage II and stage III NSCLC who had regional lymph node metastasis (eg, ipsilateral hilar, mediastinal) rather than stage IV disease (mNSCLC). Moreover, a study of data from 2013 to 2021 suggests that the coding of genomic testing may be incomplete or inaccurate (mismatch range, 23%-54%) when compared to the EHR (actual testing) in patients with advanced NSCLC.22 The disparities could be due to the variability of provider billing practices and/or cost-sharing differences. Furthermore, claims data are primarily collected for billing and reimbursement purposes and may be subject to coding errors and omissions. Whether IHC tests were used to distinguish tumor type (eg, squamous cell carcinoma vs large cell carcinoma) or to identify ALK mutations or PD-L1 expression was not assessed. Additionally, claims data did not provide information on genes tested; the study authors assumed that providers would have selected NCCN-recommended biomarkers. Finally, identification of patients with NSCLC relied on a treatment-based algorithm, which may have led to some misclassification.

Conclusion

The results of this study highlight persistent gaps in biomarker testing for mNSCLC, with most patients not receiving guideline-concordant biomarker testing within 90 days of diagnosis. These gaps are associated with disparities in treatment selection and may lead to missed opportunities for targeted therapy, especially in populations with lower SES or limited health care access. Expanding access to comprehensive biomarker testing—through tissue and liquid biopsy—with payer policies that enable unencumbered patient access to comprehensive biomarker testing may improve outcomes, reduce costs, and support more equitable care across diverse patient populations.

Authorship Affiliation: Value Strategy & Evidence, US Market Access, AstraZeneca (SB and AS), Wilmington, DE; HEOR, Carelon Research (KD), Wilmington, DE; Oncology Outcomes Research, AstraZeneca (PSK), Gaithersburg, MD; Department of Radiation Medicine, Oregon Health & Science University (KCO), Portland, OR.

Source of Funding: This supplement was supported by AstraZeneca.

Author Disclosures: Dr Boykin, Dr Karia, and Dr Stanford report stock ownership in AstraZeneca and are employed by AstraZeneca.

Dr Desai and Dr Ohaegbulam have no relevant commercial financial relationships or affiliations to disclose.

Authorship Information: Concept and design (SB, PSK, AS); acquisition of data (KD); analysis and interpretation of data (SB, KD, PSK, KCO, AS); drafting of the manuscript (SB, PSK, KCO, AS); critical revision of the manuscript for important intellectual content (KD, PSK, KCO, AS); provision of study materials or patients (SB); obtaining funding (PSK, AS); administrative, technical, or logistic support (SB, PSK, AS); supervision (SB, PSK, AS).

Acknowledgments: AstraZeneca was given the opportunity to review the content for medical accuracy. Under the direction of the authors, medical writing support and editorial assistance were provided by Erin Garrow, PhD, of MJH Life Sciences®.

Address Correspondence to: Amy Stanford, PharmD. Email: amy.stanford@astrazeneca.com

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