Patient Adherence to Screening for Lung Cancer in the US

Key Points Question What is the of rate of adherence to lung cancer screening among high-risk individuals outside randomized clinical trials, and how does adherence differ across patient subgroups? Findings In this systematic review and meta-analysis of 15 cohort studies with a total of 16 863 individuals, the pooled lung cancer screening adherence rate was 55%. Current smokers, patients of races other than White, those younger than 65 years, and those with less than a college education had lower adherence to screening. Meaning These findings suggest that adherence to lung cancer screening is much lower than reported in large randomized clinical trials and is lower for current smokers and smokers from minority populations.


Introduction
Screening high-risk current and former smokers for lung cancer with low-dose computed tomography (LDCT) reduces deaths from lung cancer. [1][2][3] The US Preventive Services Task Force recommends annual screening with LDCT for individuals with a smoking history of at least 30 packyears who currently smoke or have quit within the past 15 years, are between 55 and 80 years of age, and meet other eligibility criteria. 4 Screening should continue annually until the person is no longer eligible. 5 In the National Lung Screening Trial (NLST) and the Dutch-Belgian lung cancer screening (LCS) trial (the Nederlands-Leuvens Longkanker Screenings Onderzoek [NELSON] trial), adherence to subsequent screening was high. The NELSON trial's adherence rates exceeded 90% during 4 screenings (final screening scan occurred 5.5 years after enrollment), 3 and the NLST reported adherence rates greater than 95% during 3 annual screenings. 2 Monitoring adherence rates for LCS outside clinical trials is important in understanding how LCS is being implemented in the US. This systematic review and meta-analysis examines LCS adherences rates outside the context of randomized clinical trials, differences in adherence rates among subgroups of patients, and diagnostic testing rates after screening.

Protocol and Registration
The protocol for this systematic review and meta-analysis is registered with PROSPERO. We followed the standards of the Cochrane Handbook for Systematic Reviews of Interventions 6 and report our results according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. 7

Eligibility Criteria
We included studies that reported LCS adherence rates in the US and/or determinants of LCS adherence. We considered prospective or retrospective studies that screened adult patients at any risk level of developing cancer who opted to initiate LCS and continued to undergo additional screening after the first LDCT. Because in some instances screening was not performed annually, from here on we use the term periodic to indicate a subsequent screening. We also considered any length of follow-up and setting. We excluded randomized clinical trials, studies without enough information to perform meta-analysis (ie, did not provide a denominator for adherence rates or determinants of adherence without the magnitude of association), and studies that reported on imaging techniques other than LDCT. For studies that reported the results in different years of the same cohort, we included the most updated report. ensure that only studies published after the NLST 2 results were captured. The new citations were added for review before the analysis.

Study Selection and Data Collection
Two members of the research team independently screened citations (K.G.M. and N.J.C.). Titles and abstracts were first screened to eliminate any citations not relevant to the study, and then the full text of the relevant citations were further screened for eligibility. Disagreements between reviewers were resolved by consensus or by a third person (M.A.L.-O.). Two members of the study team independently extracted data from the studies (K.G.M and N.J.C.), and any discrepancies were resolved by discussion. The data were also cross-checked for any errors by another author (M.A.L.-O.).

Data Items
When available, we captured the following: (1) general study information, such as title, authors, follow-up, year, funding agency, study design, setting (ie, academic or community), definition of adherence, geography (ie, rural or urban), hospital type (ie, safety net or federally qualified health center), screening type (ie, integrated health center or need to refer patients for diagnostic testing), use of electronic health record, and number of patients analyzed; (2) characteristics of participants, such as age, sex, eligibility criteria, socioeconomic status, smoking status, and race/ethnicity; and (3) outcome variables, such as adherence rates of LCS, characteristics associated with adherence, and completion rates of recommended diagnostic testing after screening. Inclusion of data items was determined by possible associations between these factors and periodic LCS adherence. For instance, some federally qualified health centers serve individuals regardless of insurance status or ability to pay 8,9 ; these factors may be associated with subsequent screening behavior.

Risk of Bias in Individual Studies
Two authors (K.G.M. and N.J.C.) independently appraised the included studies for potential bias.
Disagreements were resolved by consensus or by a third person (M.A.L.-O. or R.J.V.). We used the Newcastle-Ottawa Scale to assess the quality of nonrandomized studies in meta-analyses. 10 The scale evaluates 3 domains of bias: selection, comparability, and measurement of outcomes. Each domain includes items that are scored with a star system. 10 The maximum scores were 4 stars for the selection domain, 2 for the comparability domain, and 3 for the outcome (or exposure for casecontrol studies) domain. A total maximum score of 9 can be achieved, and a higher score indicates a lower risk of bias.

Summary Measures
We analyzed data as reported in the studies. We determined adherence rates using the number of patients undergoing screening in each trial per time point as numerators. For the denominator, we considered all patients followed up for each time point (not everyone who receives a baseline scan is eligible for subsequent scans; for example, people may move to diagnostic testing or treatment or die). To quantify the association between adherence and variables of interest, we pooled the reported odds ratios (ORs) and 95% CIs. To determined diagnostic testing rates after screening, we used the number of patients undergoing any test or procedure with the purpose of diagnosis after an abnormal screening result as the numerator and all patients with abnormal results from LDCT as the denominator.

Statistical Analysis
We used a random-effects model to calculate a combined estimate of LCS adherence rate and a 95% CI. For the pooled adherence rate, we used the Freeman-Tukey double arcsine transformation to stabilize variances and conducted a meta-analysis using inverse variance weights. Resulting estimates and 95% CI boundaries were back transformed into proportions. We used the generic inverse-variance method with a random-effects model when estimates of log ORs and SEs had been obtained from the included studies. When needed, we applied 1 divided by the OR for consistency of the referent group to pool estimates. For studies in which the number of events was provided, we calculated ORs and then converted them into log ORs and SEs. No attempts were made to contact authors of studies with missing data. When data were unclear or not provided for a given outcome, the study was not included in the analysis for the outcome, assuming that the data were missing at random. 11 Heterogeneity of the data was formally tested by using the χ 2 test, with P < .10 indicating significant heterogeneity; the I 2 statistic results were also assessed (a value >50% may indicate substantial heterogeneity) and forest plots reviewed. All analyses were 2-sided and performed using Stata statistical software version 15 (StataCorp) and RevMan version 5.3 (The Cochrane Collaboration).
We used subgroup analysis to explore the length of follow-up and eligibility criteria as potential factors associated with heterogeneity. A metaregression was performed to evaluate the association between enrollment year and adherence rates. We planned to perform a funnel plot and a regression asymmetry test to assess small-study bias for the meta-analysis to identify the patient characteristics associated with adherence. Because of the small number of studies, a funnel plot and a regression asymmetry test to assess small-study bias for the meta-analysis could not be performed.

Study Selection and Characteristics
The flow diagram of study disposition is shown in Figure 1.  The mean age of participants ranged from 50 to 75 years, the percentage of men ranged from 42% to 65%, the percentage of current smokers ranged from 42% to 76%, and the mean pack-year smoking history ranged from 32 to 53 pack-years ( Table 2). 16

JAMA Network Open | Oncology
Patient Adherence to Screening for Lung Cancer in the US follow-up time that was long enough to adequately assess periodic adherence beyond 1 year. All of the studies reported loss-to-follow-up rates greater than 20% (eTable 2 in the Supplement).
Screening adherence rates across studies ranged from 12% (95% CI, 8%-20%) to 91% (95% CI, 88%-93% eFigure 2 in the Supplement shows the results of studies that reported adherence rates within a period of 10 to 14 months 22 and 11 to 30 months 27 from baseline scan. One of these studies 27 also reported adherence rates at any time point for those people with at least 1 additional screening and people with at least 2 additional screenings.

Additional Analyses
Subgroup analysis was conducted to explore differences on the adherence rates per eligibility criteria used (eFigure 3 in the Supplement). We observed a difference only in a study 28 that included patients

Discussion
This systematic review and meta-analysis examined high-risk patients' adherence to periodic LCS reported in cohort studies. It provides an indication of how successfully LCS is being implemented in the US since the release of the NLST's main findings and subsequent recommendations endorsing screening with LDCT. We found that periodic screening rates for lung cancer were much lower-55% in our overall pooled analysis-than the rates reported in clinical trials. In addition, the rates varied widely, from 12% to 91%, and were higher when longer periods between initial and subsequent screenings were used.
Given the overall low rates of cancer screening adherence within the US population 31-34 and among high-risk individuals, 35,36 it is not surprising that LCS adherence was lower than that seen within the controlled setting of clinical trials. 37  The higher screening uptake and adherence rates for colon and breast cancer compared with lung cancer are the results of these tests being available and recommended for many years, and a great deal of effort has gone into educating patients, 40 working with practitioners, 41 and Lung-RADS is a categorization tool designed to standardize the reporting of screening-detected lung nodules. This figure shows the adherence rates reported per study. The first column represents the studies included in the analysis. The adherence rates were sorted from lowest to highest. The boxes represent the adherence rate reported per study after initial lung cancer screening (second screening regardless of the time point used). The horizontal lines represent 95% CIs. The diamond represents the overall adherence rate (pooled adherence rate) and the width of the diamond the 95% CI. The dotted line indicates where the overall effect estimate (pooled adherence rate) lies. ES indicates effect size. understanding factors that relate to screening behaviors. [42][43][44] In contrast, LDCT for LCS is a relatively nascent field 45 with most intervention efforts still focusing on increasing uptake and acceptability among patients and practitioners 46,47 rather than promoting the importance of annual adherence. Important differences between patient subgroups were found in this review. Current smokers were less likely to adhere to LCS than former smokers. This finding aligns with previous research reporting lower rates of cancer screening among eligible current smokers (compared with never smokers). 48,49 Stigma may be a key barrier for LCS, with patients feeling judged and blamed and therefore delaying early screening. 50 Prior work 51 suggests that lung cancer stigma is a multilayered issue that spans individual and societal levels and includes placing blame on the individual for smoking as well as public attitudes and policies. Furthermore, patients have reported feeling as though some health care professionals do not understand how their smoking was affected by the culture and period in which they have lived. 50 White people were more likely to adhere to periodic LCS than people of other races, a finding consistent with disparities seen by others 49 and for other cancer screenings and diagnostic testing. 52,53 Reasons for this disparity are unclear and may relate to insurance status and access to screening facilities, among other factors. Previous research has also found racial/ethnic disparities in screening, including for breast cancer, 54,55 colorectal cancer, 56,57 and follow-up diagnostic testing after a positive prostate cancer screening test result. 58 Similarly, prior work 52 has found a longer screening interval between prostate-specific antigen testing and prostate cancer diagnosis in Black men compared with White men. This review has implications for future research and updates to current screening recommendations. Extending the recommended interval between lung cancer screenings 59 has the potential to increase screening adherence, reduce false-positive test results, and decrease screening costs. Future research should investigate the optimal screening interval that balances the harmbenefit tradeoffs of LCS. There is also interest in the role of risk-based screening in lung cancer. 60 Because smoking status is an important risk factor for lung cancer, concerns about adherence will be even greater if screening recommendations prioritize identification of high-risk current smokers.
Interventions should be directed toward increasing LCS adherence among several key groups: current smokers, patients of races other that White, and patients with lower levels of education.
Finally, data are needed to determine the adherence with diagnostic testing among patients with abnormal scan results and adherence with curative treatment for those diagnosed with a stage I or II cancer.

Limitations
This review has limitations. We only included studies that were conducted in the US. The follow-up period was shorter than seen in the clinical trials, with most studies 12-17,19,20,22,23,25,27-

Conclusions
In this study, rates of LCS adherence in the US published in the literature varied widely and were lower than seen in the controlled setting of clinical trials. Few studies reported adherence beyond 1 subsequent screening after baseline. Although there is concern that screening rates nationally are low, 61 equally important is the need for interventions to improve adherence to screening for current smokers and smokers from minority populations to fully realize the benefits of early detection of lung cancer.