Adherence to Radiology Recommendations in a Clinical CT Lung Screening Program

Inadequate Uptake of USPSTF-Recommended Low Dose CT Lung Cancer Screening

In 2023, Journal of Primary Care and Community Health published the results of 4 outstanding studies in which investigators aimed to explore and improve clinician and eligible individuals' knowledge of the rationale for lung cancer screening (LCS). Their results highlighted the underutilization of LCS, particularly for certain high risk populations, and the continued disparities in screening seen between groups of eligible individuals. Here, key findings from those 2023 Journal of Primary Care and Community Health reports, along with salient findings of other recent LCS reports, are discussed. The bases for the United States Preventive Task Force (USPSTF) LCS recommendations, barriers primary care providers face, the perspective of eligible individuals, importance of shared decision-making (SDM) and disparities between groups in LCS are reviewed along with potential strategies to ensure that more eligible individuals are offered LCS.

Lung cancer screening adherence among people living with and without HIV: An analysis of an integrated health system in Florida, United States (2012-2021)

Although lung cancer is a leading cause of death among people living with HIV (PLWH), limited research exists characterizing real-world lung cancer screening adherence among PLWH. Our objective was to compare low-dose computed tomography (LDCT) adherence among PLWH to those without HIV treated at one integrated health system. Using the University of Florida's Health Integrated Data Repository (01/01/2012-10/31/2021), we identified PLWH with at least one LDCT procedure, using Current Procedural Terminology codes(S8032/G0297/71271). Lung cancer screening adherence was defined as a second LDCT based on the Lung Imaging Reporting and Data System (Lung-RADS®). Lung-RADS categories were extracted from radiology reports using a natural language processing system. PLWH were matched with 4 randomly selected HIV-negative patients based on (+/- 1 year) age, Lung-RADS category, and calendar year. Seventy-three PLWH and 292 matched HIV-negative adults with at least one LDCT were identified. PLWH were more likely to be male (66% vs.52%,p < 0.04), non-Hispanic Black (53% vs.23%,p < 0.001), and live in an area of high poverty (45% vs.31%,p < 0.001). PLWH were more likely to be diagnosed with lung cancer after first LDCT (8% vs.0%,p < 0.001). Seventeen percent of HIV-negative and 12% of PLWH were adherent to LDCT screenings. Only 25% of PLWH diagnosed with category 4A were adherent compared to 44% of HIV-negative. On multivariable analyses, those with older age (66-80 vs.50-64 years) and with either Medicaid, charity-based, or other government insurance (vs. Medicare) were less likely to be adherent to LDCT screenings. PLWH may have poorer adherence to LDCT compared to their HIV-negative counterparts.

Timely adherence to follow-up after high-risk lung cancer screenings

OBJECTIVE

To achieve the lung cancer screening (LCS) mortality benefit in clinical trials, timely, real-world follow-up of abnormal test results is necessary. Presently, annual LCS rates are lower than in trials, and adherence to follow-up after suspicious findings has not been well studied. This study examined timely adherence to follow-up recommendations after positive low-dose computed tomography (LDCT) screenings.

METHODS

This retrospective study included individuals from two academic primary care practices in New York City who met United States Preventative Services Task Force LCS eligibility and had a positive LDCT scan between 2013 and 2020. They were recommended for shorter interval follow-up repeat computed tomography (CT), CT biopsy, or positron emission tomography/CT. Adherence was completion of the prescribed imaging by 15 days after the recommended 7-, 30-, and 90-day follow-up and by 30 days after the 180-day recommended follow-up.

RESULTS

Among 106 individuals with a positive LDCT scan, 64 (60%) were adherent to follow-up recommendations. Adherence was 72%, 63%, and 42% for recommended follow-ups of 30, 90, and 180 days, respectively. Being male was a predictor of a lower adherence rate. Among 23 individuals newly diagnosed with lung cancer after a positive LDCT scan, 83% were adherent to follow-up testing and 82% of cancers were Stage 1A or limited stage.

CONCLUSIONS

There was variable adherence to the LCS follow-up recommendations despite positive screening CT, suggesting that even in a well-established screening program there may not be an efficient, systematic approach for follow-up. The delays in repeat testing potentially undermine the benefits of early detection.

A predictive model for lung cancer screening nonadherence in a community setting health-care network

BACKGROUND

Lung cancer screening (LCS) decreases lung cancer mortality. However, its benefit may be limited by nonadherence to screening. Although factors associated with LCS nonadherence have been identified, to the best of our knowledge, no predictive models have been developed to predict LCS nonadherence. The purpose of this study was to develop a predictive model leveraging a machine learning model to predict LCS nonadherence risk.

METHODS

A retrospective cohort of patients who enrolled in our LCS program between 2015 and 2018 was used to develop a model to predict the risk of nonadherence to annual LCS after the baseline examination. Clinical and demographic data were used to fit logistic regression, random forest, and gradient-boosting models that were internally validated on the basis of accuracy and area under the receiver operating curve.

RESULTS

A total of 1875 individuals with baseline LCS were included in the analysis, with 1264 (67.4%) as nonadherent. Nonadherence was defined on the basis of baseline chest computed tomography (CT) findings. Clinical and demographic predictors were used on the basis of availability and statistical significance. The gradient-boosting model had the highest area under the receiver operating curve (0.89, 95% confidence interval = 0.87 to 0.90), with a mean accuracy of 0.82. Referral specialty, insurance type, and baseline Lung CT Screening Reporting & Data System (LungRADS) score were the best predictors of nonadherence to LCS.

CONCLUSIONS

We developed a machine learning model using readily available clinical and demographic data to predict LCS nonadherence with high accuracy and discrimination. After further prospective validation, this model can be used to identify patients for interventions to improve LCS adherence and decrease lung cancer burden.

Patient Experience of Managing Adherence to Repeat Lung Cancer Screening

Lung cancer screening (LCS) is a process involving multiple low-dose computed tomography (LDCT) scans over multiple years. While adherence to recommended follow-up is critical in reducing lung cancer mortality, little is known about factors influencing adherence following the initial LDCT scan. The purpose of this study was to examine patients' and providers' depictions of continued screening and their understandings of patients' decisions to return for follow-up. Qualitative methodology involves interviews with patients about their understanding of the screening process and perceptions of lung cancer risk, including motivations to adhere to follow-up screening and surveillance. Analysis of interview transcripts followed the general procedures of grounded theory methodology. Patient adherence to LCS was influenced by their understanding of the process of screening, and their expectations for the next steps. Perceptions of lung cancer risk and associated motivation were not static and changed throughout the screening process. Recognizing that patients' motivations may be dynamic over the course of screening and surveillance will assist providers in helping patients make decisions regarding continued engagement with LCS.

Racial Disparities in Adherence to Annual Lung Cancer Screening and Recommended Follow-Up Care: A Multicenter Cohort Study

Rationale: Black patients receive recommended lung cancer screening (LCS) follow-up care less frequently than White patients, but it is unknown if this racial disparity persists across both decentralized and centralized LCS programs. Objectives: To determine adherence to American College of Radiology Lung Imaging Reporting and Data System (Lung-RADS) recommendations among individuals undergoing LCS at either decentralized or centralized programs and to evaluate the association of race with LCS adherence. Methods: We performed a multicenter retrospective cohort study of patients receiving LCS at five heterogeneous U.S. healthcare systems. We calculated adherence to annual LCS among patients with a negative baseline screen (Lung-RADS 1 or 2) and recommended follow-up care among those with a positive baseline screen (Lung-RADS 3, 4A, 4B, or 4X) stratified by type of LCS program and evaluated the association between race and adherence using multivariable modified Poisson regression. Results: Of the 6,134 total individuals receiving LCS, 5,142 (83.8%) had negative baseline screens, and 992 (16.2%) had positive baseline screens. Adherence to both annual LCS (34.8% vs. 76.1%; P < 0.001) and recommended follow-up care (63.9% vs. 74.6%; P < 0.001) was lower at decentralized compared with centralized programs. Among individuals with negative baseline screens, a racial disparity in adherence was observed only at decentralized screening programs (interaction term, P < 0.001). At decentralized programs, Black race was associated with 27% reduced adherence to annual LCS (adjusted relative risk [aRR], 0.73; 95% confidence interval [CI], 0.63-0.84), whereas at centralized programs, no effect by race was observed (aRR, 0.98; 95% CI, 0.91-1.05). In contrast, among those with positive baseline screens, there was no significant difference by race for adherence to recommended follow-up care by type of LCS program (decentralized aRR, 0.95; 95% CI, 0.81-1.11; centralized aRR, 0.81; 95% CI, 0.71-0.93; interaction term, P = 0.176). Conclusions: In this large multicenter study of individuals screened for lung cancer, adherence to both annual LCS and recommended follow-up care was greater at centralized screening programs. Black patients were less likely to receive annual LCS than White patients at decentralized compared with centralized LCS programs. Our results highlight the need for further study of healthcare system-level mechanisms to optimize longitudinal LCS care.

Closing the loop: automatically identifying abnormal imaging results in scanned documents

OBJECTIVES

Scanned documents (SDs), while common in electronic health records and potentially rich in clinically relevant information, rarely fit well with clinician workflow. Here, we identify scanned imaging reports requiring follow-up with high recall and practically useful precision.

MATERIALS AND METHODS

We focused on identifying imaging findings for 3 common causes of malpractice claims: (1) potentially malignant breast (mammography) and (2) lung (chest computed tomography [CT]) lesions and (3) long-bone fracture (X-ray) reports. We train our ClinicalBERT-based pipeline on existing typed/dictated reports classified manually or using ICD-10 codes, evaluate using a test set of manually classified SDs, and compare against string-matching (baseline approach).

RESULTS

A total of 393 mammograms, 305 chest CT, and 683 bone X-ray reports were manually reviewed. The string-matching approach had an F1 of 0.667. For mammograms, chest CTs, and bone X-rays, respectively: models trained on manually classified training data and optimized for F1 reached an F1 of 0.900, 0.905, and 0.817, while separate models optimized for recall achieved a recall of 1.000 with precisions of 0.727, 0.518, and 0.275. Models trained on ICD-10-labelled data and optimized for F1 achieved F1 scores of 0.647, 0.830, and 0.643, while those optimized for recall achieved a recall of 1.0 with precisions of 0.407, 0.683, and 0.358.

DISCUSSION

Our pipeline can identify abnormal reports with potentially useful performance and so decrease the manual effort required to screen for abnormal findings that require follow-up.

CONCLUSION

It is possible to automatically identify clinically significant abnormalities in SDs with high recall and practically useful precision in a generalizable and minimally laborious way.

Association of Rurality With Annual Repeat Lung Cancer Screening in the Veterans Health Administration

PURPOSE

Lung cancer causes the largest number of cancer-related deaths in the United States. Lung cancer incidence rates, mortality rates, and rates of advanced stage disease are higher among those who live in rural areas. Known disparities in lung cancer outcomes between rural and nonrural populations may be in part because of barriers faced by rural populations. The authors tested the hypothesis that among Veterans who receive initial lung cancer screening, rural Veterans would be less likely to complete annual repeat screening than nonrural Veterans.

METHODS

A retrospective cohort study was conducted of 10 Veterans Affairs medical centers from 2015 to 2019. Rural and nonrural Veterans undergoing lung cancer screening were identified. Rural status was defined using the rural-urban commuting area codes. The primary outcome was annual repeat lung cancer screening in the 9- to 15-month window (primary analysis) and 31-day to 18-month window (sensitivity analysis) after the first documented lung cancer screening. To examine rurality as a predictor of annual repeat lung cancer screening, multivariable logistic regression models were used.

RESULTS

In the final analytic sample of 11,402 Veterans, annual repeat lung cancer screening occurred in 27.7% of rural Veterans (641 of 2,316) and 31.8% of nonrural Veterans (2,891 of 9,086) (adjusted odds ratio: 0.86; 95% confidence interval: 0.73-1.03). Similar results were seen in the sensitivity analysis, with 41.6% of rural Veterans (963 of 2,316) versus 45.2% of nonrural Veterans (4,110 of 9,086) (adjusted odds ratio: 0.88; 95% confidence interval: 0.73-1.04) having annual repeat screening in the expanded 31-day to 18-month window.

CONCLUSIONS

Among a national cohort of Veterans, rural residence was associated with numerically lower odds of annual repeat lung cancer screening than nonrural residence. Continued, intentional outreach efforts to increase annual repeat lung cancer screening among rural Veterans may offer an opportunity to decrease deaths from lung cancer.

Factors Associated With Lung Cancer Screening Adherence Among Patients With Negative Baseline CT Results in a Community Health Care Setting

PURPOSE

Lung cancer screening (LCS) decreases lung cancer mortality; however, that reduction depends upon screening adherence. The purpose of this study was to determine factors associated with adherence rate for LCS among patients with negative baseline CT results in a multi-integrated health care network.

METHODS

A retrospective analysis was conducted among patients with negative baseline CT results in a multi-integrated health care network LCS program between January 2015 and January 2020. The two outcomes were adherence for the first and second subsequent LCS studies. Negative baseline result was defined as a Lung CT Screening Reporting and Data System score 0, 1, or 2. Adherence was defined as undergoing a follow-up study within 11 to 15 months of a prior scan. Multivariable logistic regression was used to determine significant predictors of adherence, adjusting for patient demographics, median household income (on the basis of geocoding ZIP codes from the US Census Bureau), smoking history, screening sites, and provider specialty.

RESULTS

A total of 30.7% (512 of 1,668) and 16.3% (270 of 1,660) of patients were adherent for the first two annual subsequent screens, respectively. First-year adherence was higher among former smokers and varied by site and provider specialty. Second-year adherence was higher among former smokers and varied by site, provider specialty, and pack-years smoked.

CONCLUSIONS

Adherence to LCS in a multihospital integrated health care network was poor and even lower at year 2. The identified factors associated with adherence may serve as targets to increase LCS adherence and decrease lung cancer mortality.

Use of Diagnostic CT and Patient Retention in a Lung Cancer Screening Program

PURPOSE

The aims of this study were to assess the rate of subsequent diagnostic chest CT examinations in a lung cancer screening (LCS) program and examine the effect on retention of patients in the program.

METHODS

Patients who underwent LCS CT between June 2011 and August 2018 were included. The occurrence of patients' being subsequently imaged with diagnostic CT versus LCS CT and the effect this had on patients' returning for LCS CT (patient retention) were evaluated. Multivariable logistic regression was used to evaluate variables associated with undergoing diagnostic CT and risk factors associated with loss of patient retention.

RESULTS

Of the 5,912 patients who underwent LCS CT, 2,756 underwent subsequent diagnostic or LCS chest CT. Increasing Lung-RADS® score was more likely to lead to subsequent diagnostic chest CT (P < .0001). A total of 1,240 patients underwent at least three chest CT examinations in the time interval. For the 711 patients whose subsequent CT studies were for LCS, 585 (82%) were retained, whereas of the 529 patients who underwent subsequent diagnostic CT, only 208 (39%) were retained (P < .0001). For the 197 subsequent diagnostic CT examinations performed for pulmonary nodule or screening indications, 81 patients (41%) returned for LCS CT, compared with 498 of 612 patients (81%) who underwent subsequent LCS CT (P < .0001). In multivariable analysis, subsequent diagnostic chest CT and increasing Lung-RADS score were associated with loss of retention.

CONCLUSIONS

A higher Lung-RADS score is a risk factor for subsequent diagnostic chest CT, and this is an independent risk factor for loss from the LCS program.

Patient Identification of Lung Cancer Screening Follow-up Recommendations and the Association with Adherence

RATIONALE

Adherence to follow-up lung cancer screening (LCS) in real-world settings is suboptimal. Patient understanding of screening results and anticipated follow-up may be crucial to adherence.

OBJECTIVE

To determine patient-factors associated with identification of follow-up recommendations as a measure of patient understanding of screening results after LCS , and to determine whether misidentification of follow-up is associated with lower adherence to recommendations.

METHODS

We performed a prospective study of patients in the University of Washington/Seattle Cancer Care Alliance LCS registry who underwent an initial LCS exam between June 2017- September 2019. We mailed potential participants a survey following initial LCS exam, with additional data abstracted from the electronic health record and LCS registry. Participants were asked to identify the timing and next step for their follow-up, with answers corresponding to Lung-RADS recommendations. We examined associations between incorrect identification of recommended follow-up and patient-level characteristics, self-perceived benefit/harm of LCS, LCS knowledge, Lung-RADS score, and patient-reported method of LCS results communication (letter, telephone or in-person). We used multivariable logistic regression to evaluate associations with incorrect identification of recommendations and assessed incorrect identification of recommendations as a potential mechanism for poor adherence in a separate regression model.

RESULTS

One-hundred eighty-eight participants completed the survey (response rate 44%); 47% misidentified their follow-up recommendation. Those with lung-RADS scores ≥3 had higher odds of incorrectly identifying follow-up recommendations compared to those with scores <3, as did those with lower educational attainment. However, there was no significant association between incorrect identification of follow-up and ultimate adherence to follow-up.

CONCLUSION

Understanding of LCS follow-up appears to be poor, especially among those with lower education levels and positive findings. Among survey responders, incorrect identification of follow-up was not associated with poor adherence, suggesting other factors, such as provider interventions, may be driving adherence behavior. These results can inform efforts to target improved patient education regarding follow-up for LCS. Primary sources of funding. American Lung Association and American Thoracic Society.

Patient Adherence to Lung CT Screening Reporting & Data System-Recommended Screening Intervals in the United States: A Systematic Review and Meta-Analysis

Lung cancer screening (LCS) is effective in reducing mortality, particularly when patients adhere to follow-up recommendations standardized by the Lung CT Screening Reporting & Data System (Lung-RADS). Nevertheless, patient adherence to recommended intervals varies, potentially diminishing benefit from screening. We conducted a systematic review and meta-analysis of patient adherence to Lung-RADS-recommended screening intervals. We systematically searched MEDLINE, EMBASE, Web of Science, the Cochrane Central Register of Controlled Trials, and major radiology and oncology conference archives between April 28, 2014, and December 17, 2020. Eligible studies mentioned patient adherence to the recommendations of Lung-RADS. The review protocol was registered with PROSPERO (CRD42020189326). We identified 24 eligible studies for qualitative summary, of which 21 were suitable for meta-analysis. The pooled adherence rate was 57% (95% confidence interval: 46%-69%) for defined adherence (e.g., an annual incidence screen was performed within 15 mo) among 6689 patients and 65% (95% confidence interval: 55%-75%) for anytime adherence among 5085 patients. Large heterogeneity in adherence rates between studies was observed (I² = 99% for defined adherence, I² = 98% for anytime adherence). Heterogeneous adherence rates were associated with Lung-RADS scores, with significantly higher adherence rates among Lung-RADS 3 to 4 than Lung-RADS 1 to 2 (p < 0.05). Patient adherence to Lung-RADS-recommended screening intervals is suboptimal across clinical LCS programs in the United States, especially among patients with results of Lung-RADS categories 1 to 2. To improve adherence rates, future research may focus on implementing tailored interventions after identifying barriers to LCS. We also propose a minimum standardized set of data elements for future pooled analyses of LCS adherence on the basis of our findings.

Adherence to Follow-up Testing Recommendations in US Veterans Screened for Lung Cancer, 2015-2019

IMPORTANCE

Lung cancer screening (LCS) can reduce lung cancer mortality with close follow-up and adherence to management recommendations. Little is known about factors associated with adherence to LCS in real-world practice, with data limited to case series from selected LCS programs.

OBJECTIVE

To analyze adherence to follow-up based on standardized follow-up recommendations in a national cohort and to identify factors associated with delayed or absent follow-up.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study was conducted in Veterans Health Administration (VHA) facilities across the US. Veterans were screened for lung cancer between 2015 to 2019 with sufficient follow-up time to receive recommended evaluation. Patient- and facility-level logistic regression analyses were performed. Data were analyzed from November 26, 2019, to December 16, 2020.

MAIN OUTCOMES AND MEASURES

Receipt of the recommended next step after initial LCS according to Lung CT Screening Reporting & Data System (Lung-RADS) category, as captured in VHA or Medicare claims.

RESULTS

Of 28 294 veterans (26 835 [94.8%] men; 21 969 individuals [77.6%] were White; mean [SD] age, 65.2 [5.5] years) who had an initial LCS examination, 17 863 veterans (63.1%) underwent recommended follow-up within the expected timeframe, whereas 3696 veterans (13.1%) underwent late evaluation, and 4439 veterans (15.7%) had no apparent evaluation. Facility-level differences were associated with 9.2% of the observed variation in rates of late or absent evaluation. In multivariable-adjusted models, Black veterans (odds ratio [OR], 1.19 [95% CI, 1.10-1.29]), veterans with posttraumatic stress disorder (OR, 1.13 [95% CI, 1.03-1.23]), veterans with substance use disorders (OR, 1.11 [95% CI, 1.01-1.22]), veterans with lower income (OR, 0.88 [95% CI, 0.79-0.98]), and those living at a greater distance from a VHA facility (OR, 1.06 [95% CI, 1.02-1.10]) were more likely to experience delayed or no follow-up; veterans with higher risk findings (Lung-RADS category 4 vs Lung-RADS category 1: OR, 0.35 [95% CI, 0.28-0.43]) and those screened in high LCS volume facilities (OR, 0.38 [95% CI, 0.21-0.67]) or academic facilities (OR, 0.86 [95% CI, 0.80-0.92]) were less likely to experience delayed or no follow-up. In sensitivity analyses, varying how stringently adherence was defined, expected evaluation ranged from 14 486 veterans (49.7%) under stringent definitions to 20 578 veterans (78.8%) under liberal definitions.

CONCLUSIONS AND RELEVANCE

In this cohort study that captured follow-up care from the integrated VHA health care system and Medicare, less than two-thirds of patients received timely recommended follow-up after initial LCS, with higher risk of delayed or absent follow-up among marginalized populations, such as Black individuals, individuals with mental health disorders, and individuals with low income, that have long experienced disparities in lung cancer outcomes. Future work should focus on identifying facilities that promote high adherence and disseminating successful strategies to promote equity in LCS among marginalized populations.

Patient Adherence in an Academic Medical Center's Low-dose Computed Tomography Screening Program

OBJECTIVES

Low-dose computed tomography (LDCT) screening is an important tool for reducing lung cancer mortality. This study describes a single center's experience with LDCT and attempts to identify any barriers to compliance with standard guidelines.

MATERIALS AND METHODS

This is a retrospective review of a single university-based hospital system from 2015 to 2019. All individuals who met eligibility for lung cancer screening were entered into a database. The definition of adherence with the screening program was determined by the recommended timeline for the follow-up LDCT. Cohorts were split by adherence and demographics were compared.

RESULTS

A total of 203 LDCTs were performed in 121 patients who met eligibility for LDCT and had appropriate surveillance from 2015 to 2019. The average age was 64 years old. The overall adherence rate for prescribed LDCTs was 59.1%. Patients with Lung-RADS score 2 had 2.43 times higher odds of adherence relative to patients with Lung-RADS score 1 (odds ratio [OR]=2.43; 95% confidence interval [CI]: 1.23-4.83; P=0.011). African American patients had 42% lower odds of adherence relative to white patients (OR=0.58; 95% CI: 0.32-1.06; P=0.076). Patients with non-District of Columbia zip codes had 57% higher odds of adherence relative to those with District of Columbia zip codes, although this did not reach statistical significance (OR=1.57; 95% CI: 0.87-2.82; P=0.136).

CONCLUSIONS

Despite the implementation of a multidisciplinary, academic LDCT screening program, overall adherence rate to prescribed follow-up scans was suboptimal. Socioeconomic disparities and African American race may negatively affect adherence to lung cancer screening LDCT guidelines. Patients with concerning findings on initial LDCT had a higher association of adherence to guidelines.

Patterns and Factors Associated With Adherence to Lung Cancer Screening in Diverse Practice Settings

IMPORTANCE

For lung cancer screening to confer mortality benefit, adherence to annual screening with low-dose computed tomography scans is essential. Although the National Lung Screening Trial had an adherence rate of 95%, current data are limited on screening adherence across diverse practice settings in the United States.

OBJECTIVE

To evaluate patterns and factors associated with adherence to annual screening for lung cancer after negative results of a baseline examination, particularly in centralized vs decentralized screening programs.

DESIGN, SETTING, AND PARTICIPANTS

This observational cohort study was conducted at 5 academic and community-based sites in North Carolina and California among 2283 individuals screened for lung cancer between July 1, 2014, and March 31, 2018, who met US Preventive Services Task Force eligibility criteria, had negative results of a baseline screening examination (American College of Radiology Lung Imaging Reporting and Data System category 1 or 2), and were eligible to return for a screening examination in 12 months.

EXPOSURES

To identify factors associated with adherence, the association of adherence with selected baseline demographic and clinical characteristics, including type of screening program, was estimated using multivariable logistic regression. Screening program type was classified as centralized if individuals were referred through a lung cancer screening clinic or program and as decentralized if individuals had a direct clinician referral for the baseline low-dose computed tomography scan.

MAIN OUTCOMES AND MEASURES

Adherence to annual lung cancer screening, defined as a second low-dose computed tomography scan within 11 to 15 months after baseline screening.

RESULTS

Among the 2283 eligible individuals (1294 men [56.7%]; mean [SD] age, 64.9 [5.8] years; 1160 [50.8%] aged ≥65 years) who had negative screening results at baseline, overall adherence was 40.2% (n = 917), with higher adherence among those who underwent screening through centralized (46.0% [478 of 1039]) vs decentralized (35.3% [439 of 1244]) programs. The independent factor most strongly associated with adherence was type of screening program, with a 2.8-fold increased likelihood of adherence associated with centralized screening (adjusted odds ratio [aOR], 2.78; 95% CI, 1.99-3.88). Another associated factor was age (65-69 vs 55-59 years: aOR, 1.38; 95% CI, 1.07-1.77; 70-74 vs 55-59 years: aOR, 1.47; 95% CI, 1.10-1.96).

CONCLUSIONS AND RELEVANCE

After negative results of a baseline examination, adherence to annual lung cancer screening was suboptimal, although adherence was higher among individuals who were screened through a centralized program. These results support the value of centralized screening programs and the need to further implement strategies that improve adherence to annual screening for lung cancer.

Factors Affecting Patient Adherence to Lung Cancer Screening

OBJECTIVES

The National Lung Screening Trial (NLST) demonstrated a 20% reduction in mortality with low-dose computed tomography (CT) for lung cancer screening (LCS). The NLST found the greatest benefit to LCS for patients who underwent annual screening for a full 3-year follow-up period. The adherence to serial imaging in the NLST was 95%.

METHODS

We conducted a prospective study of 268 patients who presented for LCS and who were not enrolled in a research study to determine the adherence to recommended follow-up imaging and biopsy at a single center. We evaluated the correlations among sociodemographic characteristics, Lung Imaging and Reporting Data System, and adherence.

RESULTS

Only 48% of the patient population received recommended follow-up (either imaging or biopsy) after their referent LCS. Patients with abnormal LCS (Lung Imaging and Reporting Data System 3 or 4) were more likely to adhere to the recommended follow-up (additional imaging or biopsy) compared with those with negative screens. Sex, ethnicity, smoking status, and household income were not correlated with adherence to screening and biopsy.

CONCLUSIONS

The benefits from LCS observed in the NLST may be undermined by low adherence to follow-up screening. Studies targeting LCS patients to bolster adherence to follow-up are needed.

Adherence to annual lung cancer screening with low-dose CT scan in a diverse population

PURPOSE

Our aim was to develop a novel approach for lung cancer screening among a diverse population that integrates the Centers for Medicare and Medicaid Services (CMS) recommended components including shared decision making (SDM), low-dose CT (LDCT), reporting of results in a standardized format, smoking cessation, and arrangement of follow-up care.

METHODS

Between October of 2015 and March of 2018, we enrolled patients, gathered data on demographics, delivery of SDM, reporting of LDCT results using Lung-RADS, discussion of results, and smoking cessation counseling. We measured adherence to follow-up care, cancer diagnosis, cancer treatment, and smoking cessation at 2 years after initial LDCT.

RESULTS

We enrolled 505 patients who were 57% African American, 30% Caucasian, 13% Hispanic, < 1% Asian, and 61% were active smokers. All participants participated in SDM, 88.1% used a decision aid, and 96.1% proceeded with LDCT. Of 496 completing LDCT, all received a discussion about results and follow-up recommendations. Overall, 12.9% had Lung-RADS 3 or 4, and 3.2% were diagnosed with lung cancer resulting in a false-positive rate of 10.7%. All 48 patients with positive screens but no cancer diagnosis adhered to follow-up care at 1 year, but only 35.4% adhered to recommended follow-up care at 2 years. The annual follow-up for patients with negative lung cancer screening results (Lung-RADS 1 and 2) was only 23.7% after one year and 2.8% after 2 years. All active smokers received smoking cessation counseling, but only 11% quit smoking.

CONCLUSION

The findings show that an integrated lung cancer screening program can be safely implemented in a diverse population, but adherence to annual screening is poor.

Patient motivations for non-adherence to lung cancer screening in a military population

Background

Lung cancer remains the leading cause of cancer deaths in the United States, and lung cancer screening has been shown to decrease this mortality. Adherence to lung cancer screening is paramount to realize the mortality benefit, and reported adherence rates vary widely. Few reports address non-adherence to screening, and our study sought to understand the non-compliant patients in our military population.

Methods

This Institutional Review Board approved retrospective review of patients enrolled in our screening program from 2013-2019 identified patients who failed to obtain a subsequent Low Dose CT scan (LDCT) within 15 months of their prior scan. Attempts were made to contact these patients and elucidate motivations for non-adherence via telephone.

Results

Of the 242 patients enrolled, 183 (76%) patients were adherent to the protocol. Significant predictors of non-adherence versus adherence were younger age (P=0.008), female sex (P=0.005), and enlisted officer rank (P=0.03). There was no difference with regards to race, smoking status, pack-years, negative screens, lung-RADS level, or nodule size. 31 (52%) non-adherent patients were contacted, and 24 (77%) reported their reason for non-adherence was lack of follow-up for a LDCT. Twenty (64%) were interested in re-enrollment. Of the total screening cohort, 15 interventions were performed, with lung cancer identified in 5 (2%)-a 67% false positive rate. One stage IV lung cancer was found in a non-adherent patient who re-enrolled.

Conclusions

Lack of perceived contact for follow-up was expressed as the primary reason for non-compliance in our screening program. Compliance is critical to the efficacy of any screening modality, and adherence rates to lung cancer screening may be increased through improved contact with patients via multiple avenues (i.e., phone, email, and letter). There is benefit in contacting non-adherent patients as high rates of re-enrollment are possible.

Patient Adherence to Screening for Lung Cancer in the US: A Systematic Review and Meta-analysis

Importance

To be effective in reducing deaths from lung cancer among high-risk current and former smokers, screening with low-dose computed tomography must be performed periodically.

Objective

To examine lung cancer screening (LCS) adherence rates reported in the US, patient characteristics associated with adherence, and diagnostic testing rates after screening.

Data Sources

Five electronic databases (MEDLINE, Embase, Scopus, CINAHL, and Web of Science) were searched for articles published in the English language from January 1, 2011, through February 28, 2020.

Study Selection

Two reviewers independently selected prospective and retrospective cohort studies from 95 potentially relevant studies reporting patient LCS adherence.

Data Extraction and Synthesis

Quality appraisal and data extraction were performed independently by 2 reviewers using the Newcastle-Ottawa Scale for quality assessment. A random-effects model meta-analysis was conducted when at least 2 studies reported on the same outcome. Reporting followed the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guideline.

Main Outcomes and Measures

The primary outcome was LCS adherence after a baseline screening. Secondary measures were the patient characteristics associated with adherence and the rate of diagnostic testing after screening.

Results

Fifteen studies with a total of 16 863 individuals were included in this systematic review and meta-analysis. The pooled LCS adherence rate across all follow-up periods (range, 12-36 months) was 55% (95% CI, 44%-66%). Regarding patient characteristics associated with adherence rates, current smokers were less likely to adhere to LCS than former smokers (odds ratio [OR], 0.70; 95% CI, 0.62-0.80); White patients were more likely to adhere to LCS than patients of races other than White (OR, 2.0; 95% CI, 1.6-2.6); people 65 to 73 years of age were more likely to adhere to LCS than people 50 to 64 years of age (OR, 1.4; 95% CI, 1.0-1.9); and completion of 4 or more years of college was also associated with increased adherence compared with people not completing college (OR, 1.5; 95% CI, 1.1-2.1). Evidence was insufficient to evaluate diagnostic testing rates after abnormal screening scan results. The main source of variation was attributable to the eligibility criteria for screening used across studies.

Conclusions and Relevance

In this study, the pooled LCS adherence rate after a baseline screening was far lower than those observed in large randomized clinical trials of screening. Interventions to promote adherence to screening should prioritize current smokers and smokers from minority populations.

Factors affecting patient adherence to lung cancer screening: A multisite analysis

OBJECTIVE

To identify factors associated with delayed adherence to follow-up in lung cancer screening.

METHODS

Utilizing a data warehouse and lung cancer screening registry, variables were collected from a referred sample of 3110 unique participants with follow-up CT during the study period (1 January 2016 to 17 October 2018). Adherence was defined as undergoing chest CT within 90 days and 30 days of the recommended time for follow-up and was determined using proportions and multiple variable logistic regression models across the American College of Radiology Lung Imaging Reporting and Data System (Lung-RADS®) categories.

RESULTS

Of 1954 lung cancer screening participants (51.9% (1014/1954) males, 48.1% (940/1954) female; mean age 65.7 (range 45-87), smoking history median 40 pack-years, 60.2% and 44.5% did not follow-up within 30 and 90 days, respectively. Participants receiving Lung-RADS® category 1 or 2 presented later than those with Lung-RADS® category 3 at 90 days (coefficient -27.24, 95% CI -51.31, -3.16, p = 0.027). Participants with Lung-RADS® category 1 presented later than those with Lung-RADS® category 2 at both 90- and 30-days past due (OR 0.76 95% CI [0.59-0.97], p = 0.029 and OR 0.63 95% CI [0.48-0.83], p = 0.001, respectively).

CONCLUSIONS

Adherence to follow-up was higher among participants receiving more suspicious Lung-RADS® results at index screening CT and among those who had undergone more non-lung cancer screening imaging examinations prior to index lung cancer screening CT. These observations may inform strategies aimed at prospectively identifying participants at risk for delayed or nonadherence to prevent potential morbidity and mortality from incident lung cancers.

Racial/Ethnic Disparities in Follow-Up Adherence for Incidental Pulmonary Nodules: An Application of a Cascade-of-Care Framework

PURPOSE

The aim of this study was to evaluate racial/ethnic disparities in follow-up adherence for incidental pulmonary nodules (IPNs) using a cascade-of-care framework, representing the multistage pathway from IPN diagnosis to timely follow-up adherence.

METHODS

A cohort of 1,562 patients diagnosed with IPNs requiring follow-up in a tertiary health care system in 2016 were retrospectively identified. Racial/ethnic disparities in follow-up adherence were examined by developing a multistep cascade-of-care model (provider communication, follow-up examination ordering and scheduling, adherence) to identify where patients were most likely to fall off the path toward adherence. Racial/ethnic adherence disparities were measured using descriptive statistics and multivariate modeling, controlling for sociodemographic, communication, and health characteristics.

RESULTS

Among 1,562 patients whose IPNs required follow-up, unadjusted results showed that nonwhite patients were less likely to meet each step on the cascade than White patients: for provider-patient IPN communication, 55% among Black patients and 80% among White patients; for follow-up ordering and scheduling, 42% and 41% among Black patients and 66% and 64% among White patients; and for timely adherence, 29% among Black patients and 54% among White patients. Adjusting for provider communication, sociodemographic, and health characteristics, Black patients had increased odds of never adhering to and delaying follow-up compared with White patients (odds ratios, 1.30 [95% confidence interval, 0.90-1.89] and 2.51 [95% confidence interval, 1.54-4.09], respectively).

CONCLUSIONS

These findings demonstrate substantial racial/ethnic disparities in IPN follow-up adherence that persist after adjusting for multiple characteristics. The cascade of care demonstrates where on the adherence pathway patients are at risk for falling off, enabling specific targets for health policy and clinical interventions. Radiologists can play a key role in improving IPN follow-up via increased patient care involvement.

Association of a Lung Screening Program Coordinator With Adherence to Annual CT Lung Screening at a Large Academic Institution

BACKGROUND

Detection of early-stage lung cancer improves during subsequent rounds of screening with low-dose CT and potentially leads to saving lives with curative treatment. Therefore, adherence to annual lung screening is important. We hypothesized that adherence to annual screening would increase after hiring of a dedicated program coordinator.

METHODS

We performed a mixed-methods study in a retrospective cohort of patients who underwent lung screening at our academic institution between January 1, 2014, and March 31, 2018. Patients with baseline lung screening examinations performed between January 1, 2014, and September 30, 2016, with Lung CT Screening Reporting & Data System 1 or 2 scores and a 12-month follow-up recommendation were included. We tracked patient adherence to annual follow-up lung screening over time (before and after hiring of a program coordinator) and conducted a cross-sectional survey of patients nonadherent to annual follow-up to elicit quantitative and qualitative feedback.

RESULTS

Of the 319 patients who completed baseline lung screening with normal results, 189 (59%) were adherent to annual follow-up recommendations and 130 (41%) were nonadherent. Patient adherence varied over time: 21.7% adherence (10 of 46) before hiring a program coordinator and 65.6% adherence (179 of 273) after the program coordinator's hire date. Patients reported the following reasons for nonadherence to annual lung screening: lack of transportation, financial cost, lack of communication by physicians, and lack of current symptoms.

CONCLUSIONS

Adherence to annual lung screening after normal baseline studies increased significantly over time. Hiring a full-time program coordinator was likely associated with this increased in adherence.

Automated Tracking of Follow-Up Imaging Recommendations

OBJECTIVE. Radiology reports often contain follow-up imaging recommendations. Failure to comply with these recommendations in a timely manner can lead to poor patient outcomes, complications, and legal liability. As such, the primary objective of this research was to determine adherence rates to follow-up recommendations. MATERIALS AND METHODS. Radiology-related examination data, including report text, for examinations performed between June 1, 2015, and July 31, 2017, were extracted from the radiology departments at the University of Washington (UW) and Lahey Hospital and Medical Center (LHMC). The UW dataset contained 923,885 examinations, and the LHMC dataset contained 763,059 examinations. A 1-year period was used for detection of imaging recommendations and up to 14-months for the follow-up examination to be performed. RESULTS. On the basis of an algorithm with 97.9% detection accuracy, the follow-up imaging recommendation rate was 11.4% at UW and 20.9% at LHMC. Excluding mammography examinations, the overall follow-up imaging adherence rate was 51.9% at UW (range, 44.4% for nuclear medicine to 63.0% for MRI) and 52.0% at LHMC (range, 30.1% for fluoroscopy to 63.2% for ultrasound) using a matcher algorithm with 76.5% accuracy. CONCLUSION. This study suggests that follow-up imaging adherence rates vary by modality and between sites. Adherence rates can be influenced by various legitimate factors. Having the capability to identify patients who can benefit from patient engagement initiatives is important to improve overall adherence rates. Monitoring of follow-up adherence rates over time and critical evaluation of variation in recommendation patterns across the practice can inform measures to standardize and help mitigate risk.

Process improvement for follow-up radiology report recommendations of lung nodules

In the modern healthcare system, there are still wide gaps of communication of imaging results to physician and patient stakeholders and tracking of whether follow-up has occurred. Patients are also unaware of the significance of findings in radiology reports. With the increase in use of cross-sectional imaging such as CT, patients are not only being diagnosed with primary urgent findings but also with incidental findings such as lung nodules; however, they are not being told of their imaging findings nor what actions to take to mitigate their risks. In addition, patients at high risk for developing lung cancer often obtain serial CT scans, but tracking these patients is challenging for the clinician.

In order to advance quality improvement goals and improve patient outcomes, we developed a custom application and business process for radiology practitioners that mines available healthcare data, identifies patients with lung nodules in need of follow-up imaging, notifies the patient and the primary care physician via mail, and measures process efficacy via executed follow-up screenings and captured patient condition.

This integrated analytics and communication process increased our average rate of patient follow-ups for lung nodules from 26.50 in 2015 to 59.72% in 2017. 17.18% of these patients had new lung nodules or worsening severity of lung findings detected at follow-up. This new process has added missing quality and care coordination to an at-risk patient population.