Neal, Joel W

Abstract The complementarity and clinical utility of combining liquid biopsies and radiomic image analysis has not been demonstrated. ctDNA minimal residual disease after chemoradiotherapy (CRT) for non–small cell lung cancer (NSCLC) is highly prognostic, but on-treatment biomarkers are needed to enable response-adapted therapies. In this study, we analyzed 418 patients with NSCLC undergoing CRT to develop and validate a novel dynamic risk model that accurately predicts ultimate progression-free survival during treatment. We optimize tissue-free variant calling from plasma samples to facilitate ctDNA monitoring and demonstrate the importance of accounting for persistent clonal hematopoiesis variants. We show that mid-CRT ctDNA concentration is prognostic for disease progression and integrate additional pre-CRT risk factors, including radiomics, into a combined model that improves outcome prediction. Our results suggest that tumor features, radiomics, and mid-CRT ctDNA analysis are complementary and can identify patients at high and low risk of progression to potentially enable response-adapted therapies. Significance: This study demonstrates that combining tumor features, radiomics, and ctDNA analysis improves outcome prediction in NSCLC treated with CRT therapy. Our integrated model could enable personalized and response-adapted therapies to reduce toxicity and improve outcomes in patients. See related commentary by Anagnostou and Aggarwal, p. 1534

AbstractBackgroundRecent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk‐prediction model (called SPLC‐RAT) was developed and validated using data from population‐based epidemiological cohorts and clinical trials, but real‐world validation has been lacking. The predictive performance of SPLC‐RAT was evaluated in a hospital‐based cohort of lung cancer survivors.MethodsThe authors analyzed data from 8448 ever‐smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997–2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC‐RAT and further explored the potential of improving SPLC detection through risk model‐based surveillance using SPLC‐RAT versus existing clinical surveillance guidelines.ResultsOf 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person‐years. The application of SPLC‐RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10‐year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC‐RAT development cohort), the observed SPLC incidence was significantly elevated in the high‐risk versus low‐risk subgroup (13.1% vs. 1.1%, p < 1 × 10–6). The risk‐based surveillance through SPLC‐RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow‐ups needed to detect one SPLC (162 vs. 202).ConclusionIn a large, hospital‐based cohort, the authors validated the predictive performance of SPLC‐RAT in identifying high‐risk survivors of SPLC and showed its potential to improve SPLC detection through risk‐based surveillance.Plain Language Summary Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence‐based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk‐prediction model was developed and validated using data from population‐based epidemiological cohorts and clinical trials, but real‐world validation has been lacking. Using a large, real‐world cohort of lung cancer survivors, we showed the high predictive accuracy and risk‐stratification ability of the SPLC risk‐prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model‐based surveillance strategies compared to the existing consensus‐based clinical guidelines, including the National Comprehensive Cancer Network.

AbstractBackgroundTobacco use is associated with adverse outcomes among patients diagnosed with cancer. Socioeconomic determinants influence access and utilization of tobacco treatment; little is known about the relationship between neighborhood socioeconomic disadvantage (NSD) and tobacco assessment, assistance, and cessation among patients diagnosed with cancer.MethodsA modified Cancer Patient Tobacco Use Questionnaire (C‐TUQ) was administered to patients enrolled in nine ECOG‐ACRIN clinical trials. We examined associations of NSD with (1) smoking status, (2) receiving tobacco cessation assessment and support, and (3) cessation behaviors. NSD was classified by tertiles of the Area Deprivation Index. Associations between NSD and tobacco variables were evaluated using logistic regression.ResultsA total of 740 patients completing the C‐TUQ were 70% male, 94% White, 3% Hispanic, mean age 58.8 years. Cancer diagnoses included leukemia 263 (36%), lymphoma 141 (19%), prostate 131 (18%), breast 79 (11%), melanoma 69 (9%), myeloma 53 (7%), and head and neck 4 (0.5%). A total of 402 (54%) never smoked, 257 (35%) had formerly smoked, and 81 (11%) were currently smoking. Patients in high disadvantaged neighborhoods were approximately four times more likely to report current smoking (odds ratio [OR], 3.57; 95% CI, 1.69–7.54; p = .0009), and more likely to report being asked about smoking (OR, 4.24; 95% CI, 1.64–10.98; p = .0029), but less likely to report receiving counseling (OR, 0.11; 95% CI, 0.02–0.58; p = .0086) versus those in the least disadvantaged neighborhoods.ConclusionsGreater neighborhood socioeconomic disadvantage was associated with smoking but less cessation support. Increased cessation support in cancer care is needed, particularly for patients from disadvantaged neighborhoods.

Abstract Background: While cigarette smoking has declined among the U.S. general population, sale and use of non-cigarette alternative tobacco products (ATP; e.g., e-cigarettes, cigars) and dual use of cigarettes/ATPs are rising. Little is known about ATP use patterns in cancer survivors enrolled in clinical trials. We investigated prevalence of tobacco product use, and factors associated with past 30-day use, among patients with cancer in national trials. Methods: Cancer survivors (N = 756) enrolled in 9 ECOG-ACRIN clinical trials (2017–2021) completed a modified Cancer Patient Tobacco Use Questionnaire (C-TUQ) which assessed baseline cigarette and ATP use since cancer diagnosis and in the past 30 days. Results: Patients were on average 59 years old, 70% male, and the mean time since cancer diagnosis was 26 months. Since diagnosis, cigarettes (21%) were the most common tobacco product used, followed by smokeless tobacco use (5%), cigars (4%), and e-cigarettes (2%). In the past 30 days, 12% of patients reported smoking cigarettes, 4% cigars, 4% using smokeless tobacco, and 2% e-cigarettes. Since cancer diagnosis, 5.5% of the sample reported multiple tobacco product use, and 3.0% reported multiple product use in the past 30 days. Males (vs. females; OR 4.33; P = 0 &lt; 0.01) and individuals not living with another person who smokes (vs. living with; OR, 8.07; P = 0 &lt; 0.01) were more likely to use ATPs only versus cigarettes only in the past 30 days. Conclusions: Among patients with cancer, cigarettes were the most prevalent tobacco product reported. Impact: Regardless, ATPs and multiple tobacco product use should be routinely assessed in cancer care settings.