Experienced financial toxicity among long-term cancer survivors: results from a national cross-sectional survey.

PURPOSE: Financial toxicity, the subjective distress caused by objective financial burden, significantly impacts cancer survivors. Yet, enduring effects on survivors remain unclear. Therefore, we investigated the experienced objective financial burden and subjective financial distress in long-term cancer survivors. METHODS: A cross-sectional nationwide online survey of adult cancer survivors ≥ 5y after diagnosis were analyzed. Objective financial burden was measured via extra expenses and income loss, while subjective financial distress covered psychological well-being, coping and support-seeking behavior, and financial concerns. Groups were compared (i.e., having cancer vs. former patients) by t-tests and chi-squared tests. Financial toxicity was visualized with Sankey plots and sunburst diagrams. RESULTS: 4,675 respondents completed the survey, of whom 2,391 (51%) were ≥ 5y after their cancer diagnosis. Among them, 75% experienced income loss and/or extra expenses after diagnosis. One-third of the previously employed respondents relied on work disability benefits. Further, 'being unable to make ends meet' increased from 2% before diagnosis to 13% ≥ 5y after diagnosis (p < .001). Additionally, 58% reported negative psychological impacts of financial toxicity, and 47% worried about their financial future. CONCLUSIONS: Cancer survivors often face income loss and additional expenses, leading to ongoing financial difficulties that affect their psychological well-being. Despite this significant impact, there is a lack of guidance and support to help them manage these financial challenges. These findings highlight the need for healthcare professionals to recognize and address the financial challenges. IMPLICATIONS FOR CANCER SURVIVORS: This study underscores the widespread financial challenges cancer survivors encounter, emphasizing the need for ongoing financial support and comprehensive assessments of their physical and psychological well-being.

mRNA-1273 vaccination induces polyfunctional memory CD4 and CD8 T cell responses in patients with solid cancers undergoing immunotherapy or/and chemotherapy.

Introduction: Research has confirmed the safety and comparable seroconversion rates following SARS-CoV-2 vaccination in patients with solid cancers. However, the impact of cancer treatment on vaccine-induced T cell responses remains poorly understood. Methods: In this study, we expand on previous findings within the VOICE trial by evaluating the functional and phenotypic composition of mRNA-1273-induced T cell responses in patients with solid tumors undergoing immunotherapy, chemotherapy, or both, compared to individuals without cancer. We conducted an ELISpot analysis on 386 participants to assess spike-specific T cell responses 28 days after full vaccination. Further in-depth characterization of using flow cytometry was performed on a subset of 63 participants to analyze the functional phenotype and differentiation state of spike-specific T cell responses. Results: ELISpot analysis showed robust induction of spike-specific T cell responses across all treatment groups, with response rates ranging from 75% to 80%. Flow cytometry analysis revealed a distinctive cytokine production pattern across cohorts, with CD4 T cells producing IFNγ, TNF, and IL-2, and CD8 T cells producing IFNγ, TNF, and CCL4. Variations were observed in the proportion of monofunctional CD4 T cells producing TNF, particularly higher in individuals without cancer and patients treated with chemotherapy alone, while those treated with immunotherapy or chemoimmunotherapy predominantly produced IFNγ. Despite these differences, polyfunctional spike-specific memory CD4 and CD8 T cell responses were comparable across cohorts. Notably, immunotherapy-treated patients exhibited an expansion of spike-specific CD4 T cells with a terminally differentiated effector memory phenotype. Discussion: These findings demonstrate that systemic treatment in patients with solid tumors does not compromise the quality of polyfunctional mRNA-1273-induced T cell responses. This underscores the importance of COVID-19 vaccination in patients with solid cancers undergoing systemic treatment.

Clinical Utility of Circulating Tumor DNA in Patients With Advanced KRASG12C-Mutated NSCLC Treated With Sotorasib.

INTRODUCTION: For patients with KRASG12C-mutated NSCLC who are treated with sotorasib, there is a lack of biomarkers to guide treatment decisions. We therefore investigated the clinical utility of pretreatment and on-treatment circulating tumor DNA (ctDNA) and treatment-emergent alterations on disease progression. METHODS: Patients with KRASG12C-mutated NSCLC treated with sotorasib were prospectively enrolled in our biomarker study (NCT05221372). Plasma samples were collected before sotorasib treatment, at first-response evaluation and at disease progression. The TruSight Oncology 500 panel was used for ctDNA and variant allele frequency analysis. Tumor response and progression-free survival were assessed per Response Evaluation Criteria in Solid Tumors version 1.1. RESULTS: Pretreatment KRASG12C ctDNA was detected in 50 of 66 patients (76%). Patients with detectable KRASG12C had inferior progression-free survival (hazard ratio [HR] 2.13 [95% confidence interval [CI]: 1.06-4.30], p = 0.031) and overall survival (HR 2.61 [95% CI: 1.16-5.91], p = 0.017). At first-response evaluation (n = 40), 29 patients (73%) had a molecular response. Molecular nonresponders had inferior overall survival (HR 3.58 [95% CI: 1.65-7.74], p = 0.00059). The disease control rate was significantly higher in those with a molecular response (97% versus 64%, p = 0.015). KRAS amplifications were identified as recurrent treatment-emergent alterations. CONCLUSIONS: Our data suggest detectable pretreatment KRASG12C ctDNA as a marker for poor prognosis and on-treatment ctDNA clearance as a marker for treatment response. We identified KRAS amplifications as a potential recurring resistance mechanism to sotorasib. Identifying patients with superior prognosis could aid in optimizing time of treatment initiation, and identifying patients at risk of early progression could allow for earlier treatment decisions.

Osimertinib Plasma Trough Concentration in Relation to Brain Metastases Development in Patients With Advanced EGFR-Mutated NSCLC.

Introduction: Brain metastases (BM) are common in patients with advanced EGFR-mutated (EGFRm+) NSCLC. Despite good BM-related outcomes of osimertinib, several patients still experience intracranial progression. A possible explanation is pharmacologic failure due to low plasma trough levels (Cmin,SS) and consequently limited intracranial osimertinib exposure. We investigated the relation between osimertinib Cmin,SS and BM development or progression. Methods: A prospective multicenter cohort study, including patients receiving osimertinib for advanced EGFRm+ NSCLC. At osimertinib start, patients were allocated to the BM or no or unknown BM cohort and were further divided into subgroups based on osimertinib Cmin,SS (low, middle, and high exposure). Cumulative incidence of BM progression or development and overall survival were determined for each group. Results: A total of 173 patients were included, with 49 (28.3%) had baseline BM. Of these patients, 36.7% experienced BM progression, of which 16.7% in the low (<159.3 ng/mL), 40.0% in the middle, and 47.1% in the high (>270.7 ng/mL) Cmin,SS subgroups. After 12 months, the cumulative incidence of BM progression for the BM cohort was 20% (95% confidence interval [CI] 2.6-49.0), 31% (95% CI:10.6-53.9), and 31% (95% CI:10.8-54.5) per Cmin,SS subgroup, respectively. After 20 months, this was 20% (95% CI:2.6-49.0), 52% (95% CI:23.8-74.2), and 57% (95% CI:24.9-79.7), respectively. For the no or unknown BM cohort, 4.0% developed BM without differences within Cmin,SS subgroups. Conclusions: No relation was found between osimertinib Cmin,SS and BM development or progression in patients with advanced EGFRm+ NSCLC. This suggests that systemic osimertinib exposure is not a surrogate marker for BM development or progression.

Hepatotoxicity in patients with non-small cell lung cancer treated with sotorasib after prior immunotherapy: a comprehensive clinical and pharmacokinetic analysis.

BACKGROUND: Sotorasib given after immunotherapy could put patients at increased risk of hepatotoxicity. Therefore, there is a need to gain insight into the potential correlation between anti-PD-(L)1 treatment, anti-PD-(L)1 concentrations, sotorasib concentrations, and the incidence of hepatotoxicity during sotorasib. METHODS: Patients with KRASG12C-mutated NSCLC treated with sotorasib were prospectively enrolled in our biomarker cohort study (NCT05221372). Plasma samples were collected prior and during sotorasib treatment for anti-PD-1 and sotorasib concentrations. ALT/AST/ALP/GGT increases were collected prospectively and graded according to CTCAEv5.0. Severe hepatotoxicity was defined as grade ≥3 ALT/AST/ALP/GGT increase. FINDINGS: Of the 91 included patients, 80 (88%) received prior anti-PD-(L)1. Prior anti-PD-(L)1 and prior immune-related hepatotoxicity were associated with a higher incidence of severe hepatotoxicity (35% versus 0%, p = 0.016 and 75% versus 31%, p = 0.019, respectively). Patients with an interval of ≤6 weeks between anti-PD-(L)1 and sotorasib (n = 18) had a significantly higher incidence of severe hepatotoxicity than those with a 6-12 week (n = 24) and ≥12 week (n = 38) interval (83% versus 33% versus 13%, respectively, p < 0.0001). Sotorasib trough concentrations did not differ significantly between those with or without severe hepatotoxicity (106 versus 126 ng/mL, p = 0.16). Pembrolizumab concentrations were higher in those with severe hepatotoxicity versus those without (25.6 versus 6.1 µg/mL, p < 0.0001). INTERPRETATION: In this preliminary prospective study, sotorasib after PD-(L)1 blockade was associated with severe hepatotoxicity, especially in patients with a short interval between treatments, prior immune-related hepatitis and higher anti-PD-1 plasma concentrations. Our results suggest a minimum interval of 6 weeks between anti-PD-(L)1 and sotorasib to minimize the risk of hepatotoxicity. FUNDING: None.

Quantitative modeling of tumor dynamics and development of drug resistance in non-small cell lung cancer patients treated with erlotinib.

Insight into the development of treatment resistance can support the optimization of anticancer treatments. This study aims to characterize the tumor dynamics and development of drug resistance in patients with non-small cell lung cancer treated with erlotinib, and investigate the relationship between baseline circulating tumor DNA (ctDNA) data and tumor dynamics. Data obtained for the analysis included (1) intensively sampled erlotinib concentrations from 29 patients from two previous pharmacokinetic (PK) studies, and (2) tumor sizes, ctDNA measurements, and sparsely sampled erlotinib concentrations from 18 patients from the START-TKI study. A two-compartment population PK model was first developed which well-described the PK data. The PK model was subsequently applied to investigate the exposure-tumor dynamics relationship. To characterize the tumor dynamics, models accounting for intra-tumor heterogeneity and acquired resistance with or without primary resistance were investigated. Eventually, the model assumed acquired resistance only resulted in an adequate fit. Additionally, models with or without exposure-dependent treatment effect were explored, and no significant exposure-response relationship for erlotinib was identified within the observed exposure range. Subsequently, the correlation of baseline ctDNA data on EGFR and TP53 variants with tumor dynamics' parameters was explored. The analysis indicated that higher baseline plasma EGFR mutation levels correlated with increased tumor growth rates, and the inclusion of ctDNA measurements improved model fit. This result suggests that quantitative ctDNA measurements at baseline have the potential to be a predictor of anticancer treatment response. The developed model can potentially be applied to design optimal treatment regimens that better overcome resistance.

Overall Survival From the EORTC LCG-1613 APPLE Trial of Osimertinib Versus Gefitinib Followed by Osimertinib in Advanced EGFR-Mutant Non-Small-Cell Lung Cancer.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.Osimertinib has been established as a standard of care for patients with common sensitizing EGFR-mutant advanced non-small-cell lung cancer (NSCLC) although the sequential approach (first-generation inhibitor gefitinib followed by osimertinib) has not been formally compared. The phase II APPLE trial (ClinicalTrials.gov identifier: NCT02856893) enrolled 156 treatment-naïve patients, and two treatment strategies were evaluated: osimertinib up front or the sequential treatment approach with gefitinib up front followed by osimertinib at the time of progression, either molecular progression (detection of plasma T790M resistance mutation) regardless of the radiologic status or just at the time of radiologic progression. Patients' characteristics were well balanced, except for the higher proportion of baseline brain metastases in the sequential approach (29% v 19%). Per protocol, 73% of patients switched to osimertinib in the sequential arm. Up-front treatment with osimertinib was associated with a lower risk of brain progression versus the sequential approach (hazard ratio [HR], 0.54 [90% CI, 0.34 to 0.86]), but a comparable overall survival was observed between both strategies (HR, 1.01 [90% CI, 0.61 to 1.68]), with the 18-month survival probability of 84% and 82.3%, respectively. The APPLE trial suggests that a sequential treatment approach is associated with more frequent progression in the brain but a similar survival in advanced EGFR-mutant NSCLC.

Exploring the impact of patient-specific clinical features on osimertinib effectiveness in a real-world cohort of patients with EGFR mutated non-small cell lung cancer.

Osimertinib is prescribed to patients with metastatic non-small cell lung cancer (NSCLC) and a sensitizing EGFR mutation. Limited data exists on the impact of patient characteristics or osimertinib exposure on effectiveness outcomes. This was a Dutch, multicenter cohort study. Eligible patients were ≥18 years, with metastatic EGFRm+ NSCLC, receiving osimertinib. Primary endpoint was progression-free survival (PFS). Secondary endpoints included overall survival (OS) and safety. Kaplan-Meier analyses and multivariate Cox proportional hazard models were performed. In total, 294 patients were included. Primary EGFR-mutations were mainly exon 19 deletions (54%) and p.L858R point mutations (30%). Osimertinib was given in first-line (40%), second-line (46%) or beyond (14%), with median PFS 14.4 (95% CI: 9.4-19.3), 13.9 (95% CI: 11.3-16.1) and 8.7 months (95% CI: 4.6-12.7), respectively. Patients with low BMI (<20.0 kg/m2 ) had significantly shorter PFS/OS compared to all other subgroups. Patients with a high plasma trough concentration in steady state (Cmin,SS ; >271 ng/mL) had shorter PFS compared to a low Cmin,SS (<163 ng/mL; aHR 2.29; 95% CI: 1.13-4.63). A significant longer PFS was seen in females (aHR = 0.61, 95% CI: 0.45-0.82) and patients with the exon 19 deletion (aHR = 0.58, 95% CI: 0.36-0.92). A trend towards longer PFS was seen for TP53 wild-type patients, while age did not impact PFS. Patients with a primary EGFR exon 19 deletion had longer PFS, while a low BMI, male sex and a high Cmin,SS were indicative for shorter PFS and/or OS. Age was not associated with effectiveness outcomes of osimertinib.

Differentiating interstitial lung diseases from other respiratory diseases using electronic nose technology.

INTRODUCTION: Interstitial lung disease (ILD) may be difficult to distinguish from other respiratory diseases due to overlapping clinical presentation. Recognition of ILD is often late, causing delay which has been associated with worse clinical outcome. Electronic nose (eNose) sensor technology profiles volatile organic compounds in exhaled breath and has potential to detect ILD non-invasively. We assessed the accuracy of differentiating breath profiles of patients with ILD from patients with asthma, chronic obstructive pulmonary disease (COPD), and lung cancer using eNose technology. METHODS: Patients with ILD, asthma, COPD, and lung cancer, regardless of stage or treatment, were included in a cross-sectional study in two hospitals. Exhaled breath was analysed using an eNose (SpiroNose) and clinical data were collected. Datasets were split in training and test sets for independent validation of the model. Data were analyzed with partial least squares discriminant and receiver operating characteristic analyses. RESULTS: 161 patients with ILD and 161 patients with asthma (n = 65), COPD (n = 50) or lung cancer (n = 46) were included. Breath profiles of patients with ILD differed from all other diseases with an area under the curve (AUC) of 0.99 (95% CI 0.97-1.00) in the test set. Moreover, breath profiles of patients with ILD could be accurately distinguished from the individual diseases with an AUC of 1.00 (95% CI 1.00-1.00) for asthma, AUC of 0.96 (95% CI 0.90-1.00) for COPD, and AUC of 0.98 (95% CI 0.94-1.00) for lung cancer in test sets. Results were similar after excluding patients who never smoked. CONCLUSIONS: Exhaled breath of patients with ILD can be distinguished accurately from patients with other respiratory diseases using eNose technology. eNose has high potential as an easily accessible point-of-care medical test for identification of ILD amongst patients with respiratory symptoms, and could possibly facilitate earlier referral and diagnosis of patients suspected of ILD.

Identification of protein biomarkers for prediction of response to platinum-based treatment regimens in patients with non-small cell lung cancer.

The majority of patients with resected stage II-IIIA non-small cell lung cancer (NSCLC) are treated with platinum-based adjuvant chemotherapy (ACT) in a one-size-fits-all approach. However, a significant number of patients do not derive clinical benefit, and no predictive patient selection biomarker is currently available. Using mass spectrometry-based proteomics, we have profiled tumour resection material of 2 independent, multi-centre cohorts of in total 67 patients with NSCLC who underwent ACT. Unsupervised cluster analysis of both cohorts revealed a poor response/survival sub-cluster composed of ~ 25% of the patients, that displayed a strong epithelial-mesenchymal transition signature and stromal phenotype. Beyond this stromal sub-population, we identified and validated platinum response prediction biomarker candidates involved in pathways relevant to the mechanism of action of platinum drugs, such as DNA damage repair, as well as less anticipated processes such as those related to the regulation of actin cytoskeleton. Integration with pre-clinical proteomics data supported a role for several of these candidate proteins in platinum response prediction. Validation of one of the candidates (HMGB1) in a third independent patient cohort using immunohistochemistry highlights the potential of translating these proteomics results to clinical practice.

Systematic Literature Review of the Prevalence and Prognostic Value of Delta-Like Ligand 3 Protein Expression in Small Cell Lung Cancer.

BACKGROUND: Delta-like ligand 3 (DLL3), a member of the Notch pathway, has been identified as a potential therapeutic target as it is highly expressed in small cell lung cancer (SCLC), a subtype accounting for 15% of lung cancer cases. OBJECTIVE: A systematic literature review (SLR) was conducted to understand the prevalence and prognostic impact of DLL3 expression on survival of patients with SCLC and treatment response. PATIENTS AND METHODS: Systematic literature searches were conducted across multiple databases to capture studies of any SCLC population that evaluated DLL3 expression. Specific outcomes of interest included prevalence of DLL3 expression, method of expression analysis, and impact on outcome, including treatment response and survival (overall, progression-free, disease-free) according to varying levels of DLL3 expression/positivity. Standard risk of bias tools were used to evaluate study quality. RESULTS: Among the 30 included studies, the most common DLL3 testing method was immunohistochemistry (N = 26, 86.7%). For comparability, results focused on the 13 (22.3%) studies that used the Ventana DLL3 (SP347) immunohistochemistry assay. The prevalence of DLL3 positivity ranged from 80.0-93.5% for studies using a threshold of ≥ 1% of tumor cells (N = 4) and 58.3-91.1% for studies with a ≥ 25% threshold (N = 4). DLL3 expression was generally categorized as high using cutoffs of ≥ 50% (prevalence range: 45.8-79.5%; N = 6) or ≥ 75% (prevalence range: 47.3-75.6%; N = 5) of cells with positivity. Two studies used an H-score of ≥ 150 to define high DLL3 expression with prevalence ranging from 33.3-53.1%. No consistent associations were seen between DLL3 expression level and patient age, sex, smoking history, or disease stage. Two studies reported change in DLL3 expression category (high versus low) before and after chemotherapy. No statistically significant differences were reported between DLL3 expression groups and survival (overall, progression-free, or disease-free) or treatment response. CONCLUSIONS: There is a high prevalence of DLL3 expression in SCLC. Further research and analytical methods may help to characterize different populations of patients with SCLC based on DLL3 expression. While no significant prognostic factor in the included studies was identified, additional cohort studies using standardized methodology, with longer follow-up, are needed to better characterize any potential differences in patient survival or response by DLL3 expression level in SCLC.

Artificial intelligence-based recurrence prediction outperforms classical histopathological methods in pulmonary adenocarcinoma biopsies.

INTRODUCTION: Between 10 and 50% of early-stage lung adenocarcinoma patients experience local or distant recurrence. Histological parameters such as a solid or micropapillary growth pattern are well-described risk factors for recurrence. However, not every patient presenting with such a pattern will develop recurrence. Designing a model which can more accurately predict recurrence on small biopsy samples can aid the stratification of patients for surgery, (neo-)adjuvant therapy, and follow-up. MATERIAL AND METHODS: In this study, a statistical model on biopsies fed with histological data from early and advanced-stage lung adenocarcinomas was developed to predict recurrence after surgical resection. Additionally, a convolutional neural network (CNN)-based artificial intelligence (AI) classification model, named AI-based Lung Adenocarcinoma Recurrence Predictor (AILARP), was trained to predict recurrence, with an ImageNet pre-trained EfficientNet that was fine-tuned on lung adenocarcinoma biopsies using transfer learning. Both models were validated using the same biopsy dataset to ensure that an accurate comparison was demonstrated. RESULTS: The statistical model had an accuracy of 0.49 for all patients when using histology data only. The AI classification model yielded a test accuracy of 0.70 and 0.82 and an area under the curve (AUC) of 0.74 and 0.87 on patch-wise and patient-wise hematoxylin and eosin (H&E) stained whole slide images (WSIs), respectively. CONCLUSION: AI classification outperformed the traditional clinical approach for recurrence prediction on biopsies by a fair margin. The AI classifier may stratify patients according to their recurrence risk, based only on small biopsies. This model warrants validation in a larger lung biopsy cohort.