Cost-effectiveness analysis of a lung cancer screening program in the netherlands: a simulation based on NELSON and NLST study outcomes.

BACKGROUND: In the Netherlands, lung cancer is the leading cause of cancer-related death, accounting for more than 10,000 annual deaths. Lung cancer screening (LCS) studies using low-dose computed tomography (LDCT) have demonstrated that early detection reduces lung cancer mortality. However, no LCS program has been implemented yet in the Netherlands. A national LCS program has the potential to enhance the health outcomes for lung cancer patients in the Netherlands. OBJECTIVE AND METHODS: This study evaluates the cost-effectiveness of LCS compared to no-screening in the Netherlands, by simulating the screening outcomes based on data from NEderlands-Leuvens Longkanker Screenings ONderzoek (NELSON) and National Lung Screening Trial (NLST). We simulated annual screening up to 74 years of age, using inclusion criteria from the respective studies. A decision tree and Markov model was used to predict the incremental costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICERs) for the screening population. The analysis used a lifetime horizon and a societal perspective. RESULTS: Compared to no-screening, LCS resulted in an ICER of €5,169 per QALY for the NELSON simulation, and an ICER of €17,119 per QALY for the NLST simulation. The screening costs were highly impactful for the cost-effectiveness. The most influential parameter was the CT scan cost. Cost reduction for CT from €201 to €101 per scan would reduce the ICER to €2,335 using NELSON criteria. Additionally, LCS could prevent 15,115 and 12,611 premature lung cancer deaths, accompanied by 1.66 and 1.31 QALYs gained per lung cancer case for the NELSON and NLST simulations, respectively. CONCLUSION: LCS was estimated to be cost-effective in the Netherlands for both simulations at a willingness-to-pay threshold of €20,000 per QALY. Using the NELSON criteria, less than €5,500 per QALY had to be spent. Lowering the cost per CT exam would lead to a further reduction of this amount.

Development and validation of an ultra-performance liquid chromatography-tandem mass spectrometry method to quantify the small molecule inhibitors adagrasib, alectinib, brigatinib, capmatinib, crizotinib, lorlatinib, selpercatinib, and sotorasib in human plasma.

Small molecule inhibitors (SMIs) are increasingly being used in the treatment of non-small cell lung cancer. To support pharmacokinetic research and clinical treatment monitoring, our aim was to develop and validate an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) assay for quantification of eight SMIs: adagrasib, alectinib, brigatinib, capmatinib, crizotinib, lorlatinib, selpercatinib, and sotorasib. Development of the UPLC-MS/MS assay was done by trying different columns and eluents to optimize peak shape. The assay was validated based on guidelines of the European Medicines Agency. Chromatographic separation was performed with a gradient elution using ammonium formate in water and methanol. Detection was performed using a triple quadrupole tandem mass spectrometer with electrospray ionization. Validation was performed in a range of 10-2500 µg/L for lorlatinib, 25-6250 µg/L for alectinib and crizotinib, 25-10,000 µg/L for capmatinib and selpercatinib, 50-12,500 µg/L for brigatinib, and 100-25,000 µg/L for adagrasib and sotorasib. Imprecision was <8.88% and inaccuracy was <12.5% for all compounds. Seven out of eight compounds were stable for 96 h at room temperature. Sotorasib was stable for 8 h at room temperature. A sensitive and reliable method has been developed to quantify eight SMIs with a single assay, enhancing efficacy and safety of targeted therapies.

Head-to-head comparison of composite and individual biomarkers to predict clinical benefit to PD-1 blockade in non-small cell lung cancer.

BACKGROUND: The efficacy of PD-1 blocking agents in advanced NSCLC has shown prolonged effectiveness, but only in a minority of patients. Multiple biomarkers have been explored to predict treatment benefit, yet their combined performance remains inadequately examined. In this study, we assessed the combined predictive performance of multiple biomarkers in NSCLC patients treated with nivolumab. METHODS: Pretreatment samples from 135 patients receiving nivolumab were used to evaluate the predictive performance of CD8 tumor-infiltrating lymphocytes (TILs), intratumoral (IT) localization of CD8 TILs, PD-1 high expressing TILs (PD1T TILs), CD3 TILs, CD20 B-cells, tertiary lymphoid structures (TLS), PD-L1 tumor proportion score (TPS) and the Tumor Inflammation score (TIS). Patients were randomly assigned to a training (n = 55) and validation cohort (n = 80). The primary outcome measure was Disease Control at 6 months (DC 6m) and the secondary outcome measure was DC at 12 months (DC 12m). RESULTS: In the validation cohort, the two best performing composite biomarkers (i.e. CD8+IT-CD8 and CD3+IT-CD8) demonstrated similar or lower sensitivity (64% and 83%) and NPV (76% and 85%) compared to individual biomarkers PD-1T TILs and TIS (sensitivity: 72% and 83%, NPV: 86% and 84%) for DC 6m, respectively. Additionally, at 12 months, both selected composite biomarkers (CD8+IT-CD8 and CD8+TIS) demonstrated inferior predictive performance compared to PD-1T TILs and TIS alone. PD-1T TILs and TIS showed high sensitivity (86% and 100%) and NPV (95% and 100%) for DC 12m. PD-1T TILs could more accurately discriminate patients with no long-term benefit, as specificity was substantially higher compared to TIS (74% versus 39%). CONCLUSION: Composite biomarkers did not show improved predictive performance compared to PD-1T TILs and TIS alone for both the 6- and 12-month endpoints. PD-1T TILs and TIS identified patients with DC 12m with high sensitivity. Patients with no long-term benefit to PD-1 blockade were most accurately identified by PD-1T TILs.

Proactive monitoring of drug-drug interactions between direct oral anticoagulants and small-molecule inhibitors in patients with non-small cell lung cancer.

BACKGROUND: Small-molecule inhibitors (SMIs) have revolutionised the treatment of non-small cell lung cancer (NSCLC). However, SMI-induced drug-drug interactions (DDIs) with frequently co-administered direct oral anticoagulants (DOACs), increase thromboembolic and bleeding risks. This study investigated and proactively managed the consequences of DOAC-SMI DDIs. METHODS: This prospective, observational study enrolled patients with NSCLC concomitantly using a DOAC and SMI. The primary outcome was the proportion of patients with DOAC plasma trough (Ctrough) and peak (Cpeak) concentrations outside expected ranges. Secondary outcomes included DOAC treatment modifications, incidence of bleeding and thromboembolic events and feasibility evaluation of pharmacokinetically guided DOAC dosing. RESULTS: Thirty-three patients were analysed. Thirty-nine percent (13/33) had DOAC Ctrough and/or Cpeak were outside the expected ranges in 39% (13/33). In 71% (5/7) of patients with DOAC concentrations quantified before and during concurrent SMI use, DOAC Ctrough and/or Cpeak increased or decreased >50% upon SMI initiation. In all patients in whom treatment modifications were deemed necessary, DOAC concentrations were adjusted to within the expected ranges. CONCLUSION: Proactive monitoring showed that a substantial proportion of patients had DOAC concentrations outside the expected ranges. DOAC concentrations were successfully normalised after treatment modifications. These results highlight the importance of proactive monitoring of DOAC-SMI DDIs to improve treatment in patients with NSCLC.

Model-Informed Development of a Cost-Saving Dosing Regimen for Sacituzumab Govitecan.

BACKGROUND: The antibody-drug conjugate sacituzumab govitecan is approved for metastatic triple-negative breast cancer and has shown promising results in various other types of cancer. Its costs may limit patient access to this novel effective treatment modality. OBJECTIVE: The purpose of this study was to develop an evidence-based rational dosing regimen that results in targeted drug exposure within the therapeutic range while minimizing financial toxicity, to improve treatment access. PATIENTS AND METHODS: Exposure equivalent dosing strategies were developed based on pharmacokinetic modeling and simulation by using the published pharmacokinetic model developed by the license holder. The alternative dose was based on the principle of using complete vials to prevent spillage and on the established non-linear relationship between body weight and systemic exposure. Equivalent exposure compared to the approved dosing regimen of 10 mg/kg was aimed for. Equivalent exposure was conservatively defined as calculated geometric mean ratios within the 0.9-1.11 boundaries for area under the concentration-time curve (AUC), trough concentration (Ctrough) and maximum concentration (Cmax) of the alternative dosing regimen compared to the approved dosing regimen. Since different vial sizes are available for the European Union (EU) and United States (US) market, because body weight distributions differ between these populations, we performed our analysis for both scenarios. RESULTS: Dosing regimens of sacituzumab govitecan for the EU (< 50 kg: 400 mg, 50-80 kg: 600 mg, and > 80 kg: 800 mg) and US population (< 40 kg: 360 mg, 40-65 kg: 540 mg, 65-90 kg: 720 mg, and > 90 kg: 900 mg) were developed, based on weight bands. The geometric mean ratios for all pharmacokinetic outcomes were within the predefined equivalence boundaries, while the quantity of drug used was 21.5% and 19.0% lower for the EU and US scenarios, respectively. CONCLUSIONS: With the alternative dosing proposal, an approximately 20% reduction in drug expenses for sacituzumab govitecan can be realized while maintaining an equivalent and more evenly distributed exposure throughout the body weight range, without notable increases in pharmacokinetic variability.

Comparing modeling strategies combining changes in multiple serum tumor biomarkers for early prediction of immunotherapy non-response in non-small cell lung cancer.

BACKGROUND: Patients treated with immune checkpoint inhibitors (ICI) are at risk of adverse events (AEs) even though not all patients will benefit. Serum tumor markers (STMs) are known to reflect tumor activity and might therefore be useful to predict response, guide treatment decisions and thereby prevent AEs. OBJECTIVE: This study aims to compare a range of prediction methods to predict non-response using multiple sequentially measured STMs. METHODS: Nine prediction models were compared to predict treatment non-response at 6-months (n = 412) using bi-weekly CYFRA, CEA, CA-125, NSE, and SCC measurements determined in the first 6-weeks of therapy. All methods were applied to six different biomarker combinations including two to five STMs. Model performance was assessed based on sensitivity, while model training aimed at 95% specificity to ensure a low false-positive rate. RESULTS: In the validation cohort, boosting provided the highest sensitivity at a fixed specificity across most STM combinations (12.9% -59.4%). Boosting applied to CYFRA and CEA achieved the highest sensitivity on the validation data while maintaining a specificity >95%. CONCLUSIONS: Non-response in NSCLC patients treated with ICIs can be predicted with a specificity >95% by combining multiple sequentially measured STMs in a prediction model. Clinical use is subject to further external validation.

Detection of dendritic cell subsets in the tumor microenvironment by multiplex immunohistochemistry.

Dendritic cells (DCs) are essential in antitumor immunity. In humans, three main DC subsets are defined: two types of conventional DCs (cDC1s and cDC2s) and plasmacytoid DCs (pDCs). To study DC subsets in the tumor microenvironment (TME), it is important to correctly identify them in tumor tissues. Tumor-derived DCs are often analyzed in cell suspensions in which spatial information about DCs which can be important to determine their function within the TME is lost. Therefore, we developed the first standardized and optimized multiplex immunohistochemistry panel, simultaneously detecting cDC1s, cDC2s, and pDCs within their tissue context. We report on this panel's development, validation, and quantitative analysis. A multiplex immunohistochemistry panel consisting of CD1c, CD303, X-C motif chemokine receptor 1, CD14, CD19, a tumor marker, and DAPI was established. The ImmuNet machine learning pipeline was trained for the detection of DC subsets. The performance of ImmuNet was compared with conventional cell phenotyping software. Ultimately, frequencies of DC subsets within several tumors were defined. In conclusion, this panel provides a method to study cDC1s, cDC2s, and pDCs in the spatial context of the TME, which supports unraveling their specific roles in antitumor immunity.

A Dysfunctional T-cell Gene Signature for Predicting Nonresponse to PD-1 Blockade in Non-small Cell Lung Cancer That Is Suitable for Routine Clinical Diagnostics.

PURPOSE: Because PD-1 blockade is only effective in a minority of patients with advanced-stage non-small cell lung cancer (NSCLC), biomarkers are needed to guide treatment decisions. Tumor infiltration by PD-1T tumor-infiltrating lymphocytes (TIL), a dysfunctional TIL pool with tumor-reactive capacity, can be detected by digital quantitative IHC and has been established as a novel predictive biomarker in NSCLC. To facilitate translation of this biomarker to the clinic, we aimed to develop a robust RNA signature reflecting a tumor's PD-1T TIL status. EXPERIMENTAL DESIGN: mRNA expression analysis using the NanoString nCounter platform was performed in baseline tumor samples from 41 patients with advanced-stage NSCLC treated with nivolumab that were selected on the basis of PD-1T TIL infiltration by IHC. Samples were included as a training cohort (n = 41) to develop a predictive gene signature. This signature was independently validated in a second cohort (n = 42). Primary outcome was disease control at 12 months (DC 12 m), and secondary outcome was progression-free and overall survival. RESULTS: Regularized regression analysis yielded a signature using 12 out of 56 differentially expressed genes between PD-1T IHC-high tumors from patients with DC 12 m and PD-1T IHC-low tumors from patients with progressive disease (PD). In the validation cohort, 6/6 (100%) patients with DC 12 m and 23/36 (64%) with PD were correctly classified with a negative predictive value (NPV) of 100% and a positive predictive value of 32%. CONCLUSIONS: The PD-1T mRNA signature showed a similar high sensitivity and high NPV as the digital IHC quantification of PD-1T TIL. This finding provides a straightforward approach allowing for easy implementation in a routine diagnostic clinical setting.

Pre-analytical stability of the CEA, CYFRA 21.1, NSE, CA125 and HE4 tumor markers.

BACKGROUND: For lung cancer, circulating tumor markers (TM) are available to guide clinical treatment decisions. To ensure adequate accuracy, pre-analytical instabilities need to be known and addressed in the pre-analytical laboratory protocols. OBJECTIVE: This study investigates the pre-analytical stability of CA125, CEA, CYFRA 21.1, HE4 and NSE for the following pre-analytical variables and procedures; i) whole blood stability, ii) serum freeze-thaw cycles, iii) electric vibration mixing and iv) serum storage at different temperatures. METHODS: Left-over patient samples were used and for every investigated variable six patient samples were used and analysed in duplicate. Acceptance criteria were based on analytical performance specifications based on biological variation and significant differences with baseline. RESULTS: Whole blood was stable for at least 6 hours for all TM except for NSE. Two freeze-thaw cycles were acceptable for all TM except CYFRA 21.1. Electric vibration mixing was allowed for all TM except for CYFRA 21.1. Serum stability at 4°C was 7 days for CEA, CA125, CYFRA 21.1 and HE4 and 4 hours for NSE. CONCLUSIONS: Critical pre-analytical processing step conditions were identified that, if not taken into account, will result in reporting of erroneous TM results.

Clinical perspectives on serum tumor marker use in predicting prognosis and treatment response in advanced non-small cell lung cancer.

The optimal positioning and usage of serum tumor markers (STMs) in advanced non-small cell lung cancer (NSCLC) care is still unclear. This review aimed to provide an overview of the potential use and value of STMs in routine advanced NSCLC care for the prediction of prognosis and treatment response. Radiological imaging and clinical symptoms have shown not to capture a patient's entire disease status in daily clinical practice. Since STM measurements allow for a rapid, minimally invasive, and safe evaluation of the patient's tumor status in real time, STMs can be used as companion decision-making support tools before start and during treatment. To overcome the limited sensitivity and specificity associated with the use of STMs, tests should only be applied in specific subgroups of patients and different test characteristics should be defined per clinical context in order to answer different clinical questions. The same approach can similarly be relevant when developing clinical applications for other (circulating) biomarkers. Future research should focus on the approaches described in this review to achieve STM test implementation in advanced NSCLC care.

Blood platelet RNA profiles do not enable for nivolumab response prediction at baseline in patients with non-small cell lung cancer.

BACKGROUND: Anti-PD-(L)1 immunotherapy has emerged as a promising treatment approach for non-small cell lung cancer (NSCLC), though the response rates remain low. Pre-treatment response prediction may improve patient allocation for immunotherapy. Blood platelets act as active immune-like cells, thereby constraining T-cell activity, propagating cancer metastasis, and adjusting their spliced mRNA content. OBJECTIVE: We investigated whether platelet RNA profiles before start of nivolumab anti-PD1 immunotherapy may predict treatment responses. METHODS: We performed RNA-sequencing of platelet RNA samples isolated from stage III-IV NSCLC patients before treatment with nivolumab. Treatment response was scored by the RECIST-criteria. Data were analyzed using a predefined thromboSeq analysis including a particle-swarm-enhanced support vector machine (PSO/SVM) classification algorithm. RESULTS: We collected and processed a 286-samples cohort, separated into a training/evaluation and validation series and subjected those to training of the PSO/SVM-classification algorithm. We observed only low classification accuracy in the 107-samples validation series (area under the curve (AUC) training series: 0.73 (95% -CI: 0.63-0.84, n = 88 samples), AUC evaluation series: 0.64 (95% -CI: 0.51-0.76, n = 91 samples), AUC validation series: 0.58 (95% -CI: 0.45-0.70, n = 107 samples)), employing a five-RNAs biomarker panel. CONCLUSIONS: We concluded that platelet RNA may have minimally discriminative capacity for anti-PD1 nivolumab response prediction, with which the current methodology is insufficient for diagnostic application.

Cerebrospinal Fluid Concentration of the RET Inhibitor Pralsetinib: A Case Report.

Introduction: Pralsetinib is used to treat metastatic RET fusion-positive non-small cell lung cancer. Preclinical studies of pralsetinib have shown blood-brain barrier (BBB) penetration and intracranial activity. The intracranial efficacy of pralsetinib in patients with brain metastasis is considered to be greater compared to older multikinase tyrosine kinase inhibitors. However, CSF concentrations of pralsetinib in patients are not well described in the literature. Case Presentation: We report a case of a patient with RET fusion-positive NSCLC treated with pralsetinib. Despite extracranial clinical and radiological remission, the patient developed progressive brain metastasis during treatment with pralsetinib. We measured the pralsetinib concentration in plasma and in CSF to determine the CSF-to-unbound plasma ratio. The measured pralsetinib concentrations in plasma and CSF were 1,951 ng/mL (∼57 unbound) and 14 ng/mL, respectively, reflecting a CSF-to-unbound plasma concentration ratio of 0.25. Our findings were compared with data from the literature. Conclusion: We showed that pralsetinib penetrates the CSF well and is expected to be an effective treatment for brain metastasis of RET fusion-positive NSCLC. Lack of intracranial efficacy is more likely to be caused by intrinsic or acquired tumor resistance instead of suboptimal exposure of pralsetinib in the brain.

Integrating treatment cost reduction strategies and biomarker research to reduce costs and personalize expensive treatments: an example of a self-funding trial in non-small cell lung cancer.

Personalization of treatment offers the opportunity to treat patients more effectively based on their dominant disease-specific features. The increasing number and types of treatment, and the high costs associated with these treatments, however, demand new approaches that improve patient selection while reducing treatment-associated costs to ensure sustainable healthcare. The DEDICATION-1 trial has been designed to investigate the non-inferiority of lower dosing regimens when compared to standard of care dosing regimens as a potential effective treatment cost reduction strategy to reduce costs of treatment with expensive immune checkpoint inhibitors in non-small cell lung cancer. If non-inferiority is confirmed, lower dosing regimens could be implemented for all therapeutic indications of pembrolizumab. The cost savings obtained within the trial are partly reinvested in biomarker research to improve the personalization of pembrolizumab treatment. The implementation of these biomarkers will potentially lead to additional cost savings by preventing ineffective pembrolizumab exposure, thereby further reducing the financial pressure on healthcare systems. The concepts discussed within this perspective can be applied both to other anticancer agents, as well as to treatments prescribed outside the oncology field.

Impact of time-to-treatment on survival for early-stage non-small cell lung cancer in The Netherlands-a nationwide observational cohort study.

Background: Varied outcomes on the relation between time-to-treatment and survival in early-stage non-small cell lung cancer (NSCLC) patients are reported. We examined this relation in a large multicentric retrospective cohort study and identified factors associated with extended time-to-treatment. Methods: We included 9,536 patients with clinical stage I-II NSCLC, diagnosed and treated in 2014-2019, from the Netherlands Cancer Registry that includes nation-wide data. Time-to-treatment was defined as the number of days between first outpatient visit for suspected lung cancer and start of treatment. The effect of extended time-to-treatment beyond the first quartile and survival was studied with Cox proportional hazard regression. Analyses were stratified for stage and type of therapy. Time-to-treatment was adjusted for multiple covariates including performance status and socioeconomic status. Factors associated with treatment delay were identified by multilevel logistic regression. Results: Median time-to-treatment was 47 days [interquartile range (IQR): 34-65] for stage I and 46 days (IQR: 34-62) for stage II. The first quartile extended to 33 days for both stages. Risk of death increased significantly with extended time-to-treatment for surgical treatment of clinical stage II patients [adjusted hazard ratio (aHR) >33 days: 1.36, 95% confidence intervals (CI): 1.09-1.70], but not in stage II patients treated with radiotherapy or in stage I patients. Causes of prolonged time-to-treatment were multifactorial including diagnostic tests, such as endoscopic ultrasound (EUS) or endobronchial ultrasound (EBUS). Conclusions: Clinical stage II patients benefit from fast initiation of surgical treatment. Surprisingly this appears to be accounted for by patients who are clinically stage II but pathologically stage I. Further study is needed on characterizing these patients and the significance of lymph node- or distant micrometastasis in guiding time-to-treatment and treatment strategy.

Prognostic Value of Nivolumab Clearance in Non-Small Cell Lung Cancer Patients for Survival Early in Treatment.

INTRODUCTION: Immune checkpoint inhibitors improved survival of advanced stage non-small cell lung cancer patients, but the overall response rate remains low. A biomarker that identifies non-responders would be helpful to allow treatment decisions. Clearance of immune checkpoint inhibitors is related to treatment response, but its prognostic potential early in treatment remains unknown. Our primary aim was to investigate the prognostic potential of nivolumab clearance for overall survival early in treatment. Our secondary aim was to evaluate the performance of nivolumab clearance as prognostic biomarker. PATIENTS AND METHODS: Individual estimates of nivolumab clearances at first dose, 6 and 12 weeks after treatment initiation were obtained via nonlinear mixed-effects modelling. Prognostic value of nivolumab clearance was estimated using univariate Cox regression at first dose and for the ratios between 6 and 12 weeks to first dose. The performance of nivolumab clearance as biomarker was assessed by calculating sensitivity and specificity. RESULTS: During follow-up of 75 months, 69 patients were included and 865 died. Patients with a nivolumab clearance ≥ 7.3 mL/h at first dose were more likely to die compared to patients with a nivolumab clearance < 7.3 mL/h at first dose (hazard ratio [HR] = 3.55, 955 CI 1.75-7.20). The HRs of dose nivolumab clearance ratios showed similar results with a HR of 3.93 (955 CI 1.66-9.32) for 6 weeks to first-dose clearance ratio at a 0.953 cut-point and a HR of 2.96 (955 CI 1.32-6.64) for 12 weeks to first-dose clearance ratio at a cut-point of 0.814. For nivolumab clearance at all early time points, sensitivity was high (≥ 0.95) but specificity was low (0.11-0.29). CONCLUSION: Nivolumab clearance is indicative of survival early in treatment. Our results encourage to further assess the prognostic potential of immunotherapy clearance.

Prospective Detection of Early Lung Cancer in Patients With COPD in Regular Care by Electronic Nose Analysis of Exhaled Breath.

BACKGROUND: Patients with COPD are at high risk of lung cancer developing, but no validated predictive biomarkers have been reported to identify these patients. Molecular profiling of exhaled breath by electronic nose (eNose) technology may qualify for early detection of lung cancer in patients with COPD. RESEARCH QUESTION: Can eNose technology be used for prospective detection of early lung cancer in patients with COPD? STUDY DESIGN AND METHODS: BreathCloud is a real-world multicenter prospective follow-up study using diagnostic and monitoring visits in day-to-day clinical care of patients with a standardized diagnosis of asthma, COPD, or lung cancer. Breath profiles were collected at inclusion in duplicate by a metal-oxide semiconductor eNose positioned at the rear end of a pneumotachograph (SpiroNose; Breathomix). All patients with COPD were managed according to standard clinical care, and the incidence of clinically diagnosed lung cancer was prospectively monitored for 2 years. Data analysis involved advanced signal processing, ambient air correction, and statistics based on principal component (PC) analysis, linear discriminant analysis, and receiver operating characteristic analysis. RESULTS: Exhaled breath data from 682 patients with COPD and 211 patients with lung cancer were available. Thirty-seven patients with COPD (5.4%) demonstrated clinically manifest lung cancer within 2 years after inclusion. Principal components 1, 2, and 3 were significantly different between patients with COPD and those with lung cancer in both training and validation sets with areas under the receiver operating characteristic curve of 0.89 (95% CI, 0.83-0.95) and 0.86 (95% CI, 0.81-0.89). The same three PCs showed significant differences (P < .01) at baseline between patients with COPD who did and did not subsequently demonstrate lung cancer within 2 years, with a cross-validation value of 87% and an area under the receiver operating characteristic curve of 0.90 (95% CI, 0.84-0.95). INTERPRETATION: Exhaled breath analysis by eNose identified patients with COPD in whom lung cancer became clinically manifest within 2 years after inclusion. These results show that eNose assessment may detect early stages of lung cancer in patients with COPD.

A Systematic Evaluation of Cost-Saving Dosing Regimens for Therapeutic Antibodies and Antibody-Drug Conjugates for the Treatment of Lung Cancer.

BACKGROUND: Expensive novel anticancer drugs put a serious strain on healthcare budgets, and the associated drug expenses limit access to life-saving treatments worldwide. OBJECTIVE: We aimed to develop alternative dosing regimens to reduce drug expenses. METHODS: We developed alternative dosing regimens for the following monoclonal antibodies used for the treatment of lung cancer: amivantamab, atezolizumab, bevacizumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, and ramucirumab; and for the antibody-drug conjugate trastuzumab deruxtecan. The alternative dosing regimens were developed by means of modeling and simulation based on the population pharmacokinetic models developed by the license holders. They were based on weight bands and the administration of complete vials to limit drug wastage. The resulting dosing regimens were developed to comply with criteria used by regulatory authorities for in silico dose development. RESULTS: We found that alternative dosing regimens could result in cost savings that range from 11 to 28%, and lead to equivalent pharmacokinetic exposure with no relevant increases in variability in exposure. CONCLUSIONS: Dosing regimens based on weight bands and the use of complete vials to reduce drug wastage result in less expenses while maintaining equivalent exposure. The level of evidence of our proposal is the same as accepted by regulatory authorities for the approval of alternative dosing regimens of other monoclonal antibodies in oncology. The proposed alternative dosing regimens can, therefore, be directly implemented in clinical practice.

Therapeutic drug monitoring guided dosing versus standard dosing of alectinib in advanced ALK positive non-small cell lung cancer patients: Study protocol for an international, multicenter phase IV randomized controlled trial (ADAPT ALEC).

Background: Alectinib is first-line therapy in patients with stage IV non-small cell lung carcinoma (NSCLC) and an anaplastic lymphoma kinase (ALK) fusion. A shorter median progression-free survival (mPFS) was observed when alectinib minimum plasma concentrations during steady state (Cmin,SS) were below 435 ng/mL. This may suggest that patients should have an alectinib Cmin,SS ≥ 435 ng/mL for a more favorable outcome. This potential target could be attained by using therapeutic drug monitoring (TDM), i.e. adjusting the dose based on measured plasma trough concentrations. Hypothetically, this will increase mPFS, but this has not yet been evaluated in a randomized controlled trial (RCT). Therefore, the ADAPT ALEC trial is designed, with the primary objective to prolong mPFS in NSCLC patients treated with alectinib by using TDM. Methods: ADAPT ALEC is a multicenter, phase IV RCT, in which patients aged ≥ 18 years with advanced ALK positive (+) NSCLC eligible for alectinib in daily care are enrolled. Participants will be randomized (1:1 ratio) into intervention arm A (TDM) or B (control), stratified by brain metastases and prior ALK treatments. Starting dose in both arms is the approved flat fixed dose of alectinib 600 mg taken twice daily with food. In case of alectinib Cmin,SS < 435 ng/mL, arm A will receive increased doses of alectinib till Cmin,SS ≥ 435 ng/mL when considered tolerable. The primary outcome is mPFS, where progressive disease is defined according to RECIST v1.1 or all-cause death and assessed by CT-scans and MRI brain. Secondary endpoints are feasibility and tolerability of TDM, patient and physician adherence, overall response rate, median overall survival, intracranial PFS, quality of life, toxicity, alectinib-M4 concentrations and cost-effectiveness of TDM. Exploratory endpoints are circulating tumor DNA and body composition. Discussion: The ADAPT ALEC will show whether treatment outcomes of patients with advanced ALK+ NSCLC improve when using TDM-guided dosing of alectinib instead of fixed dosing. The results will provide high quality evidence for deciding whether TDM should be implemented as standard of care and this will have important consequences for the prescribing of alectinib. Clinical trial registration: ClinicalTrials.gov, identifier NCT05525338.

Feasibility of an Individualized Dispensing Program for Patients Prescribed Oral Anticancer Drugs to Prevent Waste.

PURPOSE: Waste of oral anticancer drugs (OACDs) causes financial and environmental burdens. This study evaluates the feasibility of an individualized dispensing program to prevent waste of OACDs. METHODS: Adult patients were dispensed individualized quantities of niraparib, abiraterone, enzalutamide, ruxolitinib, osimertinib, or imatinib as standard care, during the first 6 months of treatment. The first 50 patients participated in an feasibility evaluation conform five domains of Bowen's Framework. (1) implementation: reach (eligible patients included) and protocol fidelity (executions following protocol) assessed from pharmacy data, (2) acceptability: rated from 1 to 10 and agreement with theoretical framework acceptability domains via a survey among patients and pharmacy technicians, (3) practicality: program's costs, (4) effect: compared with previous practice (full package supply per month), defined as difference in unused OACD unit doses and net cost-savings, and (5) demand: potential scale-up of the program by including more OACDs. RESULTS: Participants' median age was 67 (interquartile range [IQR], 58-71) years, and 76% was male. (1) Implementation: reach and protocol fidelity were 89% and 90%, respectively. (2) Acceptability was high among patients (median, 9; IQR, 8-9) and pharmacy technicians (median, 7; IQR, 6-8). All acceptability domains were agreed on. (3) Practicality: program costs were €4,289. (4) Effect: unused OACD unit doses were reduced by 34%, causing net cost-savings of €693 per discontinued patient. (5) Demand: the program could be scaled up to seven times by including all OACDs. CONCLUSION: Individualized dispensing for patients prescribed OACDs is feasible for preventing waste in terms of implementation, acceptability, practicality, effect, and demand.

Renal function-based versus standard dosing of pemetrexed: a randomized controlled trial.

PURPOSE: Pemetrexed is a chemotherapeutic drug in the treatment of non-small cell lung cancer and mesothelioma. Optimized dosing of pemetrexed based on renal function instead of body surface area (BSA) is hypothesized to reduce pharmacokinetic variability in systemic exposure and could therefore improve treatment outcomes. The aim of this study is to compare optimized dosing to standard BSA-based dosing. METHODS: A multicenter randomized (1:1) controlled trial was performed to assess superiority of optimized dosing versus BSA-based dosing in patients who were eligible for pemetrexed-based chemotherapy. The individual exposure to pemetrexed in terms of area under the concentration-time curve (AUC) was determined. The fraction of patients attaining to a predefined typical target AUC (164 mg × h/L ± 25%) was calculated. RESULTS: A total of 81 patients were included. Target attainment was not statistically significant different between both arms (89% vs. 84% (p = 0.505)). The AUC of pemetrexed was similar between the optimized dosing arm (n = 37) and the standard of care arm (n = 44) (155 mg × h/L vs 160 mg × h/L (p = 0.436). CONCLUSION: We could not show superiority of optimized dosing of pemetrexed in patients with an adequate renal function does not show added value on the attainment of a pharmacokinetic endpoint, safety, nor QoL compared to standard of care dosing. CLINICAL TRIAL NUMBER: Clinicaltrials.gov identifier: NCT03655821.