Validation of a clinical blood-based decision aid to guide immunotherapy treatment in patients with non-small cell lung cancer

Can blood-based markers predict RECIST progression in non-small cell lung cancer treated with immunotherapy?

PURPOSE

In this study, we aimed to evaluate the potential of routine blood markers, serum tumour markers and their combination in predicting RECIST-defined progression in patients with stage IV non-small cell lung cancer (NSCLC) undergoing treatment with immune checkpoint inhibitors.

METHODS

We employed time-varying statistical models and machine learning classifiers in a Monte Carlo cross-validation approach to investigate the association between RECIST-defined progression and blood markers, serum tumour markers and their combination, in a retrospective cohort of 164 patients with NSCLC.

RESULTS

The performance of the routine blood markers in the prediction of progression free survival was moderate. Serum tumour markers and their combination with routine blood markers generally improved performance compared to routine blood markers alone. Elevated levels of C-reactive protein (CRP) and alkaline phosphatase (ALP) ranked as the top predictive routine blood markers, and CYFRA 21.1 was consistently among the most predictive serum tumour markers. Using these classifiers to predict overall survival yielded moderate to high performance, even when cases of death-defined progression were excluded. Performance varied across the treatment journey.

CONCLUSION

Routine blood tests, especially when combined with serum tumour markers, show moderate predictive value  of RECIST-defined progression in NSCLC patients receiving immune checkpoint inhibitors. The relationship between overall survival and RECIST-defined progression may be influenced by confounding factors.

Investigating the Current Harmonization Status of Tumor Markers Using Global External Quality Assessment Programs: A Feasibility Study

BACKGROUND

The harmonization status of most tumor markers (TMs) is unknown. We report a feasibility study performed to determine whether external quality assessment (EQA) programs can be used to obtain insights into the current harmonization status of the tumor markers α-fetoprotein (AFP), prostate specific antigen (PSA), carcinoembryonic antigen (CEA), cancer antigen (CA)125, CA15-3 and CA19-9.

METHODS

EQA sample results provided by 6 EQA providers (INSTAND [Germany], Korean Association of External Quality Assessment Service [KEQAS, South Korea], National Center for Clinical Laboratories [NCCL, China], United Kingdom National External Quality Assessment Service [UK NEQAS, United Kingdom], Stichting Kwaliteitsbewaking Medische Laboratoriumdiagnostiek [SKML, the Netherlands], and the Royal College of Pathologists of Australasia Quality Assurance Programs [RCPAQAP, Australia]) between 2020 and 2021 were used. The consensus means, calculated from the measurement procedures present in all EQA programs (Abbott Alinity, Beckman Coulter DxI, Roche Cobas, and Siemens Atellica), was used as reference values. Per measurement procedure, the relative difference between consensus mean for each EQA sample and the mean of all patient-pool-based EQA samples were calculated and compared to minimum, desirable, and optimal allowable bias criteria based on biological variation.

RESULTS

Between 19040 (CA15-3) and 25398 (PSA) individual results and 56 (PSA) to 76 (AFP) unique EQA samples were included in the final analysis. The mean differences with the consensus mean of patient-pool-based EQA samples for all measurement procedures were within the optimum bias criterion for AFP, the desirable bias for PSA, and the minimum bias criterion for CEA. However, CEA results <8 µg/L exceeded the minimum bias criterion. For CA125, CA15-3, and CA19-9, the harmonization status was outside the minimum bias criterion, with systematic differences identified.

CONCLUSIONS

This study provides relevant information about the current harmonization status of 6 tumor markers. A pilot harmonization investigation for CEA, CA125, CA15-3, and CA19-9 would be desirable.

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.

Serum tumor markers for response prediction and monitoring of advanced lung cancer: A review focusing on immunotherapy and targeted therapies

BACKGROUND

The value of serum tumor markers (STMs) in the current therapeutic landscape of lung cancer is unclear.

OBJECTIVE

This scoping review gathered evidence of the predictive, prognostic, and monitoring value of STMs for patients with advanced lung cancer receiving immunotherapy (IT) or targeted therapy (TT).

METHODS

Literature searches were conducted (cut-off: May 2022) using PubMed and Cochrane CENTRAL databases. Medical professionals advised on the search strategies.

RESULTS

Study heterogeneity limited the evidence and inferences from the 36 publications reviewed. While increased baseline levels of serum cytokeratin 19 fragment antigen (CYFRA21-1) and carcinoembryonic antigen (CEA) may predict IT response, results for TT were less clear. For monitoring IT-treated patients, STM panels (including CYFRA21-1, CEA, and neuron-specific enolase) may surpass the power of single analyses to predict non-response. CYFRA21-1 measurement could aid in monitoring TT-treated patients, but the value of CEA in this context requires further investigation. Overall, baseline and dynamic changes in individual or combined STM levels have potential utility to predict treatment outcome and for monitoring of patients with advanced lung cancer.

CONCLUSIONS

In advanced lung cancer, STMs provide additional relevant clinical information by predicting treatment outcome, but further standardization and validation is warranted.

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.

Prognostic value of blood-based protein biomarkers in non-small cell lung cancer: A critical review and 2008-2022 update

BACKGROUND

Therapeutic possibilities for non-small cell lung cancer (NSCLC) have considerably increased during recent decades.

OBJECTIVE

To summarize the prognostic relevance of serum tumor markers (STM) for early and late-stage NSCLC patients treated with classical chemotherapies, novel targeted and immune therapies.

METHODS

A PubMed database search was conducted for prognostic studies on carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA 21-1), neuron-specific enolase, squamous-cell carcinoma antigen, progastrin-releasing-peptide, CA125, CA 19-9 and CA 15-3 STMs in NSCLC patients published from 2008 until June 2022.

RESULTS

Out of 1069 studies, 141 were identified as meeting the inclusion criteria. A considerable heterogeneity regarding design, patient number, analytical and statistical methods was observed. High pretherapeutic CYFRA 21-1 levels and insufficient decreases indicated unfavorable prognosis in many studies on NSCLC patients treated with chemo-, targeted and immunotherapies or their combinations in early and advanced stages. Similar results were seen for CEA in chemotherapy, however, high pretherapeutic levels were sometimes favorable in targeted therapies. CA125 is a promising prognostic marker in patients treated with immunotherapies. Combinations of STMs further increased the prognostic value over single markers.

CONCLUSION

Protein STMs, especially CYFRA 21-1, have prognostic potential in early and advanced stage NSCLC. For future STM investigations, better adherence to comparable study designs, analytical methods, outcome measures and statistical evaluation standards is recommended.

Lung cancer tumor marker analysis: A clinical laboratory perspective

 Clinical laboratories are responsible for performing lung cancer tumor marker testing as part of routine clinical care. It is their responsibility to guarantee that the reported tumor marker results are reliable and meet the necessary quality standards for proper clinical use. During the different laboratory phases, pre-analytical, analytical and post-analytical, specific steps and processes can introduce errors and generate incorrect clinical interpretation. This editorial briefly outlines critical laboratory issues related to lung cancer tumor markers, specific for each of these three laboratory phases.

Modeling strategies to analyse longitudinal biomarker data: An illustration on predicting immunotherapy non-response in non-small cell lung cancer

Serum tumor markers acquired through a blood draw are known to reflect tumor activity. Their non-invasive nature allows for more frequent testing compared to traditional imaging methods used for response evaluations. Our study aims to compare nine prediction methods to accurately, and with a low false positive rate, predict progressive disease despite treatment (i.e. non-response) using longitudinal tumor biomarker data. Bi-weekly measurements of CYFRA, CA-125, CEA, NSE, and SCC were available from a cohort of 412 advanced stage non-small cell lung cancer (NSCLC) patients treated up to two years with immune checkpoint inhibitors. Serum tumor marker measurements from the first six weeks after treatment initiation were used to predict treatment response at 6 months. Nine models with varying complexity were evaluated in this study, showing how longitudinal biomarker data can be used to predict non-response to immunotherapy in NSCLC patients.

Combinatorial Power of cfDNA, CTCs and EVs in Oncology

Liquid biopsy is a promising technique for clinical management of oncological patients. The diversity of analytes circulating in the blood useable for liquid biopsy testing is enormous. Circulating tumor cells (CTCs), cell-free DNA (cfDNA) and extracellular vesicles (EVs), as well as blood cells and other soluble components in the plasma, were shown as liquid biopsy analytes. A few studies directly comparing two liquid biopsy analytes showed a benefit of one analyte over the other, while most authors concluded the benefit of the additional analyte. Only three years ago, the first studies to examine the value of a characterization of more than two liquid biopsy analytes from the same sample were conducted. We attempt to reflect on the recent development of multimodal liquid biopsy testing in this review. Although the analytes and clinical purposes of the published multimodal studies differed significantly, the additive value of the analytes was concluded in almost all projects. Thus, the blood components, as liquid biopsy reservoirs, are complementary rather than competitive, and orthogonal data sets were even shown to harbor synergistic effects. The unmistakable potential of multimodal liquid biopsy testing, however, is dampened by its clinical utility, which is yet to be proven, the lack of methodical standardization and insufficiently mature reimbursement, logistics and data handling.