Trends in the epidemiology of small-cell lung cancer:a Dutch nationwide population-based study over 1989–2020

Introduction: This study describes the evolving characteristics of patients with small-cell lung cancer (SCLC) from 1989 to 2020 in the Netherlands to analyse how the population of patients with SCLC has changed in the last decades, hypothesising that this might explain the little progress made in SCLC. Methods: Patients with SCLC diagnosed from 1989 to 2020 were selected from the Dutch cancer registry. Incidence, patient and disease characteristics, treatments, and overall survival (OS) were analysed. Joinpoint analyses were used to test annual percentage changes for statistical significance. Results: A total of 52,527 patients were diagnosed with SCLC. The absolute numbers of patients with SCLC remained equal over the years; however, the incidence rates decreased from 15.01 to 8.93 per 100,000 person-years. The proportion of women increased from 22% to 50%, and those aged ≥75 years increased from 20% to 25%. The latter coincided with a higher proportion receiving only the best supportive care (BSC) over the years (18–24%). The use of surgery in stage I increased from 2% to 37%. The proportion of patients diagnosed with stage IV increased from 46% to 70% due to better staging. The OS improved for all stages, with a 2-year OS rate for stage IV doubling from 3% to 6%.Conclusion: The incidence of SCLC has significantly decreased over the last 30 years, with an increasing proportion of elderly and women. The male–female ratio became similar, and the OS improved. As a consequence of more elderly and probably more vulnerable patients, more patients received only the BSC.</p

Non-small cell lung cancer with a single metastasis, the new stage M1b; does the site matter?

Non-small cell lung cancer (NSCLC) patients with a solitary metastasis are considered to have a more favourable prognosis compared to those with multiple metastases. This is also shown in the 8th tumor, node, metastases edition for lung cancer (TNM8): patients with M1b (single extrapulmonary metastasis) have a superior prognosis than those with M1c disease (multiple metastases). Although not described in the TNM8, site of single metastatic disease may reflect tumour biology and may be of important prognostic value. We report a case of a patient with squamous cell NSCLC and a single skeletal muscle metastasis with a remarkably aggressive disease course

Immunotherapy in small cell lung cancer:One step at a time: A narrative review

Chemotherapy with or without radiotherapy has been the standard of care for many years for patients with small cell lung cancer (SCLC). Despite exceptionally high responses (up to 80%) with chemotherapy, the majority of patients relapse rapidly within weeks to months after treatment completion. Therefore, new and better treatment options are necessary. Recently, synergistic activity has been reported for the addition of immune checkpoint inhibitors (ICI) to standard platinum-based chemotherapy in the therapeutic strategy of advanced SCLC. For the first time after several decades, a significant survival improvement was achieved for this population. However, the overwhelming majority of patients do not respond to ICI, or relapse rapidly. There is need for better knowledge about the biology, histopathologic features, and molecular pathways of SCLC. This can probably help to identify the optimal predictive biomarkers, which are warranted to develop an individual therapeutic strategy including the rational use of a combination of immunotherapeutic agents. Here, we provide an overview of the rationale for and clinical results of the completed and ongoing trials using different strategies of immunotherapy in SCLC. In addition, opportunities for further improvement of therapies will be discussed, including the addition of radiotherapy, co-stimulatory antibodies, and other immune modifying agents.</p

In-depth Analysis of Lorlatinib-related neurocognitive Adverse Events in Patients With Non–small-cell Lung Cancer

Introduction: Lorlatinib is a potent, brain penetrant, next-generation ALK/ROS1 TKI, with high response rates and durable responses, including the brain. However, a significant drawback is the manifestation of neurocognitive adverse events (NCAEs). Despite being generally low-grade in severity, these NCAEs can be physically and mentally disabling. Extensive neurocognitive testing in this group of patients is lacking; therefore we conducted this study. Patients and methods: This observational prospective study was conducted across 3 Dutch university hospitals. Patients with metastatic NSCLC with an ALK- or ROS1-rearrangement and having an indication to start lorlatinib in daily clinical practice were eligible. The primary endpoints were to identify changes in neurocognitive functioning, measured through neurocognitive assessment at intervals of 2 weeks and 2 months after starting lorlatinib, in comparison to baseline. As a secondary endpoint, the correlation between neurocognitive impairment and self-reported neurocognitive dysfunction was examined. Results: Between June 2019 and October 2022, 22 patients were included. Among the various neurocognitive tests administered, only the Hopkins Verbal Learning Test-Revised parts b and c demonstrated a significant and clinically relevant decrease in scoring 2 weeks post initiation of lorlatinib (P = .036 and P = .003, respectively). However, these returned to baseline at the 2-month evaluation. The questionnaires did not result in significantly different outcomes over time.Conclusion: Lorlatinib treatment did not result in a sustained and significant decline within any of the specified neurocognitive domains.</p

Management of stage I and II nonsmall cell lung cancer

The incidence of stage I and II nonsmall cell lung cancer is likely to increase with the ageing population and introduction of screening for high-risk individuals. Optimal management requires multidisciplinary collaboration. Local treatments include surgery and radiotherapy and these are currently combined with (neo)adjuvant chemotherapy in specific cases to improve long-term outcome. Targeted therapies and immunotherapy may also become important therapeutic modalities in this patient group. For resectable disease in patients with low cardiopulmonary risk, complete surgical resection with lobectomy remains the gold standard. Minimally invasive techniques, conservative and sublobar resections are suitable for a subset of patients. Data are emerging that radiotherapy, especially stereotactic body radiation therapy, is a valid alternative in compromised patients who are high-risk candidates for surgery. Whether this is also true for good surgical candidates remains to be evaluated in randomised trials. In specific subgroups adjuvant chemotherapy has been shown to prolong survival; however, patient selection remains important. Neoadjuvant chemotherapy may yield similar results as adjuvant chemotherapy. The role of targeted therapies and immunotherapy in early stage nonsmall cell lung cancer has not yet been determined and results of randomised trials are awaited

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&amp;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.</p

Integrin expression profiling identifies integrin alpha5 and beta1 as prognostic factors in early stage non-small cell lung cancer

<p>Abstract</p> <p>Background</p> <p>Selection of early stage non-small cell lung cancer patients with a high risk of recurrence is warranted in order to select patients who will benefit from adjuvant treatment strategies. We evaluated the prognostic value of integrin expression profiles in a retrospective study on frozen primary tumors of 68 patients with early stage non-small cell lung cancer.</p> <p>Methods</p> <p>A retrospective study was performed on frozen primary tumors of 68 early stage non-small cell lung cancer patients with a follow up of at least 10 years. From all tumor tissues, RNA was isolated and reverse transcribed into cDNA. qPCR was used to generate mRNA expression profiles including integrins alpha1, 2, 3, 4, 5, 6, 7, 11, and V as well as integrins beta1, 3, 4, 5, 6, and 8.</p> <p>Results</p> <p>The expression levels of integrins alpha5, beta1 and beta3 predicted overall survival and disease free survival in early stage NSCLC patients. There was no association between integrin expression and lymph node metastases. Comparison between the histological subtypes revealed a distinct integrin signature for squamous cell carcinoma while the profiles of adenocarcinoma and large cell carcinoma were largely the same.</p> <p>Conclusion</p> <p>Integrin expression in NSCLC is important for the development and behavior of the tumor and influences the survival of the patient. Determining the integrin expression profile might serve as a tool in predicting the prognosis of individual patients.</p