-
Frontiers in Oncology 2022Establishing risk-based follow-up management strategies is crucial to the surveillance of subsolid pulmonary nodules (SSNs). However, the risk factors for SSN growth are...
BACKGROUND
Establishing risk-based follow-up management strategies is crucial to the surveillance of subsolid pulmonary nodules (SSNs). However, the risk factors for SSN growth are not currently clear. This study aimed to perform a systematic review and meta-analysis to identify clinical and CT features correlated with SSN growth.
METHODS
Relevant studies were retrieved from Web of Science, PubMed, Cochrane Library, and EMBASE. The correlations of clinical and CT features with SSN growth were pooled using a random-effects model or fixed-effects model depending on heterogeneity, which was examined by the test and test. Pooled odds ratio (OR) or pooled standardized mean differences (SMD) based on univariate analyses were calculated to assess the correlation of clinical and CT features with SSN growth. Pooled ORs based on multivariate analyses were calculated to find out independent risk factors to SSN growth. Subgroup meta-analysis was performed based on nodule consistency (pure ground-glass nodule (pGGN) and part-solid nodule (PSN). Publication bias was examined using funnel plots.
RESULTS
Nineteen original studies were included, consisting of 2444 patients and 3012 SSNs. The median/mean follow-up duration of these studies ranged from 24.2 months to 112 months. Significant correlations were observed between SSN growth and eighteen features. Male sex, history of lung cancer, nodule size > 10 mm, nodule consistency, and age > 65 years were identified as independent risk factors for SSN growth based on multivariate analyses results. Eight features, including male sex, smoking history, nodule size > 10 mm, larger nodule size, air bronchogram, higher mean CT attenuation, well-defined border, and lobulated margin were detected to be significantly correlated with pGGNs growth. Smoking history showed no significant correlation with pGGN growth based on the multivariate analysis results.
CONCLUSIONS
Eighteen clinical and CT features were identified to be correlated with SSN growth, among which male sex, history of lung cancer, nodule size > 10 mm, nodule consistency and age > 65 years were independent risk factors while history of lung cancer was not correlated with pGGN growth. These factors should be considered when making risk-based follow-up plans for SSN patients.
PubMed: 35860567
DOI: 10.3389/fonc.2022.929174 -
Journal of Thoracic Disease Jun 2022Clinical decision-making for patients with stage I lung cancer is complex. It involves multiple options [lobectomy, segmentectomy, wedge, stereotactic body radiotherapy... (Review)
Review
A guide for managing patients with stage I NSCLC: deciding between lobectomy, segmentectomy, wedge, SBRT and ablation-part 3: systematic review of evidence regarding surgery in compromised patients or specific tumors.
BACKGROUND
Clinical decision-making for patients with stage I lung cancer is complex. It involves multiple options [lobectomy, segmentectomy, wedge, stereotactic body radiotherapy (SBRT), thermal ablation], weighing multiple outcomes (e.g., short-, intermediate-, long-term) and multiple aspects of each (e.g., magnitude of a difference, the degree of confidence in the evidence, and the applicability to the patient and setting at hand). A structure is needed to summarize the relevant evidence for an individual patient and to identify which outcomes have the greatest impact on the decision-making.
METHODS
A PubMed systematic review from 2000-2021 of outcomes after lobectomy, segmentectomy and wedge resection in older patients, patients with limited pulmonary reserve and favorable tumors is the focus of this paper. Evidence was abstracted from randomized trials and non-randomized comparisons (NRCs) with adjustment for confounders. The analysis involved careful assessment, including characteristics of patients, settings, residual confounding etc. to expose degrees of uncertainty and applicability to individual patients. Evidence is summarized that provides an at-a-glance overall impression as well as the ability to delve into layers of details of the patients, settings and treatments involved.
RESULTS
In older patients, perioperative mortality is minimally altered by resection extent and only slightly affected by increasing age; sublobar resection may slightly decrease morbidity. Long-term outcomes are worse after lesser resection; the difference is slightly attenuated with increasing age. Reported short-term outcomes are quite acceptable in (selected) patients with severely limited pulmonary reserve, not clearly altered by resection extent but substantially improved by a minimally invasive approach. Quality-of-life (QOL) and impact on pulmonary function hasn't been well studied, but there appears to be little difference by resection extent in older or compromised patients. Patient selection is paramount but not well defined. Ground-glass and screen-detected tumors exhibit favorable long-term outcomes regardless of resection extent; however solid tumors <1 cm are not a reliably favorable group.
CONCLUSIONS
A systematic, comprehensive summary of evidence regarding resection extent in compromised patients and favorable tumors with attention to aspects of applicability, uncertainty and effect modifiers provides a foundation for a framework for individualized decision-making.
PubMed: 35813753
DOI: 10.21037/jtd-21-1825 -
Diagnostics (Basel, Switzerland) May 2022Radiomics is an upcoming field in nuclear oncology, both promising and technically challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia... (Review)
Review
Radiomics is an upcoming field in nuclear oncology, both promising and technically challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia and assess its quality, we performed a literature search in the PubMed database up to 18 February 2022. Inclusion criteria were: studies based on human data; at least one specified tumor type; supradiaphragmatic malignancy; performing radiomics on PET imaging. Exclusion criteria were: studies only based on phantom or animal data; technical articles without a clinically oriented question; fewer than 30 patients in the training cohort. A review database containing PMID, year of publication, cancer type, and quality criteria (number of patients, retrospective or prospective nature, independent validation cohort) was constructed. A total of 220 studies met the inclusion criteria. Among them, 119 (54.1%) studies included more than 100 patients, 21 studies (9.5%) were based on prospectively acquired data, and 91 (41.4%) used an independent validation set. Most studies focused on prognostic and treatment response objectives. Because the textural parameters and methods employed are very different from one article to another, it is complicated to aggregate and compare articles. New contributions and radiomics guidelines tend to help improving quality of the reported studies over the years.
PubMed: 35741138
DOI: 10.3390/diagnostics12061329 -
Life (Basel, Switzerland) Mar 2022Lung cancer is the most common cancer type worldwide, with non-small cell lung cancer (NSCLC) being the most common subtype. Non-disseminated NSCLC is mainly treated... (Review)
Review
Lung cancer is the most common cancer type worldwide, with non-small cell lung cancer (NSCLC) being the most common subtype. Non-disseminated NSCLC is mainly treated with surgical resection. The intraoperative detection of lung cancer can be challenging, since small and deeply located pulmonary nodules can be invisible under white light. Due to the increasing use of minimally invasive surgical techniques, tactile information is often reduced. Therefore, several intraoperative imaging techniques have been tested to localize pulmonary nodules, of which near-infrared (NIR) fluorescence is an emerging modality. In this systematic review, the available literature on fluorescence imaging of lung cancers is presented, which shows that NIR fluorescence-guided lung surgery has the potential to identify the tumor during surgery, detect additional lesions and prevent tumor-positive resection margins.
PubMed: 35330197
DOI: 10.3390/life12030446 -
International Journal of Environmental... Feb 2022Lung cancer (LC) represents the main cause of cancer-related deaths worldwide, especially because the majority of patients present with an advanced stage of the disease... (Review)
Review
Lung cancer (LC) represents the main cause of cancer-related deaths worldwide, especially because the majority of patients present with an advanced stage of the disease at the time of diagnosis. This systematic review describes the evidence behind screening results and the current guidelines available to manage lung nodules. This review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The following electronic databases were searched: PubMed, EMBASE, and the Web of Science. Five studies were included in the systematic review. The study cohort included 46,364 patients, and, in this case series, LC was detected in 9028 patients. Among the patients with detected LC, 1261 died of lung cancer, 3153 died of other types of cancers and 4614 died of other causes. This systematic review validates the use of CT in LC screening follow-ups, and bids for future integration and implementation of nodule management protocols to improve LC screening, avoid missed cancers and to reduce the number of unnecessary investigations.
Topics: Early Detection of Cancer; Humans; Lung; Lung Neoplasms; Mass Screening; Research
PubMed: 35206646
DOI: 10.3390/ijerph19042460 -
Frontiers in Cellular and Infection... 2021The multicenter literature review and case studies of 3 patients were undertaken to provide an updated understanding of nocardiosis, an opportunistic bacterial infection...
OBJECTIVE
The multicenter literature review and case studies of 3 patients were undertaken to provide an updated understanding of nocardiosis, an opportunistic bacterial infection affecting immunosuppressed nephrotic syndrome (NS) patients receiving long-term glucocorticoid and immunosuppressant treatment. The results provided clinical and microbiological data to assist physicians in managing nocardiosis patients.
METHODS
Three cases between 2017 and 2018 from a single center were reported. Additionally, a systematic review of multicenter cases described in the NCBI PubMed, Web of Science, and Embase in English between January 1, 2001 and May 10, 2021 was conducted.
RESULTS
This study described three cases of infection in NS patients. The systematic literature review identified 24 cases with sufficient individual patient data. A total of 27 cases extracted from the literature review showed that most patients were > 50 years of age and 70.4% were male. Furthermore, the glucocorticoid or corticosteroid mean dose was 30.9 ± 13.7 mg per day. The average time between hormone therapy and infection was 8.5 ± 9.7 months. Pulmonary (85.2%) and skin (44.4%) infections were the most common manifestations in NS patients, with disseminated infections in 77.8% of patients. Nodule/masses and consolidations were the major radiological manifestations. Most patients showed elevated inflammatory biomarkers levels, including white blood cell counts, neutrophils percentage, and C-reactive protein. Twenty-five patients received trimethoprim-sulfamethoxazole monotherapy (18.5%) or trimethoprim-sulfamethoxazole-based multidrug therapy (74.1%), and the remaining two patients (7.4%) received biapenem monotherapy. All patients, except the two who were lost to follow-up, survived without relapse after antibiotic therapy.
CONCLUSIONS
Nephrotic syndrome patients are at high risk of infection even if receiving low-dose glucocorticoid during the maintenance therapy. The most common manifestations of nocardiosis in NS patients include abnormal lungs revealing nodules and consolidations, skin and subcutaneous abscesses. The NS patients have a high rate of disseminated and cutaneous infections but a low mortality rate. Accurate and prompt microbiological diagnosis is critical for early treatment, besides the combination of appropriate antibiotic therapy and surgical drainage when needed for an improved prognosis.
Topics: Aged; Anti-Bacterial Agents; Drug Therapy, Combination; Humans; Leprostatic Agents; Male; Multicenter Studies as Topic; Nephrotic Syndrome; Nocardia; Nocardia Infections
PubMed: 35141169
DOI: 10.3389/fcimb.2021.789754 -
Thoracic Cancer Mar 2022Screening with low-dose computed tomography (LDCT) is an efficient way to detect lung cancer at an earlier stage, but has a high false-positive rate. Several pulmonary... (Review)
Review
BACKGROUND
Screening with low-dose computed tomography (LDCT) is an efficient way to detect lung cancer at an earlier stage, but has a high false-positive rate. Several pulmonary nodules risk prediction models were developed to solve the problem. This systematic review aimed to compare the quality and accuracy of these models.
METHODS
The keywords "lung cancer," "lung neoplasms," "lung tumor," "risk," "lung carcinoma" "risk," "predict," "assessment," and "nodule" were used to identify relevant articles published before February 2021. All studies with multivariate risk models developed and validated on human LDCT data were included. Informal publications or studies with incomplete procedures were excluded. Information was extracted from each publication and assessed.
RESULTS
A total of 41 articles and 43 models were included. External validation was performed for 23.2% (10/43) models. Deep learning algorithms were applied in 62.8% (27/43) models; 60.0% (15/25) deep learning based researches compared their algorithms with traditional methods, and received better discrimination. Models based on Asian and Chinese populations were usually built on single-center or small sample retrospective studies, and the majority of the Asian models (12/15, 80.0%) were not validated using external datasets.
CONCLUSION
The existing models showed good discrimination for identifying high-risk pulmonary nodules, but lacked external validation. Deep learning algorithms are increasingly being used with good performance. More researches are required to improve the quality of deep learning models, particularly for the Asian population.
Topics: Early Detection of Cancer; Humans; Lung; Lung Neoplasms; Multiple Pulmonary Nodules; Retrospective Studies
PubMed: 35137543
DOI: 10.1111/1759-7714.14333 -
Cureus Jan 2022Lung cancer has been the leading cause of cancer-associated deaths worldwide. While numerous reasons, including tobacco smoking, may lead to lung cancer, the purpose of... (Review)
Review
Lung cancer has been the leading cause of cancer-associated deaths worldwide. While numerous reasons, including tobacco smoking, may lead to lung cancer, the purpose of this article was to explore the association between sarcoidosis, a multisystem granulomatous disorder, and lung neoplasms. A literature search was done on multiple databases with appropriate keywords, and the authors selected case reports where patients were diagnosed with sarcoidosis and lung cancer. These reports were analyzed in detail, and nine reports were included in this study. Each case was evaluated for the presenting symptoms, age, gender, and diagnostic procedures, including a follow-up analysis. After the evaluation, it can be concluded that sarcoidosis and lung cancer can occur simultaneously, despite being rare. Appropriate diagnostic procedures, including histopathological examination of the affected lymph nodes, showed either cancerous or non-cancerous cells (granulomas), thus altering the treatment on a case-by-case basis. Being aware of all possible associations between these two diseases could alter the clinical management, whether curative or palliative, and clinicians must rule out metastatic cancer in individuals with sarcoidosis-like clinical and radiographic features.
PubMed: 35103216
DOI: 10.7759/cureus.21169 -
Computers in Biology and Medicine Feb 2022Since December 2019, the COVID-19 outbreak has resulted in countless deaths and has harmed all facets of human existence. COVID-19 has been designated an epidemic by the... (Review)
Review
Since December 2019, the COVID-19 outbreak has resulted in countless deaths and has harmed all facets of human existence. COVID-19 has been designated an epidemic by the World Health Organization (WHO), which has placed a tremendous burden on nearly all countries, especially those with weak health systems. However, Deep Learning (DL) has been applied in several applications and many types of detection applications in the medical field, including thyroid diagnosis, lung nodule recognition, fetal localization, and detection of diabetic retinopathy. Furthermore, various clinical imaging sources, like Magnetic Resonance Imaging (MRI), X-ray, and Computed Tomography (CT), make DL a perfect technique to tackle the epidemic of COVID-19. Inspired by this fact, a considerable amount of research has been done. A Systematic Literature Review (SLR) has been used in this study to discover, assess, and integrate findings from relevant studies. DL techniques used in COVID-19 have also been categorized into seven main distinct categories as Long Short Term Memory Networks (LSTM), Self-Organizing Maps (SOMs), Conventional Neural Networks (CNNs), Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs), Autoencoders, and hybrid approaches. Then, the state-of-the-art studies connected to DL techniques and applications for health problems with COVID-19 have been highlighted. Moreover, many issues and problems associated with DL implementation for COVID-19 have been addressed, which are anticipated to stimulate more investigations to control the prevalence and disaster control in the future. According to the findings, most papers are assessed using characteristics such as accuracy, delay, robustness, and scalability. Meanwhile, other features are underutilized, such as security and convergence time. Python is also the most commonly used language in papers, accounting for 75% of the time. According to the investigation, 37.83% of applications have identified chest CT/chest X-ray images for patients.
Topics: Algorithms; COVID-19; Deep Learning; Humans; Neural Networks, Computer; SARS-CoV-2
PubMed: 34929464
DOI: 10.1016/j.compbiomed.2021.105141 -
Systematic Reviews Dec 2021Solitary pulmonary nodule (SPN) is a common finding in routine clinical practice when performing chest imaging tests. The vast majority of these nodules are benign, and...
BACKGROUND
Solitary pulmonary nodule (SPN) is a common finding in routine clinical practice when performing chest imaging tests. The vast majority of these nodules are benign, and only a small proportion are malignant. The application of predictive models of nodule malignancy in routine clinical practice would help to achieve better diagnostic management of SPN. The present systematic review was carried out with the purpose of critically assessing studies aimed at developing predictive models of solitary pulmonary nodule (SPN) malignancy from SPN incidentally detected in routine clinical practice.
METHODS
We performed a search of available scientific literature until October 2020 in Pubmed, SCOPUS and Cochrane Central databases. The inclusion criteria were observational studies carried out in low-risk population from 35 years old onwards aimed at constructing predictive models of malignancy of pulmonary solitary nodule detected incidentally in routine clinical practice. Studies had to be published in peer-reviewed journals, either in Spanish, Portuguese or English. Exclusion criteria were non-human studies, or predictive models based in high-risk populations, or models based on computational approaches. Exclusion criteria were non-human studies, or predictive models based in high-risk populations, or models based on computational approaches (such as radiomics). We used The Transparent Reporting of a multivariable Prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement, to describe the type of predictive model included in each study, and The Prediction model Risk Of Bias ASsessment Tool (PROBAST) to evaluate the quality of the selected articles.
RESULTS
A total of 186 references were retrieved, and after applying the exclusion/inclusion criteria, 15 articles remained for the final review. All studies analysed clinical and radiological variables. The most frequent independent predictors of SPN malignancy were, in order of frequency, age, diameter, spiculated edge, calcification and smoking history. Variables such as race, SPN growth rate, emphysema, fibrosis, apical scarring and exposure to asbestos, uranium and radon were not analysed by the majority of the studies. All studies were classified as high risk of bias due to inadequate study designs, selection bias, insufficient population follow-up and lack of external validation, compromising their applicability for clinical practice.
CONCLUSIONS
The studies included have been shown to have methodological weaknesses compromising the clinical applicability of the evaluated SPN malignancy predictive models and their potential influence on clinical decision-making for the SPN diagnostic management.
SYSTEMATIC REVIEW REGISTRATION
PROSPERO CRD42020161559.
Topics: Humans; Lung; Lung Neoplasms; Prognosis; Risk Factors; Solitary Pulmonary Nodule
PubMed: 34872592
DOI: 10.1186/s13643-021-01856-6