A population-level comparison of cancer-related and non-cancer-related health care costs using publicly available provincial administrative data

Ru-Doped MoS2 Monolayer for Exhaled Breath Detection on Early Lung Cancer Diagnosis: A First-Principles Investigation

Nanosensor-based patient exhaled breath detection is a practical and effective way to detect lung cancer early. In this paper, a Ru-doped MoS2 monolayer (Ru-MoS2) is proposed as a promising novel biosensor based on first-principles theory for the detection of three typical early stage lung cancer exhaled volatile organic compounds, namely, C3H4O, C3H6O, and C5H8. Replacement of a S atom in the MoS2 monolayer with a Ru dopant atom to form a stable Ru-MoS2 monolayer with a binding energy of -4.78 eV is further demonstrated by the thermostability and chemical stability analysis as well as improving the adsorption performance of the system for three VOCs. The adsorption configuration structures, adsorption properties, and electronic behavior of the Ru-MoS2 monolayer are investigated by electron deformation density and density of states analysis to gain a comprehensive understanding of the physicochemical properties as sensing material. The results show that the adsorption energies of the Ru-MoS2 monolayer for C3H4O, C3H6O, and C5H8 are 3.42, -1.53, and -2.80 eV, respectively, all of which are chemisorption with excellent adsorption performance. The sensitivities for the three VOCs could be up to 1.09, 140.50, and 5.90, respectively, and the band structure and work function further elucidate the sensing mechanism of the Ru-MoS2 monolayer as a resistive gas sensor. The type and concentration of these exhaled breaths may reflect changes in the patient's physiological and biochemical status and may serve as a probe for the diagnosis of lung cancer. The results in this work could provide a guidance for researchers to explore the practical applications in the early diagnosis of lung cancer by gas sensors.

Screening for lung cancer with computed tomography: protocol for systematic reviews for the Canadian Task Force on Preventive Health Care

PURPOSE

Lung cancer is the leading cause of cancer deaths in Canada, and because early cancers are often asymptomatic screening aims to prevent mortality by detecting cancer earlier when treatment is more likely to be curative. These reviews will inform updated recommendations by the Canadian Task Force on Preventive Health Care on screening for lung cancer.

METHODS

We will update the review on the benefits and harms of screening with CT conducted for the task force in 2015 and perform de novo reviews on the comparative effects between (i) trial-based selection criteria and use of risk prediction models and (ii) trial-based nodule classification and different nodule classification systems and on patients' values and preferences. We will search Medline, Embase, and Cochrane Central (for questions on benefits and harms from 2015; comparative effects from 2012) and Medline, Scopus, and EconLit (for values and preferences from 2012) via peer-reviewed search strategies, clinical trial registries, and the reference lists of included studies and reviews. Two reviewers will screen all citations (including those in the previous review) and base inclusion decisions on consensus or arbitration by another reviewer. For benefits (i.e., all-cause and cancer-specific mortality and health-related quality of life) and harms (i.e., overdiagnosis, false positives, incidental findings, psychosocial harms from screening, and major complications and mortality from invasive procedures as a result of screening), we will include studies of adults in whom lung cancer is not suspected. We will include randomized controlled trials comparing CT screening with no screening or alternative screening modalities (e.g., chest radiography) or strategies (e.g., CT using different screening intervals, classification systems, and/or patient selection via risk models or biomarkers); non-randomized studies, including modeling studies, will be included for the comparative effects between trial-based and other selection criteria or nodule classification methods. For harms (except overdiagnosis) we will also include non-randomized and uncontrolled studies. For values and preferences, the study design may be any quantitative design that either directly or indirectly measures outcome preferences on outcomes pertaining to lung cancer screening. We will only include studies conducted in Very High Human Development Countries and having full texts in English or French. Data will be extracted by one reviewer with verification by another, with the exception of result data on mortality and cancer incidence (for calculating overdiagnosis) where duplicate extraction will occur. If two or more studies report on the same comparison and it is deemed suitable, we will pool continuous data using a mean difference or standardized mean difference, as applicable, and binary data using relative risks and a DerSimonian and Laird model unless events are rare (< 1%) where we will pool odds ratios using Peto's method or (if zero events) the reciprocal of the opposite treatment arm size correction. For pooling proportions, we will apply suitable transformation (logit or arcsine) depending on the proportions of events. If meta-analysis is not undertaken we will synthesize the data descriptively, considering clinical and methodological differences. For each outcome, two reviewers will independently assess within- and across-study risk of bias and rate the certainty of the evidence using GRADE (Grading of Recommendations Assessment, Development, and Evaluation), and reach consensus.

DISCUSSION

Since 2015, additional trials and longer follow-ups or additional data (e.g., harms, specific patient populations) from previously published trials have been published that will improve our understanding of the benefits and harms of screening. The systematic review of values and preferences will allow fulsome insights that will inform the balance of benefits and harms.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42022378858.

Increased Prevalence of Adverse Health Outcomes Across the Lifespan in Those Affected by Polycystic Ovary Syndrome: A Canadian Population Cohort

Background

Polycystic ovary syndrome (PCOS) is the most common metabolic-endocrine disorder impacting the health and quality of life of women over the lifespan. Evidence-based data on the scope of adverse health outcomes in those affected by PCOS is critical to improve healthcare and quality of life in this population. The aim of this study was to determine the prevalence of adverse health outcomes in those with PCOS compared to age-matched controls.

Methods

We conducted a retrospective observational case-control study in those diagnosed with PCOS and age-matched controls using the Alberta Health Services Health Analytics database and the International Classification of Diseases, for the period from 2002-2018 in Alberta, Canada.

Results

The cohort consisted of n = 16,531 exposed PCOS cases and n = 49,335 age-matched un-exposed controls. The prevalences of hypertension, renal disease, gastrointestinal disease, eating disorders, mental illness, depression-anxiety, rheumatoid arthritis, respiratory infections, and all malignancies were 20%-40% (P < 0.0001) higher in those with PCOS, compared to controls. The prevalence of obesity, dyslipidemia, nonalcoholic fatty liver disease, and type 2 diabetes was 2-3 fold higher in those with PCOS (P < 0.001). Cardiovascular, cerebrovascular, and peripheral vascular disease were 30%-50% higher, and they occurred 3-4 years earlier in those with PCOS (P < 0.0001); a 2-fold higher prevalence of dementia occurred in those with PCOS, compared to controls.

Conclusion

These findings provide evidence that PCOS is associated with a higher prevalence of morbidities over the lifespan, and the potential scope of the healthcare burden in women affected by PCOS.

IGWO-IVNet3: DL-Based Automatic Diagnosis of Lung Nodules Using an Improved Gray Wolf Optimization and InceptionNet-V3

Artificial intelligence plays an essential role in diagnosing lung cancer. Lung cancer is notoriously difficult to diagnose until it has progressed to a late stage, making it a leading cause of cancer-related mortality. Lung cancer is fatal if not treated early, making this a significant issue. Initial diagnosis of malignant nodules is often made using chest radiography (X-ray) and computed tomography (CT) scans; nevertheless, the possibility of benign nodules leads to wrong choices. In their first phases, benign and malignant nodules seem very similar. Additionally, radiologists have a hard time viewing and categorizing lung abnormalities. Lung cancer screenings performed by radiologists are often performed with the use of computer-aided diagnostic technologies. Computer scientists have presented many methods for identifying lung cancer in recent years. Low-quality images compromise the segmentation process, rendering traditional lung cancer prediction algorithms inaccurate. This article suggests a highly effective strategy for identifying and categorizing lung cancer. Noise in the pictures was reduced using a weighted filter, and the improved Gray Wolf Optimization method was performed before segmentation with watershed modification and dilation operations. We used InceptionNet-V3 to classify lung cancer into three groups, and it performed well compared to prior studies: 98.96% accuracy, 94.74% specificity, as well as 100% sensitivity.

Discussion of costs and financial burden in clinical practice: A survey of medical oncologists in Australia

Background

A diagnosis of cancer is associated with significant physical, psychological and financial burden. Including costs of cancer is an important component of shared decision making. Doctors bear a responsibility towards educating patients about the financial aspects of care. Multiple organisations have advocated for price transparency and implementing Informed Financial Consent in the clinic. However, few studies have evaluated the perspectives of oncologists on the current state of this discussion.

Aims

The aim of this study is to determine the views and perspectives of medical oncologists regarding communication of costs and financial burden in patients with cancer.

Methods

We conducted a prospective cross-sectional online survey via REDCap. The survey was distributed to medical oncologists and advanced trainees currently registered with Medical Oncology Group of Australia (MOGA). Data was collected using the online survey comprising socio-demographic characteristics, discussion of costs and financial burden, and facilitators and barriers to these discussions.

Results

547 members of MOGA were invited to participate in the study, and 106 of 547 MOGA members (19%) completed the survey. Most oncologists (66%) felt that it was their responsibility to discuss costs of care, however a majority of oncologists (59.3%) reported discussing costs with less than half of their patients. Only 25% of oncologists discussed financial concerns with more than half of their patients, and most oncologists were unfamiliar with cancer-related financial burden. Most Oncologists with greater clinical experience and those working in private practice were more likely to discuss costs with a majority of their patients.

Conclusions

Certain characteristics of medical oncologists and their practices were associated with reported prevalence of discussing costs of care and financial burden with their patients. In the context of rising costs of cancer care, interventions targeting modifiable factors such as raising oncologist awareness of costs of care and financial burden, screening for financial toxicity and availability of costs information in an easily accessible manner, may help increase the frequency of patient-doctor discussions about costs of care, contributing to informed decision-making and higher-quality cancer care.

Cancer Survivors’ Long-Term Health Service Costs in Queensland, Australia: Results of a Population-Level Data Linkage Study (Cos-Q)

Worldwide, the number of cancer survivors is rapidly increasing. The aim of this study was to quantify long-term health service costs of cancer survivorship on a population level. The study cohort comprised residents of Queensland, Australia, diagnosed with a first primary malignancy between 1997 and 2015. Administrative databases were linked with cancer registry records to capture all health service utilization. Health service costs between 2013–2016 were analyzed using a bottom-up costing approach. The cumulative mean annual healthcare expenditure (2013–2016) for the cohort of N = 230,380 individuals was AU$3.66 billion. The highest costs were incurred by patients with a history of prostate (AU$538 m), breast (AU$496 m) or colorectal (AU$476 m) cancers. Costs by time since diagnosis were typically highest in the first year after diagnosis and decreased over time. Overall mean annual healthcare costs per person (2013–2016) were AU$15,889 (SD: AU$25,065) and highest costs per individual were for myeloma (AU$45,951), brain (AU$30,264) or liver cancer (AU$29,619) patients. Our results inform policy makers in Australia of the long-term health service costs of cancer survivors, provide data for economic evaluations and reinforce the benefits of investing in cancer prevention.

Computer-Assisted Image Processing System for Early Assessment of Lung Nodule Malignancy

Simple Summary

Lung cancer is the second most common cancer in men after prostate cancer and in women after breast cancer, but it is the leading cause of cancer death among both genders. This manuscript proposes a new computer-aided diagnosis system that uses only a single computed tomography scan to diagnose the pulmonary nodule as benign or malignant. This system helps in the early detection of the pulmonary nodules and shows its ability to identify the pulmonary nodules precisely.

Abstract

Lung cancer is one of the most dreadful cancers, and its detection in the early stage is very important and challenging. This manuscript proposes a new computer-aided diagnosis system for lung cancer diagnosis from chest computed tomography scans. The proposed system extracts two different kinds of features, namely, appearance features and shape features. For the appearance features, a Histogram of oriented gradients, a Multi-view analytical Local Binary Pattern, and a Markov Gibbs Random Field are developed to give a good description of the lung nodule texture, which is one of the main distinguishing characteristics between benign and malignant nodules. For the shape features, Multi-view Peripheral Sum Curvature Scale Space, Spherical Harmonics Expansion, and a group of some fundamental morphological features are implemented to describe the outer contour complexity of the nodules, which is main factor in lung nodule diagnosis. Each feature is fed into a stacked auto-encoder followed by a soft-max classifier to generate the initial malignancy probability. Finally, all these probabilities are combined together and fed to the last network to give the final diagnosis. The system is validated using 727 nodules which are subset from the Lung Image Database Consortium (LIDC) dataset. The system shows very high performance measures and achieves 92.55%, 91.70%, and 93.40% for the accuracy, sensitivity, and specificity, respectively. This high performance shows the ability of the system to distinguish between the malignant and benign nodules precisely.

A Comparison of Online Medical Crowdfunding in Canada, the UK, and the US

IMPORTANCE

Despite major differences in their health care systems, medical crowdfunding is increasingly used to finance personal health care costs in Canada, the UK, and the US. However, little is known about the campaigns designed to raise monetary donations for medical expenses, the individuals who turn to crowdfunding, and their fundraising intent.

OBJECTIVE

To examine the demographic characteristics of medical crowdfunding beneficiaries, campaign characteristics, and their association with funding success in Canada, the UK, and the US.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study extracted and manually reviewed data from GoFundMe campaigns discoverable between February 2018 and March 2019. All available campaigns on each country domain's GoFundMe medical discovery webpage that benefitted a unique patient(s) were included from Canada, the UK, and the US. Data analysis was performed from March to December 2019.

EXPOSURES

Campaign and beneficiary characteristics.

MAIN OUTCOMES AND MEASURES

Log-transformed amount raised in US dollars.

RESULTS

This study examined 3396 campaigns including 1091 in Canada, 1082 in the UK, and 1223 in the US. Campaigns in the US (median [IQR], $38 204 [$31 200 to $52 123]) raised more funds than campaigns in Canada ($12 662 [$9377 to $19 251]) and the UK ($6285 [$4028 to $12 348]). In the overall cohort per campaign, Black individuals raised 11.5% less (95% CI, -19.0% to -3.2%; P = .006) than non-Black individuals, and male individuals raised 5.9% more (95% CI, 2.2% to 9.7%; P = .002) than female individuals. Female (39.4% of campaigns vs 50.8% of US population; difference, 11.3%; 95% CI, 8.6% to 14.1%; P < .001) and Black (5.3% of campaigns vs 13.4% of US population; difference, 8.1%; 95% CI, 6.8% to 9.3%; P < .001) beneficiaries were underrepresented among US campaigns. Campaigns primarily for routine treatment expenses were approximately 3 times more common in the US (77.9% [272 of 349 campaigns]) than in Canada (21.9% [55 of 251 campaigns]; difference, 56.0%; 95% CI, 49.3-62.7%; P < .001) or the UK (26.6% [127 of 478 campaigns]; difference, 51.4%; 95% CI, 45.5%-57.3%; P < .001). However, campaigns for routine care were less successful overall. Approved, inaccessible care and experimental care raised 35.7% (95% CI, 25.6% to 46.7%; P < .001) and 20.9% (95% CI, 13.3% to 29.1%; P < .001), respectively, more per campaign than routine care. Campaigns primarily for alternative treatment expenses (16.1% [174 of 1079 campaigns]) were nearly 4-fold more common for cancer (23.5% [144 of 614 campaigns]) vs noncancer (6.5% [30 of 465 campaigns]) diagnoses.

CONCLUSIONS AND RELEVANCE

Important differences were observed in the reasons individuals turn to medical crowdfunding in the 3 countries examined that suggest racial and gender disparities in fundraising success. More work is needed to understand the underpinnings of these findings and their implications on health care provision in the countries examined.

Target Analysis of Volatile Organic Compounds in Exhaled Breath for Lung Cancer Discrimination from Other Pulmonary Diseases and Healthy Persons

The aim of the present study was to investigate the ability of breath analysis to distinguish lung cancer (LC) patients from patients with other respiratory diseases and healthy people. The population sample consisted of 51 patients with confirmed LC, 38 patients with pathological computed tomography (CT) findings not diagnosed with LC, and 53 healthy controls. The concentrations of 19 volatile organic compounds (VOCs) were quantified in the exhaled breath of study participants by solid phase microextraction (SPME) of the VOCs and subsequent gas chromatography-mass spectrometry (GC-MS) analysis. Kruskal-Wallis and Mann-Whitney tests were used to identify significant differences between subgroups. Machine learning methods were used to determine the discriminant power of the method. Several compounds were found to differ significantly between LC patients and healthy controls. Strong associations were identified for 2-propanol, 1-propanol, toluene, ethylbenzene, and styrene (p-values < 0.001-0.006). These associations remained significant when ambient air concentrations were subtracted from breath concentrations. VOC levels were found to be affected by ambient air concentrations and a few by smoking status. The random forest machine learning algorithm achieved a correct classification of patients of 88.5% (area under the curve-AUC 0.94). However, none of the methods used achieved adequate discrimination between LC patients and patients with abnormal computed tomography (CT) findings. Biomarker sets, consisting mainly of the exogenous monoaromatic compounds and 1- and 2- propanol, adequately discriminated LC patients from healthy controls. The breath concentrations of these compounds may reflect the alterations in patient's physiological and biochemical status and perhaps can be used as probes for the investigation of these statuses or normalization of patient-related factors in breath analysis.

Lifetime Costs of Surviving Cancer-A Queensland Study (COS-Q): Protocol of a Large Healthcare Data Linkage Study

Australia-wide, there are currently more than one million cancer survivors. There are over 32 million world-wide. A trend of increasing cancer incidence, medical innovations and extended survival places growing pressure on healthcare systems to manage the ongoing and late effects of cancer treatment. There are no published studies of the long-term health service use and cost of cancer survivorship on a population basis in Australia. All residents of the state of Queensland, Australia, diagnosed with a first primary malignancy from 1997–2015 formed the cohort of interest. State and national healthcare databases are linked with cancer registry records to capture all health service utilization and healthcare costs for 20 years (or death, if this occurs first), starting from the date of cancer diagnosis, including hospital admissions, emergency presentations, healthcare costing data, Medicare services and pharmaceuticals. Data analyses include regression and economic modeling. We capture the whole journey of health service contact and estimate long-term costs of all cancer patients diagnosed and treated in Queensland by linking routinely collected state and national healthcare data. Our results may improve the understanding of lifetime health effects faced by cancer survivors and estimate related healthcare costs. Research outcomes may inform policy and facilitate future planning for the allocation of healthcare resources according to the burden of disease.

Why are we organizing another costing supplement in Current Oncology?

Why are we publishing another costing supplement in Current Oncology? [...]