Cost-effectiveness analysis of screening for lung cancer with low dose spiral CT (computed tomography) in the Australian setting

Introduction:
Low dose spiral computed tomography (CT) is a sensitive screening tool for lung cancer that is currently being evaluated in both non-randomised studies and randomised controlled trials.
Methods:
We conducted a quantitative decision analysis using a Markov model to determine whether, in the Australian setting, offering spiral CT screening for lung cancer to high risk individuals would be cost-effective compared with current practice. This exploratory analysis was undertaken predominantly from the perspective of the government as third-party funder. In the base-case analysis, the costs and health outcomes (life-years saved and quality-adjusted life years) were calculated in a hypothetical cohort of 10,000 male current smokers for two alternatives: (1) screen for lung cancer with annual CT for 5 years starting at age 60 year and treat those diagnosed with cancer or (2) no screening and treat only those who present with symptomatic cancer.
Results:
For male smokers aged 60–64 years, with an annual incidence of lung cancer of 552 per 100,000, the incremental cost-effectiveness ratio was $57,325 per life-year saved and $105,090 per QALY saved. For females aged 60–64 years with the same annual incidence of lung cancer, the cost-effectiveness ratio was $51,001 per life-year saved and $88,583 per QALY saved. The model was used to examine the relationship between efficacy in terms of the expected reduction in lung cancer mortality at 7 years and cost-effectiveness. In the base-case analysis lung cancer mortality was reduced by 27% and all cause mortality by 2.1%. Changes in the estimated proportion of stage I cancers detected by screening had the greatest impact on the efficacy of the intervention and the cost-effectiveness. The results were also sensitive to assumptions about the test performance characteristics of CT scanning, the proportion of lung cancer cases overdiagnosed by screening, intervention rates for benign disease, the discount rate, the cost of CT, the quality of life in individuals with early stage screen-detected cancer and disutility associated with false positive diagnoses. Given current knowledge and practice, even under favourable assumptions, reductions in lung cancer mortality of less than 20% are unlikely to be cost-effective, using a value of $50,000 per life-year saved as the threshold to define a “cost-effective” intervention.
Conclusion:
The most feasible scenario under which CT screening for lung cancer could be cost-effective would be if very high-risk individuals are targeted and screening is either highly effective or CT screening costs fall substantially.

New system to help detect lung cancer

The article tells about the development of an intelligent system that can improve early detection of lung tissue abnormalities.

A tailored, supportive care intervention using systematic assessment designed for people with inoperable lung cancer: a randomised controlled trial

Objective : People with inoperable lung cancer experience higher levels of distress, more unmet needs and symptoms than other cancer patients. There is an urgent need to test innovative approaches to improve psychosocial and symptom outcomes in this group. This study tested the hypothesis that a tailored, multidisciplinary supportive care programme based on systematic needs assessment would reduce perceived unmet needs and distress and improve quality of life.

Methods : A randomised controlled trial design was used. The tailored intervention comprised two sessions at treatment commencement and completion. Sessions included a self-completed needs assessment, active listening, self-care education and communication of unmet psychosocial and symptom needs to the multidisciplinary team for management and referral. Outcomes were assessed with the Needs Assessment for Advanced Lung Cancer Patients, Hospital Anxiety and Depression Scale, Distress Thermometer and European Organization of Research and Treatment of Cancer Quality of Life Q-C30 V2.0.

Results : One hundred and eight patients with a diagnosis of inoperable lung or pleural cancer (including mesothelioma) were recruited from a specialist facility before the trial closed prematurely (original target 200). None of the primary contrasts of interest were significant (all p > 0.10), although change score analysis indicated a relative benefit from the intervention for unmet symptom needs at 8 and 12 weeks post-assessment (effect size = 0.55 and 0.40, respectively).

Conclusion : Although a novel approach, the hypothesis that the intervention would benefit perceived unmet needs, psychological morbidity, distress and health-related quality of life was not supported overall.

Lung cancer prediction from microarray data by gene expression programming

Lung cancer is a leading cause of cancer-related death worldwide. The early diagnosis of cancer has demonstrated to be greatly helpful for curing the disease effectively. Microarray technology provides a promising approach of exploiting gene profiles for cancer diagnosis. In this study, the authors propose a gene expression programming (GEP)-based model to predict lung cancer from microarray data. The authors use two gene selection methods to extract the significant lung cancer related genes, and accordingly propose different GEP-based prediction models. Prediction performance evaluations and comparisons between the authors' GEP models and three representative machine learning methods, support vector machine, multi-layer perceptron and radial basis function neural network, were conducted thoroughly on real microarray lung cancer datasets. Reliability was assessed by the cross-data set validation. The experimental results show that the GEP model using fewer feature genes outperformed other models in terms of accuracy, sensitivity, specificity and area under the receiver operating characteristic curve. It is concluded that GEP model is a better solution to lung cancer prediction problems.

Validity of the assessment of quality of life (AQoL) utility instrument in patients with operable and inoperable lung cancer

There have been few longitudinal studies of quality of life in patients with all stages of lung cancer, particularly those that have included measures of utility. The purpose of this study was to examine the psychometric properties of the Assessment of Quality of Life instrument (AQoL) in patients with lung cancer. The AQoL is a health-related quality of life questionnaire and provides a descriptive system for a multi-attribute utility instrument (MAU), so that scores can be used in cost-utility evaluations. In the present study the reliability (internal consistency) of the AQoL was examined and the concurrent validity was assessed using the Medical Outcomes 36-item Short Form Health Survey (SF-36) as the comparator instrument. The sensitivity to different health states of the AQoL and the responsiveness to change over time was also examined. A prospective, non-experimental cohort study was undertaken. Ninety-two participants with all stages of lung cancer were recruited from a tertiary multi-disciplinary lung cancer clinic. Ninety participants had non-small cell lung cancer (NSCLC) and two had limited stage small cell lung cancer. The AQOL and SF-36 surveys were administered concurrently at baseline. In patients with NSCLC the surveys were then repeated 3 and 6 months later. Correlations between the baseline AQoL summary scales and SF-36 summary scales support the divergent and convergent validity of the AQoL. Reliability was also found to be sufficient (Cronbach's Alpha = 0.76). In addition, in patients with inoperable NSCLC, baseline AQoL scores were found to be predictive of survival at 6 months in Cox proportional hazards multivariate analysis. However, the physical components summary score of the SF-36 was more sensitive to differences in health states between patients with different stages of NSCLC at 6 months of follow-up and more responsive to change over time in both operable and inoperable patients with NSCLC than the AQoL. The findings support the construct validity and reliability of the AQoL in this population. However, there remains some uncertainty about whether the AQoL has sufficient sensitivity to different health states in this population. Further studies using other MAU instruments may determine whether alternative instruments are more sensitive to different health states in individuals with lung cancer.

Early breast cancer identification : Which way to go? Microarray or image based computer aided diagnosis!

The goal of this research is to develop a computer aided diagnostic (CAD) system that can detect breast cancer in the early stage by using microarray and image data. We verified the performance of six well known classification algorithms with various performance matrices. Although we do not suggest a unique classifier algorithm for a CAD system, we do identify a number of algorithms whose performance is very promising. The algorithms performance was validated by 3 images dataset; two have been used for the first time in this experiment. Multidimensional image filtering is adopted for the final data extraction. The image data classification performance is compared with microarray data. Results suggest the most effective means of breast cancer identification in the early stage is a hybrid approach.

Anti-angiogenic therapy for lung cancer

This is the protocol for a review and there is no abstract. The objectives are as follows:

To determine the benefits and harms of angiogenesis inhibitors in the treatment of lung cancer when given alone, following or in combination with chemotherapy or chemo-radiotherapy (in the case of locally advanced non-metastatic NSCLC or limited stage SCLC).

Plumbagin induces apoptotic and autophagic cell death through inhibition of the PI3K/Akt/mTOR pathway in human non-small cell lung cancer cells.

Plumbagin (PLB) has shown anti-cancer activity but the mechanism is unclear. This study has found that PLB has a potent pro-apoptotic and pro-autophagic effect on A549 and H23 cells. PLB arrests cells in G2/M phase, and increases the intracellular level of reactive oxygen species in both cell lines. PLB dose-dependently induces autophagy through inhibition of PI3K/Akt/mTOR pathway as indicated by reduced phosphorylation of Akt and mTOR. Inhibition or induction of autophagy enhances PLB-induced apoptosis. There is crosstalk between PLB-induced apoptosis and autophagy. These findings indicate that PLB initiates both apoptosis and autophagy in NSCLC cells through coordinated pathways.