Patient perspectives on delays in diagnosis and treatment of cancer: a qualitative analysis of free-text data

Background: Earlier cancer diagnosis is crucial in improving cancer survival. The International Cancer Benchmarking Partnership Module 4 (ICBP4) is a quantitative survey study that explores the reasons for delays in diagnosis and treatment of breast, colorectal, lung, and ovarian cancer. To further understand the associated diagnostic processes, it is also important to explore the patient perspectives expressed in the free-text comments. Aim: To use the free-text data provided by patients completing the ICBP4 survey to augment the understanding of patients’ perspectives of their diagnostic journey. Design and setting: Qualitative analysis of the free-text data collected in Wales between October 2013 and December 2014 as part of the ICBP4 survey. Newly-diagnosed patients with either breast, ovarian, colorectal, or lung cancer were identified from registry data and then invited by their GPs to participate in the survey. Method: A thematic framework was used to analyse the free-text comments provided at the end of the ICBP4 survey. Of the 905 patients who returned a questionnaire, 530 included comments. Results: The free-text data provided information about patients’ perspectives of the diagnostic journey. Analysis identified factors that acted as either barriers or facilitators at different stages of the diagnostic process. Some factors, such as screening, doctor–patient familiarity, and private treatment, acted as both barriers and facilitators depending on the context. Conclusion: Factors identified in this study help to explain how existing models of cancer diagnosis (for example, the Pathways to Treatment Model) work in practice. It is important that clinicians are aware of how these factors may interact with individual clinical cases and either facilitate, or act as a barrier to, subsequent cancer diagnosis. Understanding and implementing this knowledge into clinical practice may result in quicker cancer diagnoses

Rational clinical evaluation of suspected acute coronary syndromes: The value of more information

Objective: Many meta-analyses have provided synthesised likelihood ratio data to aid clinical decision-making. However, much less has been published on how to safely combine clinical information in practice. We aimed to explore the benefits and risks of pooling clinical information during the ED assessment of suspected acute coronary syndrome. Methods: Clinical information on 1776 patients was collected within a randomised trial conducted across five South Australian EDs between July 2011 and March 2013. Bayes theorem was used to calculate patient-specific post-test probabilities using age- and gender-specific pre-test probabilities and likelihood ratios corresponding to the presence or absence of 18 clinical factors. Model performance was assessed as the presence of adverse cardiac outcomes among patients theoretically discharged at a post-test probability less than 1%. Results: Bayes theorem-based models containing high-sensitivity troponin T (hs-troponin) outperformed models excluding hs-troponin, as well as models utilising TIMI and GRACE scores. In models containing hs-troponin, a plateau in improving discharge safety was observed after the inclusion of four clinical factors. Models with fewer clinical factors better approximated the true event rate, tended to be safer and resulted in a smaller standard deviation in post-test probability estimates. Conclusions: We showed that there is a definable point where additional information becomes uninformative and may actually lead to less certainty. This evidence supports the concept that clinical decision-making in the assessment of suspected acute coronary syndrome should be focused on obtaining the least amount of information that provides the highest benefit for informing the decisions of admission or discharge.</p

Economic evaluation of vaccination programmes: a consensus statement focusing on viral hepatitis.

The methods that have been used to estimate the clinical and economic impact of vaccination programmes are not always uniform, which makes it difficult to compare results between economic analyses. Furthermore, the relative efficiency of vaccination programmes can be sensitive to some of the more controversial aspects covered by general guidelines for the economic evaluation of healthcare programmes, such as discounting of health gains and the treatment of future unrelated costs. In view of this, we interpret some aspects of these guidelines with respect to vaccination and offer recommendations for future analyses. These recommendations include more transparency and validation, more careful choice of models (tailored to the infection and the target groups), more extensive sensitivity analyses, and for all economic evaluations (also nonvaccine related) to be in better accordance with general guidelines. We use these recommendations to interpret the evidence provided by economic evaluation applied to viral hepatitis vaccination. We conclude that universal hepatitis B vaccination (of neonates, infants or adolescents) seems to be the most optimal strategy worldwide, except in the few areas of very low endemicity, where the evidence to enable a choice between selective and universal vaccination remains inconclusive. While targeted hepatitis A vaccination seems economically unattractive, universal hepatitis A vaccination strategies have not yet been sufficiently investigated to draw general conclusions

Students' participation in collaborative research should be recognised

Letter to the editor