Jonathan P. Myles

Morbidity After Sentinel Lymph Node Biopsy in Primary Breast Cancer: Results From a Randomized Controlled Trial

PURPOSE Axillary lymph node dissection (ALND) as part of surgical treatment for patients with breast cancer is associated with significant morbidity. Sentinel lymph node biopsy (SLNB) is a newly developed method of staging the axilla and has the potential to avoid an ALND in lymph node-negative patients, thereby minimizing morbidity. The aim of this study was to investigate physical and psychological morbidity after SLNB in the treatment of early breast cancer in a randomized controlled trial. PATIENTS AND METHODS Between November 1999 and February 2003, 298 patients with early breast cancer (tumors 3 cm or less on ultrasound examination) who were clinically node negative were randomly allocated to undergo ALND (control group) or SLNB followed by ALND if subsequently found to be lymph node positive (study group). A detailed assessment of physical and psychological morbidity was performed during a 1-year period postoperatively. RESULTS A significant reduction in postoperative arm swelling, rate of seroma formation, numbness, loss of sensitivity to light touch and pinprick was observed in the study group. Although shoulder mobility was less impaired on average in the study group, this was significant only for abduction at 1 month and flexion at 3 months. Scores reflecting quality of life and psychological morbidity were significantly better in the study group in the immediate postoperative period, with fewer long-term differences. CONCLUSION SLNB in patients undergoing surgery for breast cancer results in a significant reduction in physical and psychological morbidity.

Methods in health service research: An introduction to bayesian methods in health technology assessment

This is the third of four articles Bayess theorem arose from a posthumous publication in 1763 by Thomas Bayes, a non-conformist minister from Tunbridge Wells. Although it gives a simple and uncontroversial result in probability theory, specific uses of the theorem have been the subject of considerable controversy for more than two centuries. In recent years a more balanced and pragmatic perspective has emerged, and in this paper we review current thinking on the value of the Bayesian approach to health technology assessment. A concise definition of bayesian methods in health technology assessment has not been established, but we suggest the following: the explicit quantitative use of external evidence in the design, monitoring, analysis, interpretation, and reporting of a health technology assessment. This approach acknowledges that judgments about the benefits of a new technology will rarely be based solely on the results of a single study but should synthesise evidence from multiple sources—for example, pilot studies, trials of similar interventions, and even subjective judgments about the generalisability of the studys results. A bayesian perspective leads to an approach to clinical trials that is claimed to be more flexible and ethical than traditional methods,1 and to elegant ways of handling multiple substudies—for example, when simultaneously estimating the effects of a treatment on many subgroups.2 Proponents have also argued that a bayesian approach allows conclusions to be provided in a form that is most suitable for decisions specific to patients and decisions affecting public policy.3 #### Summary points Bayesian methods interpret data from a study in the light of external evidence and judgment, and the form in which conclusions are drawn contributes naturally to decision making Prior plausibility of hypotheses is taken into account, just as when interpreting the results of a diagnostic test Scepticism about large treatment effects can be formally …

The LLP risk model: an individual risk prediction model for lung cancer.

Using a model-based approach, we estimated the probability that an individual, with a specified combination of risk factors, would develop lung cancer within a 5-year period.Data from 579 lung cancer cases and 1157 age- and sex-matched population-based controls were available for this analysis. Significant risk factors were fitted into multivariate conditional logistic regression models. The final multivariate model was combined with age-standardised lung cancer incidence data to calculate absolute risk estimates.Combinations of lifestyle risk factors were modelled to create risk profiles. For example, a 77-year-old male non-smoker, with a family history of lung cancer (early onset) and occupational exposure to asbestos has an absolute risk of 3.17% (95% CI, 1.67–5.95). Choosing a 2.5% cutoff to trigger increased surveillance, gave a sensitivity of 0.62 and specificity of 0.70, while a 6.0% cutoff gave a sensitivity of 0.34 and specificity of 0.90. A 10-fold cross validation produced an AUC statistic of 0.70, indicating good discrimination. If independent validation studies confirm these results, the LLP risk models’ application as the first stage in an early detection strategy is a logical evolution in patient care.

Long-term impact of neonatal intensive care and surgery on somatosensory perception in children born extremely preterm

Abstract Alterations in neural activity due to pain and injury in early development may produce long‐term effects on sensory processing and future responses to pain. To investigate persistent alterations in sensory perception, we performed quantitative sensory testing (QST) in extremely preterm (EP) children (n = 43) recruited from the UK EPICure cohort (born less than 26 weeks gestation in 1995) and in age and sex matched term‐born controls (TC; n = 44). EP children had a generalized decreased sensitivity to all thermal modalities, but no difference in mechanical sensitivity at the thenar eminence. EP children who also required neonatal surgery had more marked thermal hypoalgesia, but did not differ from non‐surgical EP children in the measures of neonatal brain injury or current cognitive ability. Adjacent to neonatal thoracotomy scars there was a localized decrease in both thermal and mechanical sensitivity that differed from EP children with scars relating to less invasive procedural interventions or from those without scars. No relationship was found between sensory perception thresholds and current pain experience or pain coping styles in EP or TC children. Neonatal care and surgery in EP children are associated with persistent modality‐specific changes in sensory processing. Decreases in mechanical and thermal sensitivity adjacent to scars may be related to localized tissue injury, whereas generalized decreases in thermal sensitivity but not in mechanical sensitivity suggest centrally mediated alterations in the modulation of C‐fibre nociceptor pathways, which may impact on responses to future pain or surgery.

Lung cancer risk prediction: a tool for early detection.

Although 45% of men and 39% of women will be diagnosed with cancer in their lifetime, it is difficult to predict which individuals will be affected. For some cancers, substantial progress in individual risk estimation has already been made. However, relatively few models have been developed to predict lung cancer risk beyond effects of age and smoking. This paper reviews published models for lung cancer risk prediction, discusses their potential contribution to clinical and research settings and suggests improvements to the risk modeling strategy for lung cancer. The sensitivity and specificity of existing cancer risk models is less than optimal. Improvement in individual risk prediction is important for selection of individuals for prevention or early detection interventions. In addition to smoking, factors related to occupational exposure, personal medical history and family history of cancer can add to the predictive power. A good risk prediction model is one that can identify a small fraction of the population in which a large proportion of the disease cases will occur. In the future, genetic and other biological markers are likely to be useful, although they will require rigorous evaluation. Validation is essential to establish the predictive effect and for ongoing monitoring of the models continued relevance.

Bayesian Approaches to Clinical Trials and Health-Care Evaluation: Spiegelhalter/Clinical Trials and Health-Care Evaluation

The Bayesian approach involves synthesising data and judgement in order to reach conclusions about unknown quantities and make predictions. Bayesian methods have become increasingly popular in recent years, notably in medical research, and although there are a number of books on Bayesian analysis, few cover clinical trials and biostatistical applications in any detail. Bayesian Approaches to Clinical Trials and Health-Care Evaluation provides a valuable overview of this rapidly evolving field, including basic Bayesian ideas, prior distributions, clinical trials, observational studies, evidence synthesis and cost-effectiveness analysis. Covers a broad array of essential topics, building from the basics to more advanced techniques.

Overdiagnosis, Sojourn Time, and Sensitivity in the Copenhagen Mammography Screening Program

Abstract:  The goal of this research was to estimate the overdiagnosis at the first and second screens of the mammography screening program in Copenhagen, Denmark. This study involves a mammography service screening program in Copenhagen, Denmark, with 35,123 women screened at least once. We fit multistate models to the screening data, including preclinical incidence of progressive cancers and nonprogressive (i.e., overdiagnosed) cancers. We estimated mean sojourn time as 2.7 years (95% confidence interval [CI] 2.2–3.1) and screening test sensitivity as 100% (95% CI 99.8–100). Overdiagnosis was estimated to be 7.8% (95% CI 0.3–26.5) at the first screen and 0.5% (95% CI 0.02–2.1) at the second screen. This corresponds to 4.8% of all cancers diagnosed among participants during the first two invitation rounds and following intervals. A modest overdiagnosis was estimated for the Copenhagen screening program, deriving almost exclusively from the first screen. The CIs were very broad, however, and estimates from larger datasets are warranted. 

The UK Lung Screen (UKLS): demographic profile of first 88,897 approaches provides recommendations for population screening.

The UK Lung Cancer Screening trial (UKLS) aims to evaluate low-dose computed tomography (LDCT) lung cancer population screening in the United Kingdom. In UKLS, a large population sample ages 50 to 75 years is approached with a questionnaire to determine lung cancer risk. Those with an estimated risk of at least 5% of developing lung cancer in the next 5 years (using the Liverpool Lung project risk model) are invited to participate in the trial. Here, we present demographic, risk, and response rate data from the first 88,897 individuals approached. Of note, 23,794 individuals (26.8% of all approached) responded positively to the initial questionnaire; 12% of these were high risk. Higher socioeconomic status correlated positively with response, but inversely with risk (P < 0.001). The 50- to 55-year age group was least likely to participate, and at lowest cancer risk. Only 5% of clinic attendees were ages ≤60 years (compared with 47% of all 88,897 approached); this has implications for cost effectiveness. Among positive responders, there were more ex-smokers than expected from population figures (40% vs. 33%), and fewer current smokers (14% vs. 17.5%). Of note, 32.7% of current smokers and 18.4% of ex-smokers were designated as high risk. Overall, 1,452 of 23,794 positive responders (6.1%) were deemed high risk and attended a recruitment clinic. UKLS is the first LDCT population screening trial, selecting high-risk subjects using a validated individual risk prediction model. Key findings: (i) better recruitment from ex- rather than current smokers, (ii) few clinic attendees ages early 50s, and (iii) representative number of socioeconomically deprived people recruited, despite lower response rates. Cancer Prev Res; 7(3); 362–71. ©2014 AACR.

Probabilities of progression of aortic aneurysms: estimates and implications for screening policy

Background: Screening for abdominal aortic aneurysm, and intervention with elective repair, can reduce the incidence of aneurysmal rupture by a half. If a screening programme is implemented, it is essential to determine appropriate follow up intervals for rescreening. This paper estimates probabilities of progression growth of aortic diameter to provide evidence for this. Methods: Data were taken from 2342 men aged 65–80 screened in the Chichester randomised control trial, who have been followed up for an average of 11 years. Aortic diameter was modelled as a Markov process with four categories: <30 mm (normal), 30–44 mm, 45–54 mm, and ≥55 mm. Estimates of the probabilities of progressing to each higher category were obtained. Results: The probabilities of progression increased with greater initial aortic diameter. The estimated rates/year were 0.018 (95% confidence interval 0.014 to 0.023), 0.16 (0.12 to 0.20), and 0.49 (0.35 to 0.70) respectively for moving up one category. The probabilities of moving from <30 mm to ≥55 mm were estimated as 1% in 5 years and 12% in 15 years, while the corresponding figures for moving from 45–54 mm to ≥55 mm were 91% and 99%. There were differences in rates of progression according to age, with men over 70 years having rates about three times those of men under 70. Conclusions: It seems unnecessary to follow up men with normal aortic diameter as they experience a low probability of reaching criteria for surgery even within 15 years. However, follow up intervals should be progressively shorter for those with greater aortic diameter, especially in those aged over 70. Active follow up, for example every 3 months, is appropriate for men with an aortic diameter of 45–54 mm.

Mammographic screening: a key factor in the control of breast cancer.

Since the late 1980s, there has been broad agreement, with invitation to screening in women aged 40–49 years and a significant 27% reduction in women aged 50–74 with few dissenters, that mammographic screening significantly and substantially reduced mortality from years.10,11 A sizeable proportion of the evidence comes from the Swedish Two-County Trial of mammographic breast cancer. This was based on the findings of the eight randomized trials of breast screening worldwide.1-9 screening, conducted from 1977 to 1986 in Kopparberg and Östergötland counties in Sweden. Figure 1 shows the results of these with respect to breast cancer mortality. The combined result is a significant For the most part, this consensus on the benefits of mammographic screeningcontinues to prevail, although 24% reduction in breast cancermortality in women aged 40–74 years in association with invitation to screening. it has been questioned by a meta-analysis by that claims to find no benefit of breast cancer screening. Indeed, Overviews of age-specific effects of screening show a significant 18% reduction in breast cancer mortality Gøtzsche and Olsen12,13 claim that screening causes harm by increasing the rates of radical treatment. In particular, the authors of the meta-analysis asserted that