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Biomedical subjects

Stephen W Duffy

Publications and source records attributed to Stephen W Duffy.

At least 19 recordsLinked to original sources
PubMed2007

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 model's continued relevance.

Early Diagnosis↗
PubMed2006

Single reading with computer-aided detection and double reading of screening mammograms in the United Kingdom National Breast Screening Program.

PURPOSE: To retrospectively determine if the use of a computer-aided detection (CAD) system can improve the performance of single reading of screening mammograms to match that of double reading in the United Kingdom. MATERIALS AND METHODS: Local research ethics committee approval was obtained; informed consent was not required. This study included a sample of 10 267 mammograms obtained in women aged 50 years or older who underwent routine screening at one of two breast screening centers in 1996. Mammograms that were double read in 1996 were randomly allocated to be re-read by eight different radiologists using CAD. The cancer detection and recall rates from double reading and single reading with CAD were compared. Statistical significance and confidence intervals were calculated with the McNemar test to account for the matched nature of the data. RESULTS: Single reading with CAD led to a cancer detection rate that was significantly (P = .02) higher than that achieved with double reading: 6.5% more cancers were detected by means of single reading with CAD than by means of double reading. However, the recall rate was higher for single reading with CAD than for double reading (8.6% vs 6.5%, respectively; P < .001). This was equivalent to relative increases of 15% and 32% in the cancer detection and recall rates, respectively. CONCLUSION: Single reading with CAD leads to an improved cancer detection rate and an increased recall rate.

Breast Neoplasms↗
PubMed2006

Defining high-risk individuals in a population-based molecular-epidemiological study of lung cancer.

Within the framework of the Liverpool Lung Project (LLP), population-based case-control and prospective cohort studies are in progress to identify molecular and epidemiological risk factors and define populations and individuals most at risk of developing lung cancer. This report describes a strategy for selection of a high-risk population and further provides support for the inclusion of occupational and genetic risk factors in future models. Data from the case-control study (256 incident cases and 314 population controls) were analysed to define a high-risk population. Detailed lifestyle and occupational information were collected during structured interviews. Models were constructed using conditional logistic regression and included terms for age, tobacco consumption and previous respiratory disease. Smoking duration was chosen as the most important predictor of lung cancer risk [>50 years (OR 15.65, 95% CI 6.10-40.15)]. However, such a model would preclude younger individuals. Several combinations of previous respiratory disease were also considered, of which a history of bronchitis, emphysema or pneumonia (BEP) was the most significant (OR 1.86, 95% CI 1.28-2.69). A high-risk subset (based on combinations of smoking duration and BEP) was identified, which have a 4.5-fold greater risk of developing lung cancer (OR 4.5, 95% CI 2.33-8.68). Future refinement of the risk model to include individuals occupationally exposed to asbestos and with the p21 genotypes is discussed. There is real potential for environmental and genetic factors to improve on risk prediction and targeting of susceptible individuals beyond the traditional models based only on smoking and age. The development of a molecular-epidemiological model will inform the development of effective surveillance, early detection and chemoprevention strategies.

Aged↗
PubMed2006

Some issues in screening for breast and other cancers.

BACKGROUND: There are some issues in screening for cancer, especially breast cancer, which are worthy of further study. METHODS: We reviewed some approaches to the following issues in breast cancer screening: absolute benefit, overdiagnosis, separation of effects of screening from effects of others on deaths from breast cancer over time and determination of which tumours benefit most from early detection. For separation of screening effects from other effects, we developed a simple analysis of survival by tumour size. For the other issues, we identified methods and results from the literature on the randomized trials of screening and on service screening programmes. We also reviewed screening issues pertaining to other selected cancers, including some cancers common or becoming common in Asia. RESULTS: Published results from the Swedish Two-County Trial showed that for 350 women screened for 10 years, one life would be saved. Results from service screening programmes in Florence and elsewhere suggested that overdiagnosis is a minor phenomenon and mainly confined to ductal carcinoma in situ. Data from before and after the inception of screening in East Anglia suggested that 40-60% of the recent improvement in survival of breast cancer cases was due to early detection. Published data from the Swedish Two-county Trial indicated that the majority of the benefit of breast screening derives from early detection of grades 2 and 3 ductal carcinoma. CONCLUSIONS: Mammographic screening is effective in saving lives from breast cancer. Other cancers, which have strong evidence for a benefit of screening in terms of saving lives from cancer, are cervical and colorectal cancers. There is also evidence of a reduction in mortality associated with ultrasound screening for liver cancer in subjects at very high risk of the disease. There are a number of other cancers that are potential candidates for early detection. There is clearly an opportunity for saving lives from further development and implementation of cancer screening.

Breast Neoplasms↗
PubMed2005

Overdiagnosis and overtreatment of breast cancer: estimates of overdiagnosis from two trials of mammographic screening for breast cancer.

Randomised controlled trials have shown that the policy of mammographic screening confers a substantial and significant reduction in breast cancer mortality. This has often been accompanied, however, by an increase in breast cancer incidence, particularly during the early years of a screening programme, which has led to concerns about overdiagnosis, that is to say, the diagnosis of disease that, if left undetected and therefore untreated, would not become symptomatic. We used incidence data from two randomised controlled trials of mammographic screening, the Swedish Two-county Trial and the Gothenburg Trial, to establish the timing and magnitude of any excess incidence of invasive disease and ductal carcinoma in situ (DCIS) in the study groups, to ascertain whether the excess incidence of DCIS reported early in a screening trial is balanced by a later deficit in invasive disease and provide explicit estimates of the rate of 'real' and non-progressive 'overdiagnosed' tumours from the study groups of the trials. We used a multistate model for overdiagnosis and used Markov Chain Monte Carlo methods to estimate the parameters. After taking into account the effect of lead time, we estimated that less than 5% of cases diagnosed at prevalence screen and less than 1% of cases diagnosed at incidence screens are being overdiagnosed. Overall, we estimate overdiagnosis to be around 1% of all cases diagnosed in screened populations. These estimates are, however, subject to considerable uncertainty. Our results suggest that overdiagnosis in mammography screening is a minor phenomenon, but further studies with very large numbers are required for more precise estimation.

Adult↗
PubMed2005

Screening for breast cancer.

Strong evidence supports the value of breast cancer screening with mammography, and high-quality mammography screening can be considered a major public health achievement. As noted earlier in the discussion about the evaluation of service screening, the group of women who did not participate in mammographic screening in the decades after screening had been introduced had essentially unchanged or only minor improvements in mortality compared with the pattern before the introduction of screening, despite widespread use of adjuvant chemotherapy or hormonal therapy. Breast cancer should be treated in its preclinical phase if we are to save the lives of women with this disease, and a considerable body of evidence outlines best practices that, with broader adherence, would result in greater breast cancer mortality reductions than have been observed to date.

Breast Neoplasms↗
PubMed2005

Some current issues in breast cancer screening.

Randomized trials of mammography have demonstrated the efficacy of mammographic screening for breast cancer in terms of preventing deaths, but various issues of particular interest remain, including: quantification of overdiagnosis; evaluation of service screening outside the research setting; absolute benefit in terms of number needed to screen per life saved; which types of tumours benefit most from early detection; use of screening data to investigate tumour biology and natural history. This paper describes examples of approaches to the above issues, along with some important results.

Adult↗
PubMed2004

Mammographic tumor features can predict long-term outcomes reliably in women with 1-14-mm invasive breast carcinoma.

BACKGROUND: The radiologic images of 1-14-mm invasive breast carcinomas can be classified into 5 separate categories. The use of these mammographic indicators to predict patient outcome has important prognostic and therapeutic implications. METHODS: To verify the results of previous studies conducted with smaller numbers of patients, the authors studied the 24-year survival of 714 women with 1-14-mm invasive breast carcinoma according to mammographic prognostic factors. The association of mammographic features with lymph node status, histologic malignancy grade, and 24-year survival in 714 women with invasive breast carcinomas that measured 1-14 mm also was evaluated. Adjustments were made for tumor characteristics and treatment factors in the survival analysis. RESULTS: The most common mammographic feature was a stellate lesion with no associated calcifications (420 women; 59%). Patients with stellate lesions had excellent long-term survival (95%). Casting-type calcifications were observed in 52 women (7%) and were associated significantly with a positive lymph node status (odds ratio [OR], 3.29; 95% confidence interval [95% CI], 1.41-7.67), poorer histologic grade (OR, 7.04; 95% CI, 3.77-13.16), and an increased risk of death from breast carcinoma (HR, 9.19; 95% CI, 4.18-20.17). Except for women who had tumors with associated casting-type calcifications, all other women with tumors < 10 mm in size had excellent survival regardless of lymph node status, histologic grade, or treatment. For women who had casting-type calcifications, survival was poorer even in the group with tumors that measured 1-9 mm (72% at 20 years). For women with 10-14-mm tumors, the 20-year survival rate was 52% for those who had casting calcifications and 86-100% those for those who had other mammographic features. CONCLUSIONS: The subgroup of women who had small invasive breast carcinomas accompanied by casting-type calcifications had an unexpectedly poor prognosis for this tumor-size category. The process of neoductgenesis offers a possible explanation for the unexpectedly poor outcome. There is a need to develop treatment protocols for this group and to reevaluate the present TNM classification system for mammographically detected 1-14-mm breast carcinomas. After excluding women who had tumors associated with casting-type calcifications, the remaining women had an extremely good prognosis when they were treated with surgery alone. Due to their already excellent survival, adjuvant therapeutic regimens are unlikely to offer further benefit for these patients.

Adult↗
PubMed2004

Tamoxifen and breast density in women at increased risk of breast cancer.

BACKGROUND: Although mammographic breast density is associated with the risk of breast cancer and is influenced by hormone levels, the effects of tamoxifen on breast density in healthy women and whether tamoxifen-induced density changes are associated with breast cancer risk are unclear. We investigated mammographic breast density in healthy women with an increased risk of breast cancer at baseline and during 54 months of tamoxifen treatment. METHODS: Mammograms were reviewed from 818 breast cancer-free women (388 in the tamoxifen group and 430 in the placebo group) at high risk for breast cancer, from the International Breast Cancer Intervention Study I, a trial of tamoxifen for breast cancer prevention. Breast density measurements, at baseline and during treatment, were obtained at 12- to 18-month intervals. Multivariable analysis was used to assess associations with breast density. All statistical tests were two-sided. RESULTS: Breast density at baseline was similar in placebo (42.6%, 95% confidence interval [CI] = 39.6% to 45.6%) and tamoxifen (41.9%, 95% CI = 38.8% to 45.0%) groups. The main determinants of breast density at baseline were age, menopausal status, body mass index, and previous atypical hyperplasia. A greater density reduction in the tamoxifen group (7.9%, 95% CI = 6.9% to 8.9%) than in the placebo group (3.5%, 95% CI = 2.7% to 4.3%) was apparent within 18 months of treatment (P<.001); the reduction in density continued until 54 months of treatment. After 54 months of tamoxifen treatment, breast density was 28.2% (decrease from baseline = 13.7%, 95% CI = 12.3% to 15.1%; P<.001) in the tamoxifen group and 35.3% (decrease from baseline = 7.3%, 95% CI = 6.1% to 8.4%; P<.001) in the placebo group. The tamoxifen-associated density reduction was apparent in all subgroups, but there was a statistically significant interaction with age. In women aged 45 years or younger at entry, the net reduction with tamoxifen was 13.4% (95% CI = 8.6% to 18.1%), whereas in women older than 55 years, it was 1.1% (95% CI = -3.0% to 5.1%). CONCLUSION: Tamoxifen treatment was associated with reduction in breast density, most of which occurred during the first 18 months of treatment.

Adult↗
PubMed2004

A breast cancer prediction model incorporating familial and personal risk factors.

Many factors determine a woman's risk of breast cancer. Some of them are genetic and relate to family history, others are based on personal factors such as reproductive history and medical history. While many papers have concentrated on subsets of these risk factors, no papers have incorporated personal risk factors with a detailed genetic analysis. There is a need to combine these factors to provide a better overall determinant of risk. The discovery of the BRCA1 and BRCA2 genes has explained some of the genetic determinants of breast cancer risk, but these genes alone do not explain all of the familial aggregation of breast cancer. We have developed a model incorporating the BRCA genes, a low penetrance gene and personal risk factors. For an individual woman her family history is used in conjuction with Bayes theorem to iteratively produce the likelihood of her carrying any genes predisposing to breast cancer, which in turn affects her likelihood of developing breast cancer. This risk was further refined based on the woman's personal history. The model has been incorporated into a computer program that gives a personalised risk estimate.

Adult↗
PubMed2004

Time-dependent effects on survival in breast carcinoma: results of 20 years of follow-up from the Swedish Two-County Study.

BACKGROUND: Tumor size, lymph node status, and histologic grade are reported to be important predictors of survival in the first 5 years after the diagnosis of invasive breast carcinoma. However, to the authors' knowledge, the effect of these factors in the longer term (>10 years after diagnosis) is not yet clear. METHODS: It is now >20 years since the Swedish Two-County Trial of breast carcinoma screening with mammography was instigated and long-term follow-up is now available to December 1998. In the current study, the authors analyzed the effects of tumor size, lymph node status, and tumor grade on survival to death from breast carcinoma using Cox regression and frailty models that allow the baseline hazard and/or effect of a covariate to vary with time. RESULTS: The effects of tumor size, lymph node status, and tumor grade were shown to progressively diminish with time from diagnosis. The Cox regression model with time-varying coefficients and a dampening parameter then was fitted to allow for the attenuation of prognostic effects; tumor size, lymph node status, and tumor grade were all found to be highly significant (P<0.001). CONCLUSIONS: The results of the current study suggest that long-term survival in women with invasive breast carcinoma could be modelled satisfactorily using either frailty models or Cox regression models with time-varying coefficients. The results also suggest that the value of tumor grade, lymph node status, and tumor size at the time of diagnosis have a lasting influence on subsequent survival, albeit attenuated in later years. The long-term effects of these prognostic factors may explain the fact that the impact of mass screening programs on breast carcinoma mortality rates is still apparent many years later.

Breast Neoplasms↗
PubMed2004

Prospective estimation of rates of change in mammographic parenchymal patterns: influence of age and of hormone replacement therapy.

The objective of this study was to assess the effect of age, breast size and use of hormone replacement therapy (HRT) on the rate of change of mammographic parenchymal patterns, and the effect of age on the probability of misclassification between patterns. It was designed as a longitudinal study of the members of the treatment arm of a non-randomized screening trial in which subjects were assigned to screening or not by year of birth. The subjects were women in the Kotka district of Finland, each of whom attended for four or five mammographic screens. Participants were all women living in the district who were born in the relevant years and accepted an invitation to screening. A model was fitted to the longitudinal data comprising the observed Wolfe patterns on each woman, with age and breast size as predictors of breast density at first screen, age and HRT use as predictors of change in density at future screens, and age as a predictor of misclassification of true density between favourable (non-dense) and unfavourable (dense) patterns (according to the Wolfe classification). Relevant posterior probability estimates (with 95% credible intervals) were as follows. The probability that a woman of age 43.5 is truly in the favourable state ranged from 0.35 (0.34-0.37) for smallest breast size to 0.74 (0.72-0.76) for the largest. The probability that a woman is truly in the favourable state at first screen increased from 0.37 (0.36-0.38) at age 40 to 0.59 (0.58-0.60) at age 47. The probability that a woman having a later screen who had truly been in the unfavourable state at her previous screen changed to the favourable state increased from 0.12 (0.11-0.13) at age 42 to 0.48 (0.46-0.50) at age 55 for a woman not taking HRT, and from 0.10 (0.09-0.11) to 0.43 (0.40-0.45) at the same ages for a woman taking HRT. The probability that a woman would have changed from being truly in the favourable state to the unfavourable state was 0.003 (0.001-0.003) for any age and HRT use. The probability that a woman truly in a favourable state would be correctly classified rose from 0.87 (0.85-0.89) at age 40 to 0.998 (0.997-0.998) at age 55. The probability that a woman truly in the unfavourable state would be correctly classified decreased from 0.96 (0.95-0.97) to 0.93 (0.91-0.94) between the same ages. The probability of being in a non-dense, favourable state increases with age, as does the rate of change from dense to non-dense patterns. These are consistent with previous work. The probability of non-dense patterns and the rate of change to non-dense patterns are reduced with HRT use. Errors of classification are relatively rare, but are dependent on the age of the subject.

Adult↗
PubMed2004

The randomized trials of breast cancer screening: what have we learned?

Eight randomized controlled trials of mammography screening have been conducted to date. In addition to evaluating the efficacy of screening with an experimental design, the trials provided investigators with access to information about breast cancers much earlier in their development than had previously been available. The trials of mammographic screening provide conclusive evidence that the policy of offering screening is associated with a significant and substantial reduction in breast cancer mortality.

Breast Neoplasms↗
PubMed2003

Imputation of a true endpoint from a surrogate: application to a cluster randomized controlled trial with partial information on the true endpoint.

BACKGROUND: The Anglia Menorrhagia Education Study (AMES) is a randomized controlled trial testing the effectiveness of an education package applied to general practices. Binary data are available from two sources; general practitioner reported referrals to hospital, and referrals to hospital determined by independent audit of the general practices. The former may be regarded as a surrogate for the latter, which is regarded as the true endpoint. Data are only available for the true end point on a sub set of the practices, but there are surrogate data for almost all of the audited practices and for most of the remaining practices. METHODS: The aim of this paper was to estimate the treatment effect using data from every practice in the study. Where the true endpoint was not available, it was estimated by three approaches, a regression method, multiple imputation and a full likelihood model. RESULTS: Including the surrogate data in the analysis yielded an estimate of the treatment effect which was more precise than an estimate gained from using the true end point data alone. CONCLUSIONS: The full likelihood method provides a new imputation tool at the disposal of trials with surrogate data.

Bayes Theorem↗
PubMed2003

Misclassification in a matched case-control study with variable matching ratio: application to a study of c-erbB-2 overexpression and breast cancer.

We provide a simple analytic correction for risk factor misclassification in a matched case-control study with variable numbers of controls per case. The method is an extension of existing methodology, and involves estimating the corrected proportions of controls and cases in risk factor categories within each matched set. These estimates are then used to calculate the Mantel-Haenszel odds ratio estimate corrected for misclassification. A simulation-based interval estimate is developed. An example is given from a study of risk factors for progression of benign breast disease to breast cancer, in which the risk factor is a biological marker measured with poor sensitivity.

Breast Neoplasms↗