Modelling the early detection of breast cancer.

A mathematical model was developed to predict the outcome of early detection clinical trials or programs targeted at evaluating mortality benefit from earlier diagnosis of breast cancer. The model was applied to eight randomized breast cancer trials, which were carried out to evaluate the benefits of mammography, physical examination or their combination. The model assumes that breast cancer is a progressive disease and any mortality benefit from earlier diagnosis is generated from a favorable shift in the stage at diagnosis relative to usual care. The model predicted the reduction in mortality for seven of the eight trials within the reported confidence intervals. Input data required by the models are: stage shift distribution, examination schedules, population age distribution, follow up time, and survival conditional on stage at diagnosis. Survival distributions were obtained from the 1973-82 SEER database whereas the remaining data was obtained for each of the trials. Information on sensitivity and stage was ordinarily available during the early phase of the trials. The theoretical model has the promise of being able to predict the long-term outcome of early detection trials or programs during the initial examination phase. The theoretical model is general and may be applied to other chronic diseases, which satisfy the basic assumptions.

Screening sensitivity and sojourn time from breast cancer early detection clinical trials: mammograms and physical examinations.

PURPOSE: To estimate sensitivities of breast cancer screening modalities and preclinical duration of the disease from eight breast cancer screening clinical trials. PATIENTS AND METHODS: Screening programs invariably lead to diagnosis of disease before signs or symptoms are present. Two key quantities of screening programs are the sensitivity of the disease detection modality and the mean sojourn time (MST). The observed screening histories in a periodically screened cohort make it possible to estimate these quantities of interest. We applied recently developed statistical methods to data from eight randomized breast cancer screening trials to estimate the sensitivities of early detection modalities and MST. Moreover, when a screening trial involved two screening modalities, our methods enabled the estimation of the individual sensitivity of each screening modality. RESULTS: We analyzed breast cancer data from several screening trials and have relatively complete data from the Health Insurance Plan (HIP), Edinburgh, and two Canadian studies. The screening sensitivity for mammography, physical examination, and MST were, respectively, HIP: 0.39, 0.47, and 2.5 years; Edinburgh: 0.63, 0.40, and 4.3 years; Canadian (age 40 to 49 at entry): 0.61, 0.59, and 1.9 years; Canadian (age 50 to 59 at entry): 0.66, 0.39, and 3.1 years. CONCLUSION: The public debate on early breast cancer detection is mainly centered on mammograms. However, the current study indicates that a physical examination is of comparable importance. Cautious interpretation of trial differences is required as a result of various experimental designs and the age dependency of screening sensitivity and MST.

Comparing the survival of two groups with an intermediate clinical event.

Consider a subject entered on a clinical trial in which the major endpoint is a time metric such as death or time to reach a well defined event. During the observational period the subject may experience an intermediate clinical event. The intermediate clinical event may induce a change in the survival distribution. We consider models for the one and two sample problem. The model for the one sample problem enables one to test if the occurrence of the intermediate event changed the survival distribution. This models provides a way of carrying out non-randomized clinical trial to determine if a therapy has benefit. The two sample problem considers testing if the probability distributions, with and without an intermediate event, are the same. Statistical tests are derived using a semi-Markov or a time dependent mixture model. Simulation studies are carried out to compare these new procedures with the log rank, stratified log rank and landmark tests. The new tests appear to have uniformly greater power than these competitor tests. The methods are applied to a randomized clinical trial carried out by the Aids Clinical Trial Group (ACTG) which compared low versus high doses of zidovudine (AZT).

Referent sampling, family history and relative risk: the role of length-biased sampling.

Familial risk of disease is often assessed using case control studies based on referent databases. A referent database is a collection of family histories of cases typically assembled as a result of one family member being diagnosed with disease. This sampling scheme is equivalent to sampling families proportional to their size. The larger the family, the greater the probability of finding the family in the referent registry. This phenomena is known as length-biased sampling. The consequence of this kind of sampling is to bias the regression estimate associated with family history. The estimate is typically inflated in comparison to what is true for the actual population.

Testing the independence of two diagnostic tests.

Consider two diagnostic procedures having binary outcomes. If one of the tests results in a positive finding, a more definitive diagnostic procedure will be administered to establish the presence or absence of a disease. The use of both tests will improve the overall screening sensitivity when the two tests are independent, compared with employing two tests that are positively correlated. We estimate the correlation coefficient of the two tests and derive statistical methods for testing the independence of the two diagnostic procedures conditional on disease status. The statistical tests are used to investigate the independence of mammography and clinical breast exams aimed at establishing the benefit of early detection of breast cancer. The data used in the analysis are obtained from periodic screening examinations of three randomized clinical trials of breast cancer screening. Analysis of each of these trials confirms the independence of the clinical breast and mammography examinations. Based on these three large clinical trials, we conclude that a clinical breast exam considerably increases the overall sensitivity relative to screening with mammography alone and should be routinely included in early breast cancer detection programs.

Designing cancer prevention trials: a stochastic model approach.

There is growing interest in the design and implementation of cancer prevention trials. The key idea is to have agents which interfere with carcinogenesis and/or the preclinical stage. In this article we develop multi-stage stochastic models for the planning of cancer prevention trials. For known inputs it is possible to calculate the incidence of disease for the control and intervention groups. Consequently we find designs that balance the required sample size and follow-up time while guaranteeing prespecified error probabilities. Moreover such models can incorporate the mode of action of the intervention as well as compliance. The model has been applied to breast cancer to determine the implications for planning breast cancer intervention trials. Although the model addresses issues in cancer prevention, it is quite general and may be suitable for other chronic diseases.

Milk leakage in nonlactating women: a randomized clinical trial evaluating a polyvinyl chloride device versus disposable breast pads.

A randomized clinical trial was carried out to evaluate the safety and helpfulness of the LactaPrev System (LPS) compared with disposable pads for milk leakage management for postpartum, nonlactating women (those who do not breastfeed). Fifty-five women completed the single-blind, randomized trial. Participants wore each device on each breast concurrently. Assignment of the LPS or pad to each breast was done randomly. Fifty-eight percent of participants preferred the LPS. The longer the participation in the study, which correlated with the duration of milk leakage, the greater the preference (p = 0.05). Preference was related to bra size (p = 0.05). The smaller the bra size, the greater the preference for the LPS. There was no greater incidence of complications from the LPS compared with the disposable breast pad.

Urn sampling and the proportional hazard model.

This paper investigates the urn sampling analogue for the score statistic relating survival to covariates assuming a proportional hazard model. The exact permutation distribution can be calculated as well as the exact low order moments for arbitrary censoring patterns. The asymptotic distribution of the score statistic is an easy consequence. The method is naturally extended to deal with the multivariate case, time varying covariates and interval censoring. Finally the relationship between the censoring process, the survival times and covariates are studied considering different reference sets for the distribution of the score statistic. Some assumptions about the censoring process are investigated and as a consequence the effect of censoring is clarified.

Managing milk leakage in breastfeeding women: a clinical trial evaluating a polyvinyl chloride device versus disposable nursing pads.

The object of this clinical trial was to evaluate the effectiveness and to investigate possible problems associated with the use of a polyvinyl chloride (PVC) device ("blis") compared to a disposable nursing pad, for controlling milk leakage among nursing mothers. Seventy-one women completed the single blind, paired comparison, randomized trial. Among the 28 women having a strong early preference, 21 opted for the PVC device (p = 0.01). Of the 37 women experiencing excessive milk leakage who preferred one of the devices, 24 preferred the PVC device (p = 0.05). There was no evidence that one device caused more problems or feeding complications than the other. This study is important in alleviating anxiety about device safety while promoting breastfeeding in mothers fearful of leaking at inopportune times.

Intermediate clinical events, surrogate markers and survival.

This paper investigates one- and two-sample problems comparing survival times when an individual may experience an intermediate event prior to death or reaching some well defined endpoint. The intermediate event may be polychotomous. Patients experiencing the intermediate event may have an altered survival distribution after the intermediate event. Score tests are derived for testing if the occurrence of the intermediate event actually alters survival. These models have implications for evaluating therapies without randomization as well as strengthening the log rank test for comparing two survival distributions. The exact distribution of the score tests can be found by conditioning on both the waiting time and occurrence of the intermediate event.

Randomized consent designs for clinical trials: an update.

Randomized consent designs were introduced to make it easier for physicians to enter patients in randomized clinical trials. Physician reluctance to participate in randomized clinical trials is often a reflection that the physician-patient relationship could be compromised if the physician makes known to the patient his/her inability to select a preferred therapy. Clinical trials having a no-treatment control or placebo amplify this concern. This paper reviews the main ideas of randomized consent designs (single and double) and the statistical model underlying the analysis, and presents some recent experiences.

An investigation of a reported cancer cluster in Randolph, Massachusetts.

An increasingly common public health problem is the perception that disease incidence has increased or a cluster of disease has occurred in a community. In most cases, the disease of concern is cancer and a local hazardous waste site or other environmental problem is involved. These problems can be difficult to investigate and public health officials are frequently criticized for their inability to address community concerns. This paper reports a case study of such a situation occurring in the Barlett-Green Acres (BGA) neighborhood of Randolph, Massachusetts. Study data were obtained by interviews in households of persons belonging to a list of alleged cancer cases initially supplied by residents and supplemented using records available in town and state public health offices. One objective of the investigation was to develop methods that may be of value in similar situations arising in other communities. From a list of names compiled prior to and during the investigation, 45 incident cases of cancer were identified and found suitable for analysis. An additional four cases were added from the Massachusetts Cancer Registry. The analysis showed the existence of a cancer cluster, but overall cancer incidence and mortality in the BGA neighborhood were not elevated. Residence history, disease site, and other features of the cancer cases were investigated using methods less sensitive to incomplete reporting than total incidence. No unusual features of the cancer data other than the initiating cluster were identified and no environmental hazard likely to impact the BGA neighborhood was discovered, hence we conclude that the most likely cause of the cancer cluster was random variation in cancer rates.

State of the art in comparative cancer clinical trials.

In order to investigate the current state of the art in clinical cancer research, a survey of comparative cancer clinical trials was conducted using a MEDLINE literature search of the 6-month interval from July to December of 1985. Data were obtained primarily from the published abstracts. The major observations from the study are as follows. First, trials in cancer research are published in an extraordinarily wide range of journals covering most of the major medical specialties in addition to the many cancer specialty journals. Second, randomization is now used quite extensively. It is the predominant method of control in chemotherapy trials and in trials reported in cancer journals. However, its use is much less common in other specialties, especially surgery, so efforts to popularize randomization in these specialties would be beneficial. Third, sample sizes are highly variable, and the median sample size (96 patients) is too small to reliably detect and evaluate moderate treatment advances. Finally, our survey reveals that published trials show an inordinately large proportion of breakthroughs in treatment compared with the generally accepted view that only slow progress is being made in developing effective cancer treatments. Our view is that this result reflects the strong tendency to publish only studies with positive results. This hypothesis is supported by the fact that in nonrandom trials there tend to be more positive conclusions and an absence of a strong association between conclusions and sample size.