Smoking cessation advice from healthcare professionals helps those in the contemplation and preparation stage: An application with transtheoretical model underpinning in a community-based program.

INTRODUCTION: The efficacy of smoking cessation intervention has been proven with randomized controlled trials. Our study aims to elucidate the effects of the delivery method of smoking cessation advice on the process of stage of changes with transtheorectical model underpinning in a community setting. METHODS: A total of 436 subjects were recruited in a quasi-experimental untreated control design study, with 46 receiving advice from healthcare professionals (HCP group) and 390 in the control group, in 2003, Nantou, Taiwan. A discrete time Markov model was used to quantify the multi-state process of smoking cessation in light of the transtheorectical model. Multiple polytomous logistic regression models were simultaneously applied to different transitions. RESULTS: The estimated forward transition probabilities were higher in the HCP group compared to their counterparts in the control group. On the other hand, the backward transition probabilities were smaller in the HCP group. After adjusting for confounding factors, HCP had a 4.3-fold (95% CI: 2.21-8.46) odds ratio of moving forward from the contemplation stage, and 2.4-fold odds ratio (95% CI: 1.03-4.42) from the preparation stage. Elderly people were more reluctant to change from precontemplation (AOR=0.50; 95% CI: 0.34-0.74) and contemplation (AOR=0.58; 95% CI: 0.44-0.84), but once in the preparation stage, they were more likely to take action (AOR=1.28; 95% CI: 1.01-1.83). For those in the preparation stage, longer smoking years had a negative effect on taking action (AOR=0.74; 95% CI: 0.52-0.99), but cessation advice from others enhanced the likelihood to take action (AOR=1.36; 95% CI: 1.01-1.99). CONCLUSIONS: The direct advice on smoking cessation from healthcare professionals enforced the net forward transition towards smoking cessation, especially the transition from contemplation and preparation. The proposed Markov regression model assessed the net effect of different intervention approaches allowing for the simultaneous consideration of multiple transitions and the effects of other confounders.

A Proposal to Unify the Classification of Breast and Prostate Cancers Based on the Anatomic Site of Cancer Origin and on Long-term Patient Outcome.

The similarity between the structure and function of the breast and prostate has been known for a long time, but there are serious discrepancies in the terminology describing breast and prostate cancers. The use of the large, thick-section (3D) histology technique for both organs exposes the irrationality of the breast cancer terminology. Pathologists with expertise in diagnosing prostate cancer take the anatomic site of cancer origin into account when using the terms AAP (acinar adenocarcinoma of the prostate) and DAP (ductal adenocarcinoma of the prostate) to distinguish between the prostate cancers originating primarily from the fluid-producing acinar portion of the organ (AAP) and the tumors originating either purely from the larger ducts (DAP) or from both the acini and the main ducts combined (DAP and AAP). Long-term patient outcome is closely correlated with the terminology, because patients with DAP have a significantly poorer prognosis than patients with AAP. The current breast cancer terminology could be improved by modeling it after the method of classifying prostate cancer to reflect the anatomic site of breast cancer origin and the patient outcome. The long-term survival curves of our consecutive breast cancer cases collected since 1977 clearly show that the non-palpable, screen-detected breast cancers originating from the milk-producing acini have excellent prognosis, irrespective of their histologic malignancy grade or biomarkers. Correspondingly, the breast cancer subtypes of truly ductal origin have a significantly poorer outcome, despite recent improvements in diagnosis and therapy. The mammographic appearance of breast cancers reflects the underlying tissue structure. Addition of these "mammographic tumor features" to the currently used histologic phenotypes makes it possible to distinguish the breast cancer cases of ductal origin with a poor outcome, termed DAB (ductal adenocarcinoma of the breast), from the more easily managed breast cancers of acinar origin, termed AAB (acinar adenocarcinoma of the breast), which have a significantly better outcome. This simple and easily communicable terminology could lead to better communication between the diagnostic and therapeutic team members and result in more rational treatment planning for the benefit of their patients.

Analytical decision model for sample size and effectiveness projections for use in planning a population-based randomized controlled trial of colorectal cancer screening.

RATIONALE, AIMS AND OBJECTIVES: Population-based randomized controlled trials (RCTs) often involve enormous costs and long-term follow-up to evaluate primary end points. Analytical decision-simulated model for sample size and effectiveness projections based on primary and surrogate end points are necessary before planning a population-based RCT. METHOD: Based on the study design similar to two previous RCTs, transition rates were estimated using a five-state natural history model [normal, preclinical detection phase (PCDP) Dukes' A/B, PCDP Dukes' C/D, Clinical Dukes' A/B and Clinical Dukes' C/D]. The Markov cycle tree was assigned transition parameters, variables related to screening and survival rate that simulated results of 10-year follow-up in the absence of screening for a hypothetical cohort aged 45-74 years. The corresponding screened arm was to simulate the results after the introduction of population-based screening for colorectal cancer with fecal occult blood test with stop screen design. RESULTS: The natural course of mean sojourn time for five-state Markov model were estimated as 2.75 years for preclinical Dukes' A/B and 1.38 years for preclinical Dukes' C/D. The expected reductions in mortality and Dukes' C/D were 13% (95% confidence intervals: 7-19%) and 26% (95% confidence intervals: 20-32%), respectively, given a 70% acceptance rate and a 90% colonoscopy referral rate. Sample sizes required were 86,150 and 65,592 subjects for the primary end point and the surrogate end point, respectively, given an incidence rate up to 0.0020 per year. CONCLUSIONS: The sample sizes required for primary and surrogate end points and the projection of effectiveness of fecal occult blood test for colorectal cancer screening were developed. Both are very important to plan a population-based RCT.