The epidemiology of gastrointestinal stromal tumors in Taiwan, 1998–2008: a nation-wide cancer registry-based study

BACKGROUND: To investigate the incidence of gastrointestinal stromal tumors (GISTs) in Taiwan and the impact of imatinib on the overall survival (OS) of GIST patients. METHODS: GISTs were identified from the Taiwan Cancer Registry (TCR) from 1998 to 2008. The age-adjusted incidence rates and the observed OS rates were calculated. Cox proportional hazards models were applied to examine the mortality risk in three time periods (1998–2001, 2002–2004, 2005–2008) according to the application and availability of imatinib. RESULTS: From 1998 to 2008, 2,986 GISTs were diagnosed in Taiwan. The incidence increased from 1.13 per 100,000 in 1998 to 1.97 per 100,000 in 2008. The most common sites were stomach (47-59%), small intestine (31-38%), and colon/rectum (6-9%). The 5-year observed OS was 66.5% (60.3% for men, 74.2% for women, P < .0001). GISTs in the stomach had a better 5-year observed OS (69.4%) than those in the small intestine (65.1%) (P < .0001). The outcome of GIST improved significantly after the more widespread use of imatinib; the 5-year observed OS increased from 58.9% during 1998–2001 to 70.2% during 2005–2008 (P < .0001). Younger age, female sex, stomach location, and later diagnostic years were independent predictors of a better survival. CONCLUSIONS: The incidence of GIST has been increasing in Taiwan, partially due to the advancement of diagnostic technology/method and the increased awareness by physicians. The outcome of GIST has improved significantly with the availability and the wider use of imatinib

Peer Pressure, Psychological Distress and the Urge to Smoke

Background: Psychology and addiction research have found that cigarette smokers react with subjective and automatic responses to stimuli associated with smoking. This study examines the association between the number of cigarettes smokers consume per month and their response to cues derived from peer and psychological distress. Methods: We studied 1,220 adult past and current smokers drawn from a national face-to-face interview survey administered in 2004. We defined two types of cues possibly triggering a smoker to have a cigarette: peer cues and psychological cues. We used ordinary least square linear regressions to analyze smoking amount and response to peer and psychological distress cues. Results: We found a positive association between amount smoked and cue response: peer cues (1.06, 95%CI: 0.74-1.38) and psychological cues (0.44, 95%CI = 0.17-0.70). Response to psychological cues was lower among male smokers (–1.62, 95%CI = –2.26- –0.98), but response to psychological cues were higher among those who had senior high school level educations (0.96, 95%CI = 0.40-1.53) and who began smoking as a response to their moods (1.25, 95%CI = 0.68-1.82). Conclusions: These results suggest that both peer cues and psychological cues increase the possibility of contingent smoking, and should, therefore, be addressed by anti-smoking policies and anti-smoking programs. More specifically, special attention can be paid to help smokers avoid or counter social pressure to smoke and to help smokers resist the use of cigarettes to relieve distress

Diffusion patterns of new anti-diabetic drugs into hospitals in Taiwan: the case of Thiazolidinediones for diabetes

<p>Abstract</p> <p>Background</p> <p>Diffusion of new drugs in the health care market affects patients' access to new treatment options and health care expenditures. We examined how a new drug class for diabetes mellitus, thiazolidinediones (TZDs), diffused in the health care market in Taiwan.</p> <p>Methods</p> <p>Assuming that monthly hospital prescriptions of TZDs could serve as a micro-market to perform drug penetration studies, we retrieved monthly TZD prescription data for 580 hospitals in Taiwan from Taiwan's National Health Insurance Research Database for the period between March 1, 2001 and December 31, 2005. Three diffusion parameters, time to adoption, speed of penetration (monthly growth on prescriptions), and peak penetration (maximum monthly prescription) were evaluated. Cox proportional hazards model and quantile regressions were estimated for analyses on the diffusion parameters.</p> <p>Results</p> <p>Prior hospital-level pharmaceutical prescription concentration significantly deterred the adoption of the new drug class (HR: 0.02, 95%CI = 0.01 to 0.04). Adoption of TZDs was slower in district hospitals (HR = 0.43, 95%CI = 0.24 to 0.75) than medical centers and faster in non-profit hospitals than public hospitals (HR = 1.79, 95%CI = 1.23 to 2.61). Quantile regression showed that penetration speed was associated with a hospital's prior anti-diabetic prescriptions (25%Q: 18.29; 50%Q: 25.57; 75%Q: 30.97). Higher peaks were found in hospitals that had adopted TZD early (25%Q: -40.33; 50%Q: -38.65; 75%Q: -32.29) and in hospitals in which the drugs penetrated more quickly (25%Q: 16.53; 50%Q: 24.91; 75%Q: 31.50).</p> <p>Conclusions</p> <p>Medical centers began to prescribe TZDs earlier, and they prescribed more TZDs at a faster pace. The TZD diffusion patterns varied among hospitals depending accreditation level, ownership type, and prescription volume of Anti-diabetic drugs.</p

Diffusion patterns of new anti-diabetic drugs into hospitals in Taiwan: the case of Thiazolidinediones for diabetes

<p>Abstract</p> <p>Background</p> <p>Diffusion of new drugs in the health care market affects patients' access to new treatment options and health care expenditures. We examined how a new drug class for diabetes mellitus, thiazolidinediones (TZDs), diffused in the health care market in Taiwan.</p> <p>Methods</p> <p>Assuming that monthly hospital prescriptions of TZDs could serve as a micro-market to perform drug penetration studies, we retrieved monthly TZD prescription data for 580 hospitals in Taiwan from Taiwan's National Health Insurance Research Database for the period between March 1, 2001 and December 31, 2005. Three diffusion parameters, time to adoption, speed of penetration (monthly growth on prescriptions), and peak penetration (maximum monthly prescription) were evaluated. Cox proportional hazards model and quantile regressions were estimated for analyses on the diffusion parameters.</p> <p>Results</p> <p>Prior hospital-level pharmaceutical prescription concentration significantly deterred the adoption of the new drug class (HR: 0.02, 95%CI = 0.01 to 0.04). Adoption of TZDs was slower in district hospitals (HR = 0.43, 95%CI = 0.24 to 0.75) than medical centers and faster in non-profit hospitals than public hospitals (HR = 1.79, 95%CI = 1.23 to 2.61). Quantile regression showed that penetration speed was associated with a hospital's prior anti-diabetic prescriptions (25%Q: 18.29; 50%Q: 25.57; 75%Q: 30.97). Higher peaks were found in hospitals that had adopted TZD early (25%Q: -40.33; 50%Q: -38.65; 75%Q: -32.29) and in hospitals in which the drugs penetrated more quickly (25%Q: 16.53; 50%Q: 24.91; 75%Q: 31.50).</p> <p>Conclusions</p> <p>Medical centers began to prescribe TZDs earlier, and they prescribed more TZDs at a faster pace. The TZD diffusion patterns varied among hospitals depending accreditation level, ownership type, and prescription volume of Anti-diabetic drugs.</p

The association between medical risk factors and cholangiocarcinoma by disease sites.

a<p>Oa. dds ratio (OR), 95% confidence interval (CI), and p-value were derived using conditional logistic regression with age, sex, and the time of diagnosis (reference date for the controls) as matching variables.</p

Results of the association between medical risk factors and cholangiocarcinoma stratified by sex and age, statistically significant interaction only (p<0.05).

a<p>Odds ratio (OR), 95% confidence interval (CI), and interaction p-values were derived using conditional logistic regression with age, sex, and the time of diagnosis (reference date for the controls) as matching variables.</p

Multivariable analysis adjusted for possible intermediate factors for the association between selected medical risk factors and cholangiocarcinoma by disease sites.

a<p>Odds ratio (OR) and 95% confidence interval (CI) were derived using conditional logistic regression with age, sex, and the time of diagnosis (reference date for the controls) as matching variables.</p>b<p>Odds ratio (OR) and 95% confidence interval (CI) were derived using conditional logistic regression with age, sex, and the time of diagnosis (reference date for the controls) as matching variables and adjusted for possible intermediate factors.</p

Distributions of age and sex of the study subjects.

<p>Distributions of age and sex of the study subjects.</p

Second cancers in patients with neuroendocrine tumors.

BACKGROUND: Second cancers have been reported to occur in 10-20% of patients with neuroendocrine tumors (NETs). However, most published studies used data from a single institution or focused only on specific sites of NETs. In addition, most of these studies included second cancers diagnosed concurrently with NETs, making it difficult to assess the temporality and determine the exact incidence of second cancers. In this nationwide population-based study, we used data recorded by the Taiwan Cancer Registry (TCR) to analyze the incidence and distribution of second cancers after the diagnosis of NETs. METHODS: NET cases diagnosed from January 1, 1996 to December 31, 2006 were identified from the TCR. The data on the occurrence of second cancers were ascertained up to December 31, 2008. Standardized incidence ratios (SIRs) of second cancers were calculated based on the cancer incidence rates of the general population. Cox-proportional hazards regression analysis was performed to estimate the hazard ratio (HR) and 95% confidence interval (CI) for the risk of second cancers associated with sex, age, and primary NET sites. RESULTS: A total of 1,350 newly diagnosed NET cases were identified according to the selection criteria. Among the 1,350 NET patients, 49 (3.63%) developed a second cancer >3 months after the diagnosis of NET. The risk of second cancer following NETs was increased compared to the general population (SIR = 1.48, 95% CI: 1.09-1.96), especially among those diagnosed at age 70 or older (HR = 5.08, 95% CI = 1.69-15.22). There appeared to be no preference of second cancer type according to the primary sites of NETs. CONCLUSIONS: Our study showed that the risk of second cancer following NETs is increased, especially among those diagnosed at age 70 or older. Close monitoring for the occurrence of second cancers after the diagnosis of NETs is warranted