Objective: Body dysmorphic disorder (BDD) is a form of obsessive-compulsive disorder that may be negatively associated with the self-image. It might be associated with orthodontic treatment demand and outcome, and therefore is important. Thus, this study was conducted. Methods: The Yale-Brown ObsessiveCompulsive Scale modified for Body Dysmorphic Disorder (BDD-YBOCS) questionnaire was used in 699 orthodontic patients above 12 years of age (222 males, 477 females), at seven clinics in two cities (2020–2021). BDD diagnosis and severity were calculated based on the first 3 items and all 12 items of the questionnaire. The dental health component of the index of orthodontic treatment need (IOTN-DHC) was assessed by orthodontists. Multivariable and bivariable statistical analyses were performed on ordinal and dichotomized BDD diagnoses to assess potentially associated factors (IOTN-DHC, age, sex, marital status, education level, and previous orthodontic consultation) (α = 0.05). Results: IOTN-DHC scores 1–5 were seen in 13.0%, 39.9%, 29.8%, 12.4%, and 4.9% of patients. Age/sex/ marital status/education were not associated with IOTN-DHC (p > 0.05). Based on 3-item questionnaire, 17.02% of patients had BDD (14.02% mild). Based on 12-item questionnaire, 2.86% had BDD. BDD was more prevalent or severer in females, married patients, patients with a previous history of orthodontic consultation, and patients with milder IOTN-DHCs (p< 0.05). Conclusions IOTNDHC was negatively/slightly associated with BDD in orthodontic patients. Being female and married may increase BDD risk.

OBJECTIVES:: Investigating the survival of patients with cancer is vitally necessary for controlling the disease and for assessing treatment methods. This study aimed to compare various statistical models of survival and to determine the survival rate and its related factors among patients suffering from lung cancer. METHODS:: In this retrospective cohort, the cumulative survival rate, median survival time, and factors associated with the survival of lung cancer patients were estimated using Cox, Weibull, exponential, and Gompertz regression models. Kaplan-Meier tables and the log-rank test were also used to analyze the survival of patients in different subgroups. RESULTS:: Of 102 patients with lung cancer, 74.5% were male. During the follow-up period, 80.4% died. The incidence rate of death among patients was estimated as 3.9 (95% confidence [CI], 3.1 to 4.8) per 100 person-months. The 5-year survival rate for all patients, males, females, patients with non-small cell lung carcinoma (NSCLC), and patients with small cell lung carcinoma (SCLC) was 17%, 13%, 29%, 21%, and 0%, respectively. The median survival time for all patients, males, females, those with NSCLC, and those with SCLC was 12.7 months, 12.0 months, 16.0 months, 16.0 months, and 6.0 months, respectively. Multivariate analyses indicated that the hazard ratios (95% CIs) for male sex, age, and SCLC were 0.56 (0.33 to 0.93), 1.03 (1.01 to 1.05), and 2.91 (1.71 to 4.95), respectively. CONCLUSIONS:: Our results showed that the exponential model was the most precise. This model identified age, sex, and type of cancer as factors that predicted survival in patients with lung cancer.
Cohort Studies ; Female ; Follow-Up Studies ; Humans ; Incidence ; Iran ; Lung Neoplasms ; Lung ; Male ; Models, Statistical ; Multivariate Analysis ; Retrospective Studies ; Small Cell Lung Carcinoma ; Survival Rate

OBJECTIVES: : Investigating the survival of patients with cancer is vitally necessary for controlling the disease and for assessing treatment methods. This study aimed to compare various statistical models of survival and to determine the survival rate and its related factors among patients suffering from lung cancer. METHODS: : In this retrospective cohort, the cumulative survival rate, median survival time, and factors associated with the survival of lung cancer patients were estimated using Cox, Weibull, exponential, and Gompertz regression models. Kaplan-Meier tables and the log-rank test were also used to analyze the survival of patients in different subgroups. RESULTS: : Of 102 patients with lung cancer, 74.5% were male. During the follow-up period, 80.4% died. The incidence rate of death among patients was estimated as 3.9 (95% confidence [CI], 3.1 to 4.8) per 100 person-months. The 5-year survival rate for all patients, males, females, patients with non-small cell lung carcinoma (NSCLC), and patients with small cell lung carcinoma (SCLC) was 17%, 13%, 29%, 21%, and 0%, respectively. The median survival time for all patients, males, females, those with NSCLC, and those with SCLC was 12.7 months, 12.0 months, 16.0 months, 16.0 months, and 6.0 months, respectively. Multivariate analyses indicated that the hazard ratios (95% CIs) for male sex, age, and SCLC were 0.56 (0.33 to 0.93), 1.03 (1.01 to 1.05), and 2.91 (1.71 to 4.95), respectively. CONCLUSIONS : Our results showed that the exponential model was the most precise. This model identified age, sex, and type of cancer as factors that predicted survival in patients with lung cancer.