Understanding The Number Needed to Treat.

The number needed to treat (NNT) is the inverse of the absolute risk difference, which is used as a secondary outcome to clinical trials as a measure relevant to a positive trial, supplementing statistical significance. The NNT requires dichotomous outcomes and is influenced by the baseline disease or symptom severity, the particular population, the type and intensity of the interventional, the duration of treatment, the time period to assessment of response, and the comparator response. Confidence intervals should always accompany NNT for the precision of its estimate. In this review, three meta-analyses are reviewed, which included the NNT in the analysis of response.

A comprehensive analysis of age of onset and cumulative incidence of mental disorders: A Danish register study.

BACKGROUND: The age of onset (AOO), incidence and cumulative incidence of mental disorders are critical epidemiological measures, providing essential insights into the development and course of these disorders across the lifespan. This study aims to provide up-to-date estimates of the AOO, age-specific incidence, and cumulative incidence for a comprehensive range of mental disorders using data from Danish registers. METHODS: We conducted a follow-up study encompassing all Danish residents from January 1, 2004, to December 31, 2021, totaling 91,613,465 person-years. Data were sourced from the Danish Psychiatric Central Research Register, identifying individuals treated for various mental disorders in psychiatric hospitals, outpatient departments, and accident/emergency departments, that is, treated in secondary care settings. We investigated specific categories of mental disorders, including substance abuse disorders, schizophrenia, mood disorders, anxiety, eating disorders, borderline personality disorders, intellectual disabilities, pervasive developmental disorders, and behavioral and emotional disorders. Age-sex-specific incidence rates were estimated using Poisson generalized linear models, and cumulative incidence was calculated using Aalen-Johansen's competing risks model. The study provides estimates of AOO, incidence, and cumulative incidence for various mental disorders, including their age and sex distributions. RESULTS: The cumulative incidence by age 80 years for any mental disorder was 30.72% (95% confidence interval: 30.62%-30.83%) for males and 34.46% (34.35%-34.57%) for females. The most common types of mental disorders were anxiety-related disorders 16.27% (16.19%-16.36%) for males and 23.39% (23.29%-23.50%) for females, and followed by mood disorder 10.34% (10.27%-10.41%) for males and 16.67% (16.58%-16.77%) for females. For those who develop mental disorder, half will have developed their disorder by approximately age 22 years (median and interquartile range: males 21.37 (11.85-36.00); females 22.55 (16.31-36.08)). CONCLUSIONS: Approximately one in three individuals will seek treatment for at least one mental disorder in a secondary care setting by age 80. Given that half of these individuals develop mental disorders before age 22, it is crucial to tailor service planning to meet the specific needs of young individuals. Web-based interactive data-visualization tools are provided for clinical utility.

Predicting absolute risk for a person with missing risk factors.

We compared methods to project absolute risk, the probability of experiencing the outcome of interest in a given projection interval accommodating competing risks, for a person from the target population with missing predictors. Without missing data, a perfectly calibrated model gives unbiased absolute risk estimates in a new target population, even if the predictor distribution differs from the training data. However, if predictors are missing in target population members, a reference dataset with complete data is needed to impute them and to estimate absolute risk, conditional only on the observed predictors. If the predictor distributions of the reference data and the target population differ, this approach yields biased estimates. We compared the bias and mean squared error of absolute risk predictions for seven methods that assume predictors are missing at random (MAR). Some methods imputed individual missing predictors, others imputed linear predictor combinations (risk scores). Simulations were based on real breast cancer predictor distributions and outcome data. We also analyzed a real breast cancer dataset. The largest bias for all methods resulted from different predictor distributions of the reference and target populations. No method was unbiased in this situation. Surprisingly, violating the MAR assumption did not induce severe biases. Most multiple imputation methods performed similarly and were less biased (but more variable) than a method that used a single expected risk score. Our work shows the importance of selecting predictor reference datasets similar to the target population to reduce bias of absolute risk predictions with missing risk factors.

Predicting the risk of pancreatic cancer in women with new-onset diabetes mellitus.

BACKGROUND AND AIM: People with new-onset diabetes mellitus (diabetes) could be a possible target population for pancreatic cancer surveillance. However, distinguishing diabetes caused by pancreatic cancer from type 2 diabetes remains challenging. We aimed to develop and validate a model to predict pancreatic cancer among women with new-onset diabetes. METHODS: We conducted a retrospective cohort study among Australian women newly diagnosed with diabetes, using first prescription of anti-diabetic medications, sourced from administrative data, as a surrogate for the diagnosis of diabetes. The outcome was a diagnosis of pancreatic cancer within 3 years of diabetes diagnosis. We used prescription medications, severity of diabetes (i.e., change/addition of medication within 2 months after first medication), and age at diabetes diagnosis as potential predictors of pancreatic cancer. RESULTS: Among 99 687 women aged ≥ 50 years with new-onset diabetes, 602 (0.6%) were diagnosed with pancreatic cancer within 3 years. The area under the receiver operating curve for the risk prediction model was 0.73. Age and diabetes severity were the two most influential predictors followed by beta-blockers, acid disorder drugs, and lipid-modifying agents. Using a risk threshold of 50%, sensitivity and specificity were 69% and the positive predictive value (PPV) was 1.3%. CONCLUSIONS: Our model doubled the PPV of pancreatic cancer in women with new-onset diabetes from 0.6% to 1.3%. Age and rapid progression of diabetes were important risk factors, and pancreatic cancer occurred more commonly in women without typical risk factors for type 2 diabetes. This model could prove valuable as an initial screening tool, especially as new biomarkers emerge.

Impact of Alcohol Consumption on Breast Cancer Incidence and Mortality: The Women's Health Study.

Background: Alcohol intake is associated with breast cancer (BC) risk, but estimates of greatest public health relevance have not been quantified in large studies with long duration. Materials and Methods: In this prospective cohort study of 39,811 women (median 25 years follow-up), we examined the association between alcohol consumption and BC incidence and mortality with adjusted hazard ratios (HRs), cubic splines, absolute risks, number needed to harm (NNH), and population-attributable fractions. Results: We documented 2,830 cases of BC, including 237 BC deaths. Each additional alcoholic drink/day was associated with a 10% higher rate (HR = 1.10, 95% confidence intervals [CIs]: 1.04-1.16) of total BC in a linear manner (p = 0.0004). The higher rate was apparent for estrogen receptor (ER)+ (HR = 1.12, 95% CI: 1.06-1.18) but not ER- tumors (HR = 0.95, 95% CI: 0.82-1.10), with a statistically significant difference between these associations (p = 0.03). We constructed models comparing BC incidence among 100,000 women followed for 10 years. Compared to a scenario where all women rarely or never consumed alcohol, we expect 63.79 (95% CI: 58.35-69.24) more cases (NNH = 1,567) had all women consumed alcohol at least monthly and 278.66 (95% CI: 268.70-288.62) more cases (NNH = 358) had all women consumed >1 drink/day. Approximately 4.1% of BC cases were attributable to consumption exceeding one drink/month. Conclusion: Alcohol consumption is associated with a linear dose-response increase in BC incidence even within recommended limits of up to one alcoholic drink/day, at least for ER+ tumors. Our estimates of risk differences, attributable fraction, and NNH quantify the burden that alcohol consumption imposes on women in the general population. ClinicalTrials.gov Identifier: NCT00000479.

Cause-specific mortality in a population-level cohort of diffuse large B-cell lymphoma following chemotherapy in the early 21st century.

Diffuse large B-cell lymphoma (DLBCL) is a severe non-Hodgkin's lymphoma. Life expectancy has improved with rituximab, but cause-specific mortality data is lacking. Using the Surveillance, Epidemiology, and End Results (SEER) database to study 27,449 individuals aged 20-74 years diagnosed with primary DLBCL who received chemotherapy between 2000 and 2019, we calculated standardized mortality rate (SMR) and excess absolute risk (EAR) and examined the connection between age, sex, time after diagnosis, and cause of death. Based on 12,205 deaths, 68.7% were due to lymphoma, 20.1% non-cancer causes, and 11.2% other cancers. Non-cancer mortality rates (SMR 1.2; EAR, 21.5) increased with DLBCL compared to the general population. The leading non-cancer death causes were cardiovascular (EAR, 22.6; SMR, 1.6) and infectious (EAR, 9.0; SMR, 2.9) diseases with DLBCL. Risks for non-cancer death and solid neoplasms are highest within the first diagnosis year, then decrease. Among socioeconomic factors, being white, being married, and having a higher income were favorable factors for reducing non-cancer mortality. To improve survival, close surveillance, assessment of risk factors, and early intervention are needed.

Cardiovascular disease risk communication and prevention: a meta-analysis.

BACKGROUND AND AIMS: Knowledge of quantifiable cardiovascular disease (CVD) risk may improve health outcomes and trigger behavioural change in patients or clinicians. This review aimed to investigate the impact of CVD risk communication on patient-perceived CVD risk and changes in CVD risk factors. METHODS: PubMed, Embase, and PsycINFO databases were searched from inception to 6 June 2023, supplemented by citation analysis. Randomized trials that compared any CVD risk communication strategy versus usual care were included. Paired reviewers independently screened the identified records and extracted the data; disagreements were resolved by a third author. The primary outcome was the accuracy of risk perception. Secondary outcomes were clinician-reported changes in CVD risk, psychological responses, intention to modify lifestyle, and self-reported changes in risk factors and clinician prescribing of preventive medicines. RESULTS: Sixty-two trials were included. Accuracy of risk perception was higher among intervention participants (odds ratio = 2.31, 95% confidence interval = 1.63 to 3.27). A statistically significant improvement in overall CVD risk scores was found at 6-12 months (mean difference = -0.27, 95% confidence interval = -0.45 to -0.09). For primary prevention, risk communication significantly increased self-reported dietary modification (odds ratio = 1.50, 95% confidence interval = 1.21 to 1.86) with no increase in intention or actual changes in smoking cessation or physical activity. A significant impact on patients' intention to start preventive medication was found for primary and secondary prevention, with changes at follow-up for the primary prevention group. CONCLUSIONS: In this systematic review and meta-analysis, communicating CVD risk information, regardless of the method, reduced the overall risk factors and enhanced patients' self-perceived risk. Communication of CVD risk to patients should be considered in routine consultations.

Estimation of age of onset and progression of breast cancer by absolute risk dependent on polygenic risk score and other risk factors.

BACKGROUND: Genetic, lifestyle, reproductive, and anthropometric factors are associated with the risk of developing breast cancer. However, it is not yet known whether polygenic risk score (PRS) and absolute risk based on a combination of risk factors are associated with the risk of progression of breast cancer. This study aims to estimate the distribution of sojourn time (pre-clinical screen-detectable period) and mammographic sensitivity by absolute breast cancer risk derived from polygenic profile and the other risk factors. METHODS: The authors used data from a population-based case-control study. Six categories of 10-year absolute risk based on different combinations of risk factors were derived using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm. Women were classified into low, medium, and high-risk groups. The authors constructed a continuous-time multistate model. To calculate the sojourn time, they simulated the trajectories of subjects through the disease states. RESULTS: There was little difference in sojourn time with a large overlap in the 95% confidence interval (CI) between the risk groups across the six risk categories and PRS studied. However, the age of entry into the screen-detectable state varied by risk category, with the mean age of entry of 53.4 years (95% CI, 52.2-54.1) and 57.0 years (95% CI, 55.1-57.7) in the high-risk and low-risk women, respectively. CONCLUSION: In risk-stratified breast screening, the age at the start of screening, but not necessarily the frequency of screening, should be tailored to a woman's risk level. The optimal risk-stratified screening strategy that would improve the benefit-to-harm balance and the cost-effectiveness of the screening programs needs to be studied.

Frailty in the prediction of delirium in the intensive care unit: A secondary analysis of the Deli study.

BACKGROUND: Delirium is an acute disorder of attention and cognition with an incidence of up to 70% in the adult intensive care setting. Due to the association with significantly increased morbidity and mortality, it is important to identify who is at the greatest risk of an acute episode of delirium while being cared for in the intensive care. The objective of this study was to determine the ability of the cumulative deficit frailty index and clinical frailty scale to predict an acute episode of delirium among adults admitted to the intensive care. METHODS: This study is a secondary analysis of the Deli intervention study, a hybrid stepped-wedge cluster randomized controlled trial to assess the effectiveness of a nurse-led intervention to reduce the incidence and duration of delirium among adults admitted to the four adult intensive care units in the south-west of Sydney, Australia. Important predictors of delirium were identified using a bootstrap approach and the absolute risks, based on the cumulative deficit frailty index and the clinical frailty scale are presented. RESULTS: During the 10-mth data collection period (May 2019 and February 2020) 2566 patients were included in the study. Both the cumulative deficit frailty index and the clinical frailty scale on admission, plus age, sex, and APACHE III (AP III) score were able to discriminate between patients who did and did not experience an acute episode of delirium while in the intensive care, with AUC of 0.701 and 0.703 (moderate discriminatory ability), respectively. The addition of a frailty index to a prediction model based on age, sex, and APACHE III score, resulted in net reclassified of risk. Nomograms to individualize the absolute risk of delirium using these predictors are also presented. CONCLUSION: We have been able to show that both the cumulative deficits frailty index and clinical frailty scale predict an acute episode of delirium among adults admitted to intensive care.

The role of EPAS1 polymorphisms on COPD susceptibility in southern Chinese.

Objective: COPD is the most common chronic respiratory disease with complex environmental and genetic etiologies. It was reported that EPAS1 might participate in the occurrence and development of respiratory diseases. However, the association between EPAS1 and COPD was unclear. Methods: First, a case-control study enrolling 1130 COPD patients and 1115 healthy controls in Guangzhou was conducted to clarify the association between EPAS1 polymorphisms and COPD susceptibility. Secondly, a prevalence study recruited 882 participants in Gansu to verify the effect of positive polymorphisms on lung function. Finally, the 10-year absolute risk considering environmental factors and genetic variations was calculated by the method of Gail and Bruzzi. Results: EPAS1 rs13419896 AA genotype reduced COPD risk in southern Chinese (AA vs. GG: adjusted OR = 0.689, 95% CI = 0.498-0.955; AA vs. GG/GA: adjusted OR = 0.701, 95% CI = 0.511-0.962). Further, the rs13419896 A allele was significantly associated with higher pre-FEV1/pre-FVC in both the Guangzhou and Gansu populations (P < 0.05). Smoking status, coal as fuels, education level, and rs13419896 G > A were finally retained to develop a relative risk model for males. Smoking status, biomass as fuels, and rs13419896 G > A were retained in the female model. The population-attributable risk of the male or female model was 0.457 (0.283-0.632) and 0.421 (0.227-0.616), respectively. Conclusions: This study first revealed that EPAS1 rs13419896 G > A decreased COPD susceptibility and could be a genetic marker to predict the 10-year absolute risk for COPD.

EPO rs1617640 A>C is a Protective Factor for Chronic Obstructive Pulmonary Disease: A Case Control Study.

BACKGROUND: The occurrence and development of chronic obstructive pulmonary disease (COPD) are regulated by environmental and genetic factors. In hypoxia, Erythropoietin (EPO) satisfies the body's need for oxygen by promoting the production of red blood cells. Hypoxia was proven to be a common physiological condition in COPD progression and associated with many complications. Some studies have found that EPO is involved in the development of COPD. But the mechanism has not been fully proven. METHODS: We conducted a case-control study enrolled 1095 COPD patients and 1144 healthy controls in Guangdong Province to evaluate the association between EPO polymorphisms (rs1617640 A>C, rs507392 A>G, rs564449 G>T) and COPD susceptibility. 872 participants from southern Gansu Province were recruited to verify the effect of EPO polymorphisms on lung function. RESULTS: EPO rs1617640 C allele reduced COPD susceptibility in southern Chinese significantly (AC vs. AA: adjusted Odds ratio (OR) = 0.805, 95% CI = 0.669-0.969; AC+CC vs. AA: adjusted OR = 0.822, 95% CI = 0.689-0.980). However, there was no association between rs507392 A>G and rs564449 G>T polymorphisms and COPD susceptibility (p > 0.05). We further observed that the rs1617640 C allele was associated with higher FEV1 and FVC in Guangdong and Gansu populations significantly (both p < 0.05). In brief, the level of FEV1 and FVC increased with the C allele number. We modeled the relative risk for men and women, in which the population-attributable risks chances were 0.449 (0.258-0.641) and 0.262 (0.128-0.396) respectively. In this model, smoking status, coal as fuels, education level, and rs1617640 A>C were finally retained for males, while smoking status, biomass as fuels, and1617640 A>C were retained for females. In the end, using the method developed by Gail and Bruzzi, we fitted a 10-year absolute risk model for southern Chinese with different individual relative risks, which was presented as a table. CONCLUSIONS: In conclusion, this study found that EPO rs1617640 A>C polymorphism is associated with COPD susceptibility in southern Chinese, and the C allele was associated with better lung function. In addition, it could also be considered a genetic marker associated with environmental factors to predict the absolute 10-year risk of COPD in southern Chinese.

Self-reported walking pace and 10-year cause-specific mortality: A UK biobank investigation.

OBJECTIVE: To investigate associations of self-reported walking pace (SRWP) with relative and absolute risks of cause-specific mortality. PATIENTS AND METHODS: In 391,652 UK Biobank participants recruited in 2006-2010, we estimated sex- and cause-specific (cardiovascular disease [CVD], cancer, other causes) mortality hazard ratios (HRs) and 10-year mortality risks across categories of SRWP (slow, average, brisk), accounting for confounders and competing risk. Censoring occurred in September 30, 2021 (England, Wales) and October 31, 2021 (Scotland). RESULTS: Over a median follow-up of 12.6 years, 22,413 deaths occurred. In women, the HRs comparing brisk to slow SRWP were 0.74 (95% CI: 0.67, 0.82), 0.40 (0.33, 0.49), and 0.29 (0.26, 0.32) for cancer, CVD, and other causes of death, respectively, and 0.71 (0.64, 0.78), 0.38 (0.33, 0.44), and 0.29 (0.26, 0.32) in men. Compared to CVD, HRs were greater for other causes (women: 39.6% [6.2, 72.9]; men: 31.6% [9.8, 53.5]) and smaller for cancer (-45.8% [-58.3, -33.2] and - 45.9% [-54.8, -36.9], respectively). For all causes in both sexes, the 10-year mortality risk was higher in slow walkers, but varied across sex, age, and cause, resulting in different risk reductions comparing brisk to slow: the largest were for other causes of death at age 75 years [women: -6.8% (-7.7, -5.8); men: -9.5% (-10.6, -8.4)]. CONCLUSION: Compared to slow walkers, brisk SRWP was associated with reduced cancer (smallest reduction), CVD, and other (largest) causes of death and may therefore be a useful clinical predictive marker. As absolute risk reductions varied across age, cause, and SRWP, certain groups may particularly benefit from interventions to increase SRWP.

Risk evaluation of secondary malignancies after radiotherapy of breast cancer in light of the continuous development of planning techniques.

Secondary cancer risk is a significant concern for women treated with breast radiation therapy due to improved long-term survival rates. We evaluated the potential of new advanced automated planning algorithms together with hybrid techniques to minimize the excess absolute risk (EAR) for secondary cancer in various organs after radiation treatment for early staged breast cancer. Using CT data set of 25 patients, we generated 4 different radiation treatment plans of different complexity, including 3-dimensional conformal radiotherapy (3D-CRT), field-in-field (FinF), hybrid-IMRT (HMRT) and automated hybrid-VMAT (HVMAT) techniques. The organ-equivalent dose (OED) was calculated from differential dose-volume histograms on the basis of the "linear-exponential," "plateau," and "full mechanistic" dose-response models and was used to evaluate the EAR for secondary cancer in the contralateral breast (CB), contralateral lung (CL), and ipsilateral lung (IL). Statistical comparisons of data were performed by a Kruskal-Wallis analysis of variance. The planning objectives were fulfilled with all the planning techniques for both target coverage and organs-at-risk sparing. The differences in EAR for CB, CL and IL secondary tumor induction were not significant among the 4 techniques. For the CB and CL, the mean absolute difference did not reach 1 case of 10000 patient-years. For the IL, the mean absolute difference was up to 5 cases of 10,000 patient-years. In conclusion, the automated HVMAT technique allows an EAR reduction at the level of well-consolidated tangential 3D-CRT or FinF techniques, keeping all the HVMAT dosimetric improvements unchanged. On the basis of this analysis, the adoption of the HVMAT technique poses no increase in EAR and could be considered safe also for younger patients.

Area Dose-Response and Radiation Origin of Childhood Thyroid Cancer in Fukushima Based on Thyroid Dose in UNSCEAR 2020/2021: High 131I Exposure Comparable to Chernobyl.

The FMU and the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) concluded that the high incidence of thyroid cancer after the Fukushima nuclear accident was not the result of radiation exposure, but rather might have been overdiagnosis based on the low thyroid dose estimated in the UNSCEAR 2020/2021 report. In this study, the origin of increased PTC in Fukushima was examined based on the thyroid dose estimated by UNSCEAR. The dose-response relationship of the incidence rate per person-years (PY) was analyzed for four areas in Fukushima prefecture via regression analysis. The linear response of the annual incidence rates to thyroid dose in the first six years showed that the dominant origin of childhood thyroid cancer was radiation exposure. Excess absolute risk (EAR) proportionally increased with thyroid dose, with an EAR/104 PY Gy of 143 (95%CI: 122, 165) in the second TUE (p < 0.001), which is approximately 50-100 times higher than the EAR/104 PY Gy ≒ 2.3 observed after the Chernobyl accident. This suggests an underestimation of the thyroid dose by UNSCEAR of approximately 1/50~1/100 compared with the thyroid dose for Chernobyl. The increased childhood thyroid cancer in Fukushima was found to arise from radioactive iodine exposure, which was comparable to that in Chernobyl.

Personalised decision making to predict absolute metastatic risk in cutaneous squamous cell carcinoma: development and validation of a clinico-pathological model.

Background: Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer, affecting more than 2 million people worldwide yearly and metastasising in 2-5% of patients. However, current clinical staging systems do not provide estimates of absolute metastatic risk, hence missing the opportunity for more personalised treatment advice. We aimed to develop a clinico-pathological model that predicts the probability of metastasis in patients with cSCC. Methods: Nationwide cohorts from (1) all patients with a first primary cSCC in The Netherlands in 2007-2008 and (2) all patients with a cSCC in 2013-2015 in England were used to derive nested case-control cohorts. Pathology records of primary cSCCs that originated a loco-regional or distant metastasis were identified, and these cSCCs were matched to primary cSCCs of controls without metastasis (1:1 ratio). The model was developed on the Dutch cohort (n = 390) using a weighted Cox regression model with backward selection and validated on the English cohort (n = 696). Model performance was assessed using weighted versions of the C-index, calibration metrics, and decision curve analysis; and compared to the Brigham and Women's Hospital (BWH) and the American Joint Committee on Cancer (AJCC) staging systems. Members of the multidisciplinary Skin Cancer Outcomes (SCOUT) consortium were surveyed to interpret metastatic risk cutoffs in a clinical context. Findings: Eight out of eleven clinico-pathological variables were selected. The model showed good discriminative ability, with an optimism-corrected C-index of 0.80 (95% Confidence interval (CI) 0.75-0.85) in the development cohort and a C-index of 0.84 (95% CI 0.81-0.87) in the validation cohort. Model predictions were well-calibrated: the calibration slope was 0.96 (95% CI 0.76-1.16) in the validation cohort. Decision curve analysis showed improved net benefit compared to current staging systems, particularly for thresholds relevant for decisions on follow-up and adjuvant treatment. The model is available as an online web-based calculator (https://emc-dermatology.shinyapps.io/cscc-abs-met-risk/). Interpretation: This validated model assigns personalised metastatic risk predictions to patients with cSCC, using routinely reported histological and patient-specific risk factors. The model can empower clinicians and healthcare systems in identifying patients with high-risk cSCC and offering personalised care/treatment and follow-up. Use of the model for clinical decision-making in different patient populations must be further investigated. Funding: PPP Allowance made available by Health-Holland, Top Sector Life Sciences & Health, to stimulate public-private partnerships.

Determinants of Willingness to Undergo Lung Cancer Screening among High-Risk Current and Ex-smokers in Sabah, Malaysia: A Cross-Sectional Pilot Study.

BACKGROUND: Attitudes towards smoking, lung cancer screening, and perceived risk of lung cancer have not been widely studied in Malaysia. The primary objective of this study was to describe the factors affecting the willingness of high-risk current smokers and ex-smokers to undergo low-dose computed tomography (LDCT) screening for lung cancer. METHODS: A prospective, cross-sectional questionnaire study was conducted in current smokers or ex-smokers aged between 55 and 80 years at three hospitals in Kota Kinabalu, Sabah, Malaysia. The questionnaire recorded the following parameters: perceived lung cancer risk; Prostate Lung Colon Ovarian Cancer 2012 risk prediction model excluding race and ethnicity predictor (PLCOm2012norace); demographic characteristics; psychosocial characteristics; and attitudes towards lung cancer and lung cancer screening. RESULTS: A vast majority of the 95 respondents (94.7%) indicated their willingness to undergo screening. Stigma of lung cancer, low levels of knowledge about lung cancer symptoms, concerns about financial constraints, and a preference for traditional medication were still prevalent among the respondents, and they may represent potential barriers to lung cancer screening uptake. A desire to have an early diagnosis (odds ratio [OR], 11.33; 95% confidence interval [CI], 1.53 to 84.05; p=0.02), perceived time constraints (OR, 3.94; 95% CI, 1.32 to 11.73; p=0.01), and proximity of LDCT screening facilities (OR, 14.33; 95% CI, 1.84 to 111.4; p=0.01) had significantly higher odds of willingness to undergo screening. CONCLUSION: Although high-risk current smokers and ex-smokers are likely to undergo screening for lung cancer, several psychosocial barriers persist. The results of this study may guide the policymakers and clinicians regarding the need to improve lung cancer awareness in our population.

Evidence supporting the choice of a new cardiovascular risk equation for Australia.

This article reviews the risk equations recommended for use in international cardiovascular disease (CVD) primary prevention guidelines and assesses their suitability for use in Australia against a set of a priori defined selection criteria. The review and assessment were commissioned by the National Heart Foundation of Australia on behalf of the Australian Chronic Disease Prevention Alliance to inform recommendations on CVD risk estimation as part of the 2023 update of the Australian CVD risk assessment and management guidelines. Selected international risk equations were assessed against eight selection criteria: development using contemporary data; inclusion of established cardiovascular risk factors; inclusion of ethnicity and deprivation measures; prediction of a broad selection of fatal and non-fatal CVD outcomes; population representativeness; model performance; external validation in an Australian dataset; and the ability to be recalibrated or modified. Of the ten risk prediction equations reviewed, the New Zealand PREDICT equation met seven of the eight selection criteria, and met additional usability criteria aimed at assessing the ability to apply the risk equation in practice in Australia.

A practitioner's guide to developing critical appraisal skills: How to interpret the magnitude of clinical study results.

BACKGROUND: In the oral health literature, researchers sometimes report measures of association that are inappropriate for their study design. Clinicians using evidence to inform their practice should be able to interpret clinical study results on the basis of the types of measures of association, independent of what the researchers of a study reported. TYPES OF STUDIES REVIEWED: The authors summarized which measures of association can be derived from experimental and observational studies and how to interpret them in the context of different study designs. They also suggested how inferences can be made on the basis of particular designs. RESULTS: Measures of association derived from randomized controlled trials and cohort studies differ from those of case-control and cross-sectional studies. These differences can be attributed to the temporality between exposures and outcomes inherent in the respective study designs. Different measures of association reported from the same study may lead to different clinical decisions. Furthermore, the same measure of association with the same effect estimate derived from different study designs may contribute to different clinical decisions. CONCLUSIONS AND PRACTICAL IMPLICATIONS: Measures of association should be interpreted in the context of a particular study design. Study designs and specific measures of association should be considered when drawing conclusions from clinical studies. Clinicians using the literature to inform practice should be cognizant of measures of association reported for a particular study design and whether the authors have interpreted the measure of association correctly in the context of their chosen study design.

Estimation of the risk of secondary cancer in rectum and bladder after radiation therapy for prostate cancer using a feasibility dose-volume histogram.

We investigated the risk of secondary cancers in rectum and bladder for prostate cancer radiotherapy using a feasibility assessment tool. We calculated the risk of secondary cancer by generating a dose-volume histogram based on an ideal dose falloff function (f-value). This study found a smaller f-value was associated with a lower secondary cancer risk in the rectum but a higher risk in the bladder. The study suggests setting the f-value at 0-0.1 as the optimization goal for the rectum and 0.4 for the bladder is reasonable and feasible for reducing the risk of secondary cancer and other adverse events.

Comparative dosimetric and radiobiological assessment of left-sided whole breast and regional nodes with advanced radiotherapy techniques.

The aim of this study was to analyze the dosimetric and radiobiologic differences of the left-sided whole breast and regional nodes in intensity-modulated radiotherapy (IMRT), volume-modulated arc therapy (VMAT), and helical tomotherapy (HT).  The IMRT, VMAT, and HT plans in this study were generated for thirty-five left-sided breast cancer patients after breast-conserving surgery (BCS). The planning target volume (PTV) included the whole breast and supraclavicular nodes. PTV coverage, homogeneity index (HI), conformity index (CI), dose to organs at risk (OARs), secondary cancer complication probability (SCCP), and excess absolute risk (EAR) were used to evaluate the plans. Compared to IMRT, the VMAT and HT plans resulted in higher PTV coverage and homogeneity. The VMAT and HT plans also delivered a lower mean dose to the ipsilateral lung (9.19 ± 1.36 Gy, 9.48 ± 1.17 Gy vs. 11.31 ± 1.42 Gy) and heart (3.99 ± 0.86 Gy, 4.48 ± 0.62 Gy vs. 5.53 ± 1.02 Gy) and reduced the V5Gy, V10Gy, V20Gy, V30Gy, and V40Gy of the ipsilateral lung and heart. The SCCP and EAR for the ipsilateral lung were reduced by 3.67%, 3.09% in VMAT, and 22.18%, 19.21% in HT, respectively. While were increased for the contralateral lung and breast. This study showed that VMAT plans provide a more homogeneous dose distribution to the PTV, minimizing exposure to ipsilateral structures and significantly reducing SCCP and EAR, and slightly increasing dose to contralateral structures. Overall, the VMAT plan can be considered a beneficial technique for BCS patients whose PTV includes the whole breast and regional nodes.