Development of an Automatic Rule-Based Algorithm for the Detection of Ovarian Cancer Recurrence From Electronic Health Records.

PURPOSE: As the onset of cancer recurrence is not explicitly recorded in the electronic health record (EHR), a high volume of manual chart review is required to detect the cancer recurrence. This study aims to develop an automatic rule-based algorithm for detecting ovarian cancer (OC) recurrence on the basis of minimally preprocessed EHR data. METHODS: The automatic rule-based recurrence detection algorithm (Auto-Recur), using notes on image reading (positron emission tomography-computed tomography [PET-CT], CT, magnetic resonance imaging [MRI]), biomarker (CA125), and treatment information (surgery, chemotherapy, radiotherapy), was developed to detect the first OC recurrence. Auto-Recur contains three single algorithms (images, biomarkers, treatments) and hybrid algorithms (combinations of the single algorithms). The performance of Auto-Recur was assessed using sensitivity, specificity, and accuracy of the recurrence time detected. The recurrence-free survival probabilities were estimated and compared with the retrospective chart review results. RESULTS: The proposed Auto-Recur considerably reduced human resources and time; it saved approximately 1,340 days when scaled to 100,000 patients compared with the conventional retrospective chart review. The hybrid algorithm on the basis of a combination of image, biomarker, and treatment information was the most efficient (sensitivity: 93.4%, specificity: 97.4%) and precisely captured recurrence time (average time error: 8.5 days). The estimated 3-year recurrence-free survival probability (44%) was close to the estimates by the retrospective chart review (45%, log-rank P value = .894). CONCLUSION: Our rule-based algorithm effectively captured the first OC recurrence from large-scale EHR while closely approximating the recurrence-free survival estimates obtained by conventional retrospective chart reviews. The study findings facilitate large-scale EHR analysis, enhancing clinical research opportunities.

Socioeconomic inequality in health-related quality of life among Korean adults with chronic disease: an analysis of the Korean Community Health Survey.

OBJECTIVES: Health-related quality of life is crucial for people dealing with chronic illness. This study investigated the quality of life in individuals with 5 common chronic conditions in Korea. We also analyzed socioeconomic factors such as education, income, occupation, and urbanization to identify determinants of inequality. METHODS: Using 2016 Korea Community Health Survey data, we examined individuals aged 30 or older with chronic diseases (diabetes, hypertension, cardiovascular disease, hyperlipidemia, arthritis) using the EuroQol 5-Dimension 3 Level tool. We analyzed the associations between socioeconomic factors (education, income, occupation, urbanization) and quality of life using descriptive statistics and regression analysis. Inequality indices (relative inequality index, absolute inequality index) were used to measure inequality in quality of life. RESULTS: Individuals with higher income levels showed a 1.95-fold higher likelihood of a better quality of life than those with the lowest income. The lowest income group had higher odds of mobility (adjusted odds ratio [aOR], 2.2), self-care (aOR, 2.1), activity limitations (aOR, 2.4), pain/discomfort (aOR, 1.8), and anxiety/depression (aOR, 2.3). Educational disparities included a 3-fold increase in mobility and daily activity problems for those with elementary or lower education. Well-educated participants had a 1.94 times higher quality of life, with smaller differences in anxiety/depression and self-management. The income gap accounted for 14.1% of variance in quality-of-life disparities. CONCLUSIONS: Addressing socioeconomic disparities in the quality of life for individuals with chronic diseases necessitates tailored interventions and targeted health policies. This research informs policymakers in developing focused initiatives to alleviate health inequities. It emphasizes the importance of mental health support and ensuring affordable, accessible healthcare services.

Risk factors for colorectal cancer in a fecal immunochemical test-positive group: The National Health Insurance Service-National Health Screening Cohort.

BACKGROUND AND AIM: Colorectal cancer (CRC) was the fourth most common cancer in Republic of Korea in 2019. It has a gradually increasing mortality rate, indicating the importance of screening for CRC. Among the various CRC screening test, fecal immunochemical test (FIT) is a simple yet most commonly used. Neverthelss, there have been only few long-term studies on subjects with FIT-positive. Therefore, in this study, we aimed to investigate the risk factors for CRC in FIT-positive patients using the National Health Insurance Service Bigdata database. METHODS: Among 1 737 633 individuals with a FIT screening result for CRC in 2009, 101 143 (5.82%) were confirmed to be FIT positive. The CRC incidence over 10 years (up to 2018) of these participants was investigated using the National Cancer Registry. RESULTS: Out of the 101 143 FIT-positive participants, 4395 (4.35%) were diagnosed with CRC. The FIT-positive patients who underwent a second round of screening showed a 5-year cumulative CRC incidence of approximately 1.25%, whereas those who did not showed an incidence of approximately 3.75%. Among the FIT-positive patients, the CRC incidence in the non-compliance group for the second round of screening was 2.8 times higher than that in the compliance group. CONCLUSIONS: In FIT-positive participants, non-compliance with the second round of screening was identified as a major risk factor for CRC development. It is necessary to establish appropriate strategies for managing risk factors for CRC in FIT-positive patients to increase the rate of compliance with the second round of CRC screening.

Treatment-related cardiovascular events in patients with non-small cell lung cancer: Evidence from real-world data with a competing risks approach.

BACKGROUND: Understanding cancer treatment-related cardiovascular (CV) events is important for cancer care; however, comprehensive evaluation of CV events in patients with lung cancer is limited. This study aimed to assess the cumulative incidence and associated risks of various CV event types in patients with non-small cell lung cancer (NSCLC). METHODS: A total of 7868 individuals aged 40 years and older, recently diagnosed with NSCLC (2007-2018), were assessed with data obtained from the National Cancer Center, Korea. This study included nine types of CV events. A 2-year cumulative incidence function (CIF) of CV events was estimated, with death as a competing event. The associated risks were assessed by subdistribution hazard ratio (sHR) in the Fine-Gray competing risks model. RESULTS: CV events were observed in 7.8% of patients with NSCLC, with the most frequently observed types being atrial fibrillation and flutter (AF) (2.7%), venous thromboembolic disease (2.0%), and cerebrovascular disease (CeVD) (1.5%). Overall, all CV events were highest in the group treated with systemic therapy (CIF, 10.6%; 95% confidence interval [CI], 9.5%-11.8%), followed by those treated with surgery (CIF, 10.0%; 95% CI, 8.6%-11.6%); the incidence of AF (CIF, 5.7%; 95% CI, 4.6%-7.0%) was highest in patients treated with surgery. Individuals treated with systemic therapy were found to exhibit a higher CeVD risk than those treated with surgery (sHR, 4.12; 95% CI, 1.66-10.23). Among the patients who underwent surgery, those with lobectomy and pneumonectomy had a higher AF risk (vs. wedge resection/segmentectomy; sHR, 7.79; 95% CI, 1.87-32.42; sHR, 8.10; 95% CI, 1.60-40.89). CONCLUSIONS: These findings revealed treatment-related CV event risks in patients with NSCLC, which suggests that the risk of AF in surgery and CeVD in systemic therapy should be paid more attention to achieve a better prognosis and improve cancer survivorship outcomes. PLAIN LANGUAGE SUMMARY: Atrial fibrillation and flutter (AF) is the most common cardiovascular event, particularly at a high risk in patients with non-small cell lung cancer (NSCLC) undergoing surgery. Patients receiving surgery with poor performance status, diagnosed with regional stage, and undergoing lobectomy or pneumonectomy are at a high risk of AF. Systemic/radiotherapy is associated with cerebrovascular and ischemic heart disease in patients with NSCLC.

Prevalence of pre-existing lung diseases and their association with income level among patients with lung cancer: a nationwide population-based case-control study in South Korea.

BACKGROUND: This study aimed to estimate the prevalence of pre-existing lung diseases in patients with lung cancer compared to people without lung cancer and examine the association between income levels and pre-existing lung diseases. METHODS: Data on patients with lung cancer (case) and the general population without lung cancer (non-cancer controls) matched by age, sex and region were obtained from the Korea National Health Insurance Service-National Health Information Database (n=51 586). Insurance premiums were divided into quintiles and medicaid patients. Conditional logistic regression models were used to examine the association between pre-existing lung diseases and the risk of lung cancer. The relationship between income level and the prevalence of pre-existing lung disease among patients with lung cancer was analysed using logistic regression models. RESULTS: The prevalence of asthma (17.3%), chronic obstructive lung disease (COPD) (9.3%), pneumonia (9.1%) and pulmonary tuberculosis (1.6%) in patients with lung cancer were approximately 1.6-3.2 times higher compared with the general population without lung cancer. A significantly higher risk for lung cancer was observed in individuals with pre-existing lung diseases (asthma: OR=1.36, 95% CI 1.29 to 1.44; COPD: 2.11, 95% CI 1.94 to 2.31; pneumonia: 1.49, 95% CI 1.38 to 1.61; pulmonary tuberculosis: 2.16, 95% CI 1.75 to 2.66). Patients with lung cancer enrolled in medicaid exhibited higher odds of having pre-existing lung diseases compared with those in the top 20% income level (asthma: OR=1.75, 95% CI 1.56 to 1.96; COPD: 1.91, 95% CI 1.65 to 2.21; pneumonia: 1.73, 95% CI 1.50 to 2.01; pulmonary tuberculosis: 2.45, 95% CI 1.78 to 3.36). CONCLUSIONS: Pre-existing lung diseases were substantially higher in patients with lung cancer than in the general population. The high prevalence odds of pre-existing lung diseases in medicaid patients suggests the health disparity arising from the lowest income group, underscoring a need for specialised lung cancer surveillance.

Health-related quality of life in long-term early-stage breast cancer survivors compared to general population in Korea.

PURPOSE: This study assessed health-related quality of life (HRQoL) of long-term breast cancer (BC) survivors diagnosed at early stages and compare with cancer-free, age-matched women. METHODS: The study population included BC survivors diagnosed with ductal carcinoma in situ (DCIS) or breast cancer stages I-II, who had undergone lumpectomy/mastectomy, with time since diagnosis ranging from 9 to 16 years. Survey was conducted at two tertiary hospitals in 2020. Data for cancer-free female controls was randomly drawn from a population-based survey and age-, education-matched with 1 case: 3 controls ratio. Self-reported HRQoL was assessed using EQ-5D with five dimentions. EQ-5D utility index score was calculated. Difference in EQ-5D score was evaluated using the Tobit regression model with adjustment for other covariates. RESULTS: Of 273 survivors. 88% and 12% underwent mastectomy and lumpectomy, respectively. The mean (standard deviation, SD) age at survey was 57.3 (8.5) years old. BC survivors reported significantly more problems performing daily activities (11% vs. 5%, p < 0.001), pain/discomfort (46% vs. 23%, p < 0.001), and anxious/depressed feelings (44% vs. 8%, p < 0.001) relative to the controls. Difference in EQ-5D score between BC survivors and the general population was higher in older age groups. The overall EQ-5D score of BC survivors was statistically lower than that of the control subjects (adjusted [Formula: see text]=0.117, p < 0.001). CONCLUSION: Long-term BC survivors who survived beyond ten years post-diagnosis experience more pain, anxiety, and distress, leading to an overall poorer HRQoL. IMPLICATIONS FOR CANCER SURVIVORS: This study suggest the importance of follow-up care, particularly focusing on pain, anxiety, and distress management to enhance the HRQoL of long-term BC survivors.

Key Points for Clinicians About the SEER Oral Cancer Survival Calculator.

Importance: In the setting of a new cancer diagnosis, the focus is usually on the cancer as the main threat to survival, but people may have other conditions that pose an equal or greater threat to their life than their cancer: a competing risk of death. This is especially true for patients who have cancer of the oral cavity, because prolonged exposure to alcohol and tobacco are risk factors for cancer in this location but also can result in medical conditions with the potential to shorten life expectancy, competing as a cause of death that may intervene in conjunction with or before the cancer. Observations: A calculator designed for public use has been released that allows patients age 20 to 86 years who have a newly diagnosed oral cancer to obtain estimates of their health status-adjusted age, life expectancy in the absence of the cancer, and probability of surviving, dying of the cancer, or dying of other causes within 1 to 10 years after diagnosis. The models in the calculator showed that patients with oral cavity cancer had a higher than average risk of death from other causes than the matched US population, and this risk increases by stage. Conclusions and Relevance: The Surveillance, Epidemiology and End Results Program Oral Cancer Survival Calculator supports a holistic approach to the life of the patient, and the risk of death of other causes is treated equally to consideration of the probability of death of the cancer. This tool may be usefully paired with the other available prognostic calculators for oral cancer and is an example of the possibilities now available with registry linkages to partially overlapping or independent data sets and statistical techniques that allow the use of 2 time scales in 1 analysis.

A New Personalized Oral Cancer Survival Calculator to Estimate Risk of Death From Both Oral Cancer and Other Causes.

Importance: Standard cancer prognosis models typically do not include much specificity in characterizing competing illnesses or general health status when providing prognosis estimates, limiting their utility for individuals, who must consider their cancer in the context of their overall health. This is especially true for patients with oral cancer, who frequently have competing illnesses. Objective: To describe a statistical framework and accompanying new publicly available calculator that provides personalized estimates of the probability of a patient surviving or dying from cancer or other causes, using oral cancer as the first data set. Design, Setting, and Participants: The models used data from the Surveillance, Epidemiology, and End Results (SEER) 18 registry (2000 to 2011), SEER-Medicare linked files, and the National Health Interview Survey (NHIS) (1986 to 2009). Statistical methods developed to calculate natural life expectancy in the absence of the cancer, cancer-specific survival, and other-cause survival were applied to oral cancer data and internally validated with 10-fold cross-validation. Eligible participants were aged between 20 and 94 years with oral squamous cell carcinoma. Exposures: Histologically confirmed oral cancer, general health status, smoking, and selected serious comorbid conditions. Main Outcomes and Measures: Probabilities of surviving or dying from the cancer or from other causes, and life expectancy in the absence of the cancer. Results: A total of 22 392 patients with oral squamous cell carcinoma (13 544 male [60.5%]; 1476 Asian and Pacific Islander [6.7%]; 1792 Black [8.0%], 1589 Hispanic [7.2%], 17 300 White [78.1%]) and 402 626 NHIS interviewees were included in this calculator designed for public use for patients ages 20 to 86 years with newly diagnosed oral cancer to obtain estimates of health status-adjusted age, life expectancy in the absence of the cancer, and the probability of surviving, dying from the cancer, or dying from other causes within 1 to 10 years after diagnosis. The models in the calculator estimated that patients with oral cancer have a higher risk of death from other causes than their matched US population, and that this risk increases by stage. Conclusions and relevance: The models developed for the calculator demonstrate that survival estimates that exclude the effects of coexisting conditions can lead to underestimates or overestimates of survival. This new calculator approach will be broadly applicable for developing future prognostic models of cancer and noncancer aspects of a person's health in other cancers; as registries develop more linkages, available covariates will become broader, strengthening future tools.

A comparison of machine learning models and Cox proportional hazards models regarding their ability to predict the risk of gastrointestinal cancer based on metabolic syndrome and its components.

Background: Little is known about applying machine learning (ML) techniques to identify the important variables contributing to the occurrence of gastrointestinal (GI) cancer in epidemiological studies. We aimed to compare different ML models to a Cox proportional hazards (CPH) model regarding their ability to predict the risk of GI cancer based on metabolic syndrome (MetS) and its components. Methods: A total of 41,837 participants were included in a prospective cohort study. Incident cancer cases were identified by following up with participants until December 2019. We used CPH, random survival forest (RSF), survival trees (ST), gradient boosting (GB), survival support vector machine (SSVM), and extra survival trees (EST) models to explore the impact of MetS on GI cancer prediction. We used the C-index and integrated Brier score (IBS) to compare the models. Results: In all, 540 incident GI cancer cases were identified. The GB and SSVM models exhibited comparable performance to the CPH model concerning the C-index (0.725). We also recorded a similar IBS for all models (0.017). Fasting glucose and waist circumference were considered important predictors. Conclusions: Our study found comparably good performance concerning the C-index for the ML models and CPH model. This finding suggests that ML models may be considered another method for survival analysis when the CPH model's conditions are not satisfied.

Long-term trajectory of postoperative health-related quality of life in young breast cancer patients: a 15-year follow-up study.

PURPOSE: Breast cancer (BC) patients often experience various long-term sequelae due to aggressive treatment. We analyzed and illustrated long-term trajectory during different phases of treatment and survivorship. METHODS: Data were obtained from a cohort of 298 BC patients diagnosed between 2004 and 2006 and were followed up until 2020. We measured HRQoL using EORTC QLQ-C30, QLQ-BR23, and EuroQoL-5D questionnaires and conducted eight assessments right after initial diagnosis, during treatment, post-treatment, and during survivorship phases. Linear mixed model was used to assess changes in HRQoL. Overall HRQoL measured by EQ-5D index of long-term BC survivors were further compared with that of the age-matched general population. RESULTS: Of 298 participants, 246 women survived and 124 participated in the long-term follow-up survey (LTFU). Overall, HRQoL functions deteriorated during treatment but gradually improved between 1- and 3-year post-diagnosis and stabilized over LTFU measure. Significant recovery was observed in physical, role, emotional, social functions, and future perspectives (p < 0.05). Treatment-related acute symptoms were reported in the first year but diminished afterward, and treatment-related financial difficulties lessened. At LTFU, BC survivors reported a high level of insomnia, fatigue, and pain and appeared to have poorer overall HRQoL than the general population (mean difference, EQ-5D index: 0.073, p < 0.001). CONCLUSIONS: Through 15-year survivorship, BC survivors showed improvement in many aspects of HRQoL. However, some inferior aspects remain relevant for long-term survivors. Ongoing supportive programs concentrating on pain management, persistent cancer-related fatigue, and sleeping problems might aid enhance their HRQoL.

Long-term Survivorship and Non-cancer Competing Mortality in Head and Neck Cancer: A Nationwide Population-Based Study in South Korea.

PURPOSE: As the survival of head and neck cancer (HNC) improves, survivors increasingly confront non-cancer-related deaths. This nationwide population-based study aimed to investigate non-cancer-related deaths in HNC survivors. MATERIALS AND METHODS: Data from the Korean Central Cancer Registry were obtained to characterize causes of death, mortality patterns, and survival in patients with HNC between 2006 and 2016 (n=40,890). Non-cancer-related mortality relative to the general population was evaluated using standardized mortality ratios (SMRs). The 5- and 10-year cause-specific competing risks probabilities of death (cumulative incidence function, CIF) and subdistribution hazards ratios (sHR) from the Fine-Gray models were estimated. RESULTS: Comorbidity-related mortality was frequent in older patients, whereas suicide was predominant in younger patients. The risk of suicide was greater in patients with HNC than in the general population (SMR, 3.1; 95% confidence interval [CI], 2.7 to 3.5). The probability of HNC deaths reached a plateau at 5 years (5-year CIF, 33.9%; 10-year CIF, 39.5%), whereas the probability of non-HNC deaths showed a long-term linear increase (5-year, CIF 5.6%; 10-year CIF, 11.9%). Patients who were male (sHR, 1.56; 95% CI, 1.41 to 1.72), diagnosed with early-stage HNC (localized vs. distant: sHR, 1.86; 95% CI, 1.58 to 2.21) and older age (65-74 vs. 0-44: sHR, 6.20; 95% CI, 4.92 to 7.82; ≥ 75 vs. 0-44: sHR, 9.81; 95% CI, 7.76 to 12.39) had an increased risk of non-cancer mortality. CONCLUSION: Non-HNC-related deaths continue increasing. HNC survivors are at increased risk of suicide in the younger and comorbidity-related death in the older. Better population-specific surveillance awareness and survivorship plans for HNC survivors are warranted.

Risk prediction model of peritoneal seeding in advanced gastric cancer: A decision tool for diagnostic laparoscopy.

BACKGROUND: Selective diagnostic laparoscopy in gastric cancer patients at high risk of peritoneal metastasis is essential for optimal treatment planning. In this study available clinicopathologic factors predictive of peritoneal seeding in advanced gastric cancer (AGC) were identified, and this information was translated into a clinically useful tool. METHODS: Totally 2833 patients underwent surgery for AGC between 2003 and 2013. The study identified clinicopathologic factors associated with the risk of peritoneal seeding for constructing nomograms using a multivariate logistic regression model with backward elimination. A nomogram was constructed to generate a numerical value indicating risk. Accuracy was validated using bootstrapping and cross-validation. RESULTS: The proportion of seeding positive was 12.7% in females and 9.6% in males. Of 2833 patients who underwent surgery for AGC, 300 (10.6%) were intraoperatively identified with peritoneal seeding. Multivariate analysis revealed the following factors associated with peritoneal seeding: high American Society of Anesthesiologists score, fibrinogen, Borrmann type 3 or 4 tumors, the involvement of the middle, anterior, and greater curvature, cT3 or cT4cN1 or cN2 or cN3, cM1, and the presence of ascites or peritoneal thickening or plaque or a nodule on the peritoneal wall on computed tomography. The bootstrap analysis revealed a robust concordance between mean and final parameter estimates. The area under the ROC curve for the final model was 0.856 (95% CI, 0.835-0.877), which implies good performance. CONCLUSIONS: This nomogram provides effective risk estimates of peritoneal seeding from gastric cancer and can facilitate individualized decision-making regarding the selective use of diagnostic laparoscopy.

An early interactive human coaching via a mobile application to improve quality of life in patients who underwent gastrectomy for gastric cancer: Design and protocol of a randomized controlled trial.

BACKGROUND: After gastrectomy, patients may experience the postgastrectomy syndrome and face difficulties adapting to everyday diet. Recently, human health coaching via a mobile application (app) has been used for obese patients or patients with chronic diseases, with significant improvements in clinical outcomes. The aim of this study is to evaluate and compare the effects of human health coaching via a mobile app and conventional face-to-face counseling in patients who underwent gastrectomy for gastric cancers. METHODS: This study is a single-institution, prospective randomized controlled trial comparing the mobile health and face-to-face counselling groups. After randomization, participants assigned to the mobile health coaching group will receive health coaching via a mobile app for 3 months after discharge, and the assigned coaches will provide personalized advice based on the self-recorded health data. Participants in the face-to-face group will have 1- and 3-months postoperative dietary consultations with a clinical dietitian. The primary endpoint is the food restriction score on the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-STO22, and secondary endpoints included all other quality of life scale scores and nutritional parameters. The calculated sample size is 180, and the outcomes will be measured until 1-year post-surgery. SIGNIFICANCE: This study will show the efficacy of human health coaching via a mobile app on dietary adaptation in patients who underwent gastrectomy. A relational approach based on personal data and timely intervention using a mobile platform could reduce patients' trial and error and improve quality of life. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04394585, Registered 19 May, 2020 -Retrospectively registered, http://clinicaltrials.gov/ct2/show/NCT040394585.

Multimorbidity patterns by health-related quality of life status in older adults: an association rules and network analysis utilizing the Korea National Health and Nutrition Examination Survey.

OBJECTIVES: Improved life expectancy has increased the prevalence of older adults living with multimorbidity which likely deteriorates their health-related quality of life (HRQoL). However, relatively little is known about patterns and the relationships of multimorbidity by HRQoL status in older adults. METHODS: Individuals aged 65 or older from the Korea National Health and Nutrition Examination Survey V-VII (2010-2018) were analyzed. HRQoL was assessed by the EuroQoL-5 dimensions questionnaire and categorized as poor, normal, or good. The impact of multimorbidity on HRQoL was evaluated using logistic regression. The patterns and inter-relationships between multimorbidity, stratified by HRQoL groups, were analyzed using the association rules and network analysis approach. RESULTS: Multimorbidity was significantly associated with poor HRQoL (3 or more diseases vs. none; adjusted odds ratio, 2.70; 95% confidence interval, 2.10 to 3.46). Hypertension, arthritis, hyperlipidemia, and diabetes were the most prevalent diseases across all HRQoL groups. Complex interrelationships of morbidities, higher prevalence, and node strengths in all diseases were observed in the poor HRQoL group, particularly for arthritis, depression, and stroke, compared to other groups (1.5-3.0 times higher, p<0.05 for all). Apart from hypertension, arthritis and hyperlipidemia had a higher prevalence and stronger connections with other diseases in females, whereas this was the case for diabetes and stroke in males with poor HRQoL. CONCLUSIONS: Multimorbidity patterns formed complicatedly inter-correlated disease networks in the poor HRQoL group with differences according to sex. These findings enhance the understanding of multimorbidity connections and provide information on the healthcare needs of older adults, especially those with poor HRQoL.

Hyperthermic intraperitoneal chemotherapy for epithelial ovarian cancer: A meta-analysis.

BACKGROUND: The value of hyperthermic intraperitoneal chemotherapy (HIPEC) at the time of cytoreductive surgery (CRS) for epithelial ovarian cancer (EOC) is controversial and its use remains experimental in most national and international guidelines. We wished to systematically evaluate all available evidence. METHODS: A comprehensive review of data from MEDLINE, EMBASE, and Cochrane Library databases was conducted from the first report on HIPEC in EOC till April 3, 2022. Progression-free survival (PFS) and overall survival (OS) were compared between the HIPEC and control groups. This meta-analysis was registered with PROSPERO (CRD42021265810). RESULTS: Fifteen studies (10 case-control studies and 5 randomized controlled trials [RCTs]) were included in the present meta-analysis. Based on the time interval between the last systemic chemotherapy exposure and timing of CRS +/- HIPEC, all studies and patients' cohorts we classified into recent (<6 months; n = 9 studies/patients cohorts) and non-recent (≥6 months, n = 8 studies/patients cohorts) chemotherapy exposure groups. In the recent chemotherapy exposure group, HIPEC was associated with improvement of both PFS (HR, 0.585; 95% CI, 0.422-0.811) and OS (HR, 0.519; 95% CI, 0.346-0.777). On the contrary, in the non-recent chemotherapy exposure group, HIPEC failed to significantly affect PFS (HR, 1.037; 95% CI, 0.684-1.571) or OS (HR, 0.932; 95% CI, 0.607-1.430). Consistent results were observed in subsequent sensitivity analyses. CONCLUSION: Our present meta-analysis demonstrates that the value of HIPEC at CRS for EOC appears to depend on the timing of the last systemic chemotherapy exposure. Future trials are awaited to define the role of HIPEC in EOC.

Unsupervised learning methods for efficient geographic clustering and identification of disease disparities with applications to county-level colorectal cancer incidence in California.

Many public health policymaking questions involve data subsets representing application-specific attributes and geographic location. We develop and evaluate standard and tailored techniques for clustering via unsupervised learning (UL) algorithms on such amalgamated (dual-domain) data sets. The aim of the associated algorithms is to identify geographically efficient clusters that also maximize the number of statistically significant differences in disease incidence and demographic variables across top clusters. Two standard UL approaches, k means with k++ initialization (k++) and the standard self-organizing map (SSOM), are considered along with a new, tailored version of the SOM (TSOM). The TSOM algorithm involves optimization of a customized objective function with terms promoting individual geographic cluster cohesion while also maximizing the number of differences across clusters, and two hyper-parameters controlling the relative weighting of geographic and attribute subspaces in a non-Euclidean distance measure within the clustering problem. The performance of these three techniques (k++, SSOM, TSOM) is compared and evaluated in the context of a data set for colorectal cancer incidence in the state of California, at the level of individual counties. Clusters are visualized via chloropleth maps and ordered graphs are also used to illustrate disparities in disease incidence among four identity groups. While all three approaches performed well, the TSOM identified the largest number of disease and demographic disparities while also yielding more geographically efficient top clusters. Techniques presented in this study are relevant to applications including the delivery of health care resources and identifying disparities among identity groups, and to questions involving coordination between county- and state-level policymakers.

Understanding health problems in people with extremely low health-related quality of life in Korea.

Little is known about patients reporting extremely poor health-related quality of life (HRQoL). This study targeted population with inferior HRQoL and examined their problems experienced with HRQoL dimensions, and impacts of different morbidities on these problems. Data were obtained from a population-based survey in Korea. HRQoL was measured by EQ-5D questionnaire and low-HRQoL population was defined as individuals whose EQ-5D utility score was among the lowest 5% of total survey population. Logistic regression models were used to evaluate the impact of fifteen morbidities on HRQoL dimensions. Of 2976 low-HRQoL participants, females and low socioeconomic individuals were predominant. They experienced significantly more problems in all dimensions, with pain/discomfort, and mobility as the most frequently reported problems. Problems in HRQoL dimensions diverged according to diseases. Individuals with arthritis experienced more difficulties with mobility (aOR 2.62, 95% CI 1.77-3.87) and pain/discomfort (aOR 2.86, 95% CI 1.78-4.60). Stroke patients experienced more problems in self-care (aOR 2.24, 95% CI 1.59-3.15) and usual activities (aOR 1.87, 95% CI 1.11-3.14). Having two or more diseases was associated with worse outcomes in usual activities and increased risk of depression. Thus, efforts to improve status of low-HRQoL should be customized to fulfil unmet needs corresponding to various diseases, and depression prevention is needed for those with multimorbidity status.

Infection-related and lifestyle-related cancer burden in Kampala, Uganda: projection of the future cancer incidence up to 2030.

OBJECTIVES: In Uganda, infection-related cancers have made the greatest contribution to cancer burden in the past; however, burden from lifestyle-related cancers has increased recently. Using the Kampala Cancer Registry data, we projected incidence of top five cancers, namely, Kaposi sarcoma (KS), cervical, breast and prostate cancer, and non-Hodgkin's lymphoma (NHL) in Uganda. DESIGN: Trend analysis of cancer registry data. SETTING: Kampala Cancer Registry, Uganda. MAIN OUTCOME MEASURE: Cancer incidence data from 2001 to 2015 were used and projected to 2030. Population data were obtained from the Uganda Bureau of Statistics. Age-standardised incidence rates (ASRs) and their trends over the observed and projected period were calculated. Percentage change in cancer incidence was calculated to determine whether cancer incidence changes were attributable to cancer risk changes or population changes. RESULTS: It was projected that the incidence rates of KS and NHL continue to decrease by 22.6% and 37.3%, respectively. The ASR of KS was expected to decline from 29.6 per 100 000 population to 10.4, while ASR of NHL was expected to decrease from 7.6 to 3.2. In contrast, cervical, breast and prostate cancer incidence were projected to increase by 35.3%, 57.7% and 33.4%, respectively. The ASRs of cervical and breast were projected to increase up to 66.1 and 48.4 per 100 000 women. The ASR of prostate cancer was estimated to increase from 41.6 to 60.5 per 100 000 men. These changes were due to changes in risk factors and population growth. CONCLUSION: Our results suggest a rapid shift in the profile of common cancers in Uganda, reflecting a new trend emerging in low/middle-income countries. This change in cancer spectrum, from infection-related to lifestyle-related, yields another challenge to cancer control programmes in resource-limited countries. Forthcoming cancer control programmes should include a substantial focus on lifestyle-related cancers, while infectious disease control programmes should be maintained.

Cause of death and cause-specific mortality for primary liver cancer in South Korea: A nationwide population-based study in hepatitis B virus-endemic area.

BACKGROUND/AIMS: Primary liver cancer is one of the leading causes of cancer mortality worldwide. However, the causes of death have not been studied in detail in patients with liver cancer. METHODS: The causes of death and cause-specific mortality risks in patients with primary liver cancer, diagnosed during 2000-2016, were investigated using the nationwide population-based cancer registry data in South Korea (n=231,388). The cumulative incidence function and Fine-Gray models were used to estimate the cause-specific mortality under the competing risks. Risks of non-cancer deaths relative to the general population were compared by standardized mortality ratios (SMRs). RESULTS: Among 179,921 total deaths, 92.4%, 1.7%, and 6.0% of patients died of primary liver cancer, cancer from other sites, and non-cancer illnesses, respectively. Proportionate mortality from liver cancer remained high. The 5-year competing risks probability of death from liver cancer varied by tumor stage, from 42% to 94%, and it remained high 10 years after the diagnosis (61-95%). Competing mortality from other causes has continuously increased. The most common non-cancer causes of death were underlying liver diseases (SMR, 15.6; 95% confidence interval [CI], 15.1-16.1) and viral hepatitis (SMR, 46.5; 95% CI, 43.9-49.2), which demonstrated higher mortality risks compared to the Korean general population. Higher mortality risks of suicide (SMR, 2.6; 95% CI, 2.4-2.8) was also noted. CONCLUSION: Patients with liver cancer are most likely to die from liver cancer and related liver disease, even 10 years after the diagnosis, highlighting a need for specialized long-term follow-up care.

Estimating life expectancy adjusted by self-rated health status in the United States: national health interview survey linked to the mortality.

BACKGROUND: Life expectancy is increasingly incorporated in evidence-based screening and treatment guidelines to facilitate patient-centered clinical decision-making. However, life expectancy estimates from standard life tables do not account for health status, an important prognostic factor for premature death. This study aims to address this research gap and develop life tables incorporating the health status of adults in the United States. METHODS: Data from the National Health Interview Survey (1986-2004) linked to mortality follow-up through to 2006 (age ≥ 40, n = 729,531) were used to develop life tables. The impact of self-rated health (excellent, very good, good, fair, poor) on survival was quantified in 5-year age groups, incorporating complex survey design and weights. Life expectancies were estimated by extrapolating the modeled survival probabilities. RESULTS: Life expectancies incorporating health status differed substantially from standard US life tables and by health status. Poor self-rated health more significantly affected the survival of younger compared to older individuals, resulting in substantial decreases in life expectancy. At age 40 years, hazards of dying for white men who reported poor vs. excellent health was 8.5 (95% CI: 7.0,10.3) times greater, resulting in a 23-year difference in life expectancy (poor vs. excellent: 22 vs. 45), while at age 80 years, the hazards ratio was 2.4 (95% CI: 2.1, 2.8) and life expectancy difference was 5 years (5 vs. 10). Relative to the US general population, life expectancies of adults (age < 65) with poor health were approximately 5-15 years shorter. CONCLUSIONS: Considerable shortage in life expectancy due to poor self-rated health existed. The life table developed can be helpful by including a patient perspective on their health and be used in conjunction with other predictive models in clinical decision making, particularly for younger adults in poor health, for whom life tables including comorbid conditions are limited.