Quality Index Research Articles

Insight into aquatic potential of Kunah stream, Hamirpur (HP) by analysis of water quality parameters using Weighted Arithmetic Water Quality Index

Insight into aquatic potential of Kunah stream, Hamirpur (HP) by analysis of water quality parameters using Weighted Arithmetic Water Quality Index

Sleep quality predicts future mood symptoms in adolescents with bipolar disorder

BackgroundPoor sleep is prevalent in adolescents with bipolar disorder, precedes illness onset, and is associated with worse mood symptoms. We examined interrelationships between sleep quality and mood symptoms in adolescents with bipolar disorder, particularly effects of sleep quality on emergent mood symptoms. MethodsAdolescents with bipolar disorder participated in a two-year longitudinal treatment study. Sleep quality (Pittsburgh Sleep Quality Index, PSQI) was assessed quarterly during treatment (baseline, 3-, 6-, 9-, 12-month visits) and twice during follow-up (18-, 24-month visits). Mood symptoms (ALIFE Psychiatric Status Ratings) were retrospectively rated weekly by an independent clinician. Lag models tested whether sleep quality predicted next month's mood symptoms and whether mood symptoms predicted future sleep quality. ResultsAdolescents with bipolar disorder had poor sleep quality. Sleep quality initially improved but remained stable thereafter. Worse sleep quality at 6-months predicted worse depression, hypomania, and suicidal ideation the following month. Sleep quality was worse for adolescents who had a suicide attempt during the study compared to those who did not and was worse preceding months with a suicide attempt compared to months without attempts. Alternatively, worse depression predicted worse future sleep quality at baseline, 3-, and 18-months and worse suicidal ideation predicted worse future sleep quality at baseline, 12-, and 18-months. LimitationsMood symptoms were rated retrospectively and the PSQI may not capture all dimensions of sleep important for mood symptoms. ConclusionsTargeted evidence-based sleep treatment in adolescents with bipolar disorder may alleviate sleep problems and have additional benefits on mood symptoms and suicidality risk.

Sleep quality of Chinese designers and the effects of digital screen time, stress, and job responsibility

The aim of this study was to describe the sleep status of Chinese designers and to identify the factors that affect their sleep quality. A total of 393 Chinese designers participated in the survey, which collected data on demographic information, digital screen time, stress, and the pittsburgh sleep quality index (PSQI). The average PSQI score of Chinese designers was 6.77, with 29% scoring equal to or higher than 9, indicating poor sleep quality. The most common sleep problem was difficulty falling asleep. Designers with management responsibilities had poorer sleep quality: the PSQI scores for those in design project management (M=8.74, SD=3.829) and design and management (M=9.05, SD=3.475) were significantly higher than for those in dedicated design (M=5.34, SD=2.908). There was a positive correlation between digital screen time for entertainment, work stress, other stress, and PSQI. The model equation was PSQI=1.160+0.276 * entertainment+0.675 * work stress+0.569 * other stress, with an r square of 0.232. Chinese designers should improve their sleep quality by reducing electronic entertainment and relieving stress. Managers in the design industry should pay special attention to their own sleep quality.

Improving sleep outcomes in patients with cancer with chronic insomnia using cognitive behavioral therapy: A retrospective study.

e13555 Background: Cancer patients experience a threefold higher rate of insomnia (23-54%) than the general population. Cognitive behavioral therapy for Insomnia (CBT- i) is the gold standard treatment of chronic insomnia. Few studies, however, have demonstrated CBT- i efficacy for chronic insomnia in cancer patients. To address the needs of cancer patients with insomnia, a psycho-oncology physician trained to provide CBT- i therapy established an insomnia clinic in an ambulatory oncology center tailored for oncology patients. The objective of this study is to assess the efficacy of CBT- i for chronic insomnia among cancer patients. Methods: A retrospective review of electronic medical records was performed on consecutive referrals to an insomnia clinic in an ambulatory oncology center. All patients with ICD-10 confirmed chronic insomnia diagnosis who received at least 2 sessions up to a maximum of 7 sessions of CBT- i were included in the analysis. Demographic variables, cancer-related disease and treatment variables, and sleep parameters at initial session (T1) and last session (T2) were collected. Sleep parameters included sleep efficiency, total sleep time, sleep onset latency, number of nightly awakenings, and sleep quality. Semi-structured psychiatric clinical interviews, past medical and sleep history, and patient-rated Pittsburgh Sleep Quality Index (PSQI) scores at T1 were collected. Data analysis utilized SPSS descriptive statistics and T-test to compare differences between the baseline (T1) and post-CBT- i treatment (T2) sleep variable outcome measures. Results: The sample included 18 cancer patients (mean age 59 years; 12 Hispanics, 6 non-Hispanics; 16 females, 2 males) with ICD-10-confirmed chronic insomnia treated with CBT- i. Cancer-related variables among the sample included a mean duration of 18 months since cancer diagnosis, disease staging ranging from 0-IV, and 16 patients completed curative treatment. The sample included 13 breast cancer patients. Mean duration of insomnia was 6 years. PSQI score was 14 (PSQI score ranges from 0 to 21, scores above 5 are indicative of poor sleep quality). The mean number of sessions delivered was 5. Sleep parameters at T2 showed a significant improvement compared to those at T1 (Table). The number of nightly awakenings decreased from 3 at T1 to 2 at T2 (p=0.01), and 78% (14/18) of patients reported an improvement in their sleep quality at T2. Conclusions: Cognitive Behavioral Therapy for Insomnia demonstrates efficacy in the treatment of chronic insomnia in cancer patients and is easily administered within an ambulatory oncology center. [Table: see text]

Water Quality Index and Health Risks in a Peruvian High Andean River

Water Quality Index and Health Risks in a Peruvian High Andean River

Correlation of stress, depression, sleep, and pain with race and body mass index (BMI): Secondary analysis from Alliance A011502.

e23171 Background: A011502 is a phase 3 trial that randomized high-risk nonmetastatic breast cancer (BC) patients (pts) to aspirin 300 mg daily vs. placebo. Obesity and Black race have been shown to be associated with worse clinical outcomes. We studied the association of stress, depression, sleep and pain with each other, and with BMI and race. Methods: At baseline, 2735, 2610, 2720, and 2422 pts completed Perceived Stress Scale (PSS), Center for Epidemiologic Studies Depression Scale Revised (CESD-R), Brief Pain Inventory (BPI), and Pittsburgh Sleep Quality Index (PSQI) respectively. Stress was categorized with PSS scores: low (0-13), moderate (14-26) or high (27-40). Depression was categorized with CESD-R scores: no depression (0-15) or depression (≥16). Pain was categorized with BPI scores: none/mild (0-3) or moderate/severe (≥4). Sleep quality was categorized with PSQI scores: good (0-5) or poor ( > 5). Associations of measures by race and BMI were analyzed using chi-square test. Results: There was a statistically significant association among stress, depression, pain, and sleep quality (p < 0.01 for all). Compared to pts with BMI < 25, overweight and obese women reported higher stress (2.9%, 2.3% vs. 1.7%, p = 0.04), depression (13.4%, 18% vs. 9.6%, p < 0.01), moderate/severe pain (16.5%, 20.3% vs. 12%, p < 0.01), and poor sleep (64.9%, 71.5% vs. 60.4%, p < 0.01). Black women reported more moderate/severe pain compared to White women or other races (32.9% vs. 14.2% vs. 27.8%, p < 0.01). There was no association of other symptoms with race (Table 1). Conclusions: Obesity was associated with higher stress, depression, poor sleep and pain among BC pts from A011502. Black women reported higher pain compared to other races. Future studies are warranted that determine causal associations, how symptoms may relate to outcome disparities, and develop approaches to address them. U10CA180821, U10CA180882, UG1CA233196; https://acknowledgments.alliancefound.org . Clinical trial information: NCT02927249 . [Table: see text]

Evaluation of water quality based on artificial intelligence: performance of multilayer perceptron neural networks and multiple linear regression versus water quality indexes

AbstractA significant problem in the sustainable management of water resources is the lack of funding and long-term monitoring. Today, this problem has been greatly reduced by innovative, adaptive, and sustainable learning methods. Therefore, in this study, a sample river was selected and 14 variables observed at 5 different points for 12 months, traditionally reference values, were calculated by multivariate statistical analysis methods to obtain the water quality index (WQI). The WQI index was estimated using different algorithms including the innovatively used multiple linear regression (MLR), multilayer perceptron artificial neural networks (MLP-ANN) and various machine learning estimation algorithms including neural networks (NN), support vector machine (SVM), gaussian process regression (GPR), ensemble and decision tree approach. By comparing the results, the most appropriate method was selected. The determination of water quality was best estimated by the multiple linear regression (MLR) model. As a result of this MLR modeling, high prediction performance was obtained with accuracy values of R2 = 1.0, RMSE = 0.0025, and MAPE = 0.0296. The root mean square error (RMSE), percent mean absolute error (MAE), and coefficient of determination (R2) were used to determine the accuracy of the models. These results confirm that both MLR model can be used to predict WQI with very high accuracy. It seems that it can contribute to strengthening water quality management. As a result, as with the powerful results of the innovative approaches (MLR and MLP-ANN) and other assessments, it was found that the presence of intense anthropogenic pressure in the study area and the current situation needs immediate remediation.

Efficacy of Daoyin combined with lower limb robot as a comprehensive rehabilitation intervention for stroke patients: a randomized controlled trial.

To assess the effectiveness of a comprehensive rehabilitation approach combining Traditional Chinese Medicine Daoyin with lower limb robotics during the recovery phase of stroke patients. Stroke patients meeting the specified criteria were randomly assigned to one of four groups using a random number table: Control group, Daoyin group, lower limb robot group (LLR group), and Daoyin and lower limb robot group (DLLR group). Each group received distinct treatments based on conventional rehabilitation training. The treatment duration spanned two weeks with two days of rest per week. Pre- and post-intervention assessments included various scales: Fugl-Meyer Assessment (FMA), Berg balance scale (BBS), Barthel index (BI), Fatigue Scale-14 (FS-14), Pittsburgh sleep quality index (PSQI), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD). Statistically significant differences were observed in the lower limb function measured by FAM between the Control group (15 ± 5) and the DLLR group (18 ± 5) (P = 0.049). In the Barthel index, a statistically significant difference was noted between the Control group (54 ± 18) and the DLLR group (64 ± 11) (P = 0.041). Additionally, significant differences were found in the Berg balance scale between the Control group (21 ± 10) and the DLLR group (27 ± 8) (P = 0.024), as well as between the Control group (21 ± 10) and the LLR group (26 ± 10) (P = 0.048). The findings of this study suggest that the combined use of Daoyin and robotics not only enhances motor function in stroke patients but also has a positive impact on fatigue, sleep quality, and mood. This approach may offer a more effective rehabilitation strategy for stroke patients.

Deep learning-based water quality index classification using stacked ensemble variational mode decomposition

Water is crucial to human survival in general, and determining the WQI (water quality index) is one of the primary aspects. The existing water quality classification models are facing various challenges and gaps that are impeding their effectiveness. These challenges include limited data availability, the intricate nature of water systems, spatial and temporal variability, non-linear relationships, sensor noise, and error, interpretability, and explainability. It is imperative to address these challenges to improve the accuracy and efficacy of the models and to ensure that they continue to serve as reliable tools for monitoring and safeguarding water quality. To solve the issues, this paper proposes a Stacked Ensemble efficient long short-term memory (StackEL) model for an efficient water quality index classification. At first, the raw input data is pre-processed to rescale the input data using data normalization and one-hot encoding. After that, the process known as variational mode decomposition (VMD) is applied to get at the intrinsic mode functions (IMFs). Consequently, feature selection is performed using an extended coati optimization (EX-CoA) algorithm to select the most significant attributes from the feature selection. Here, publicly available datasets, namely the water quality dataset from Kaggle, are used for classification and performed using are used to perform the Stacked Ensemble efficient long short-term memory (StackEL) classification process effectively. To further perfect the proposed prediction model, the Dwarf Mongoose optimization (DMO) method is implemented. Several measures of effectiveness are examined. When compared to other existing models, the suggested model can achieve a high accuracy of 98.85% of the water quality dataset.

Roles of Sleep Quality, Self-Efficacy, and Coping Style in the Frailty of Community-Dwelling Older Adults: A Cross-Sectional Study

ABSTRACT Objectives Although the association between sleep disorders and frailty has been well established, little is known about the cognitive appraisal mechanisms underlying this association. Building on the transactional theory of stress and coping, this study explores the role of self-efficacy and coping style in the association between sleep quality and frailty among community-dwelling older adults. Methods In this cross-sectional study, 585 community-dwelling older adults were investigated using the Pittsburgh Sleep Quality Index, Tilburg Frailty Indicator, General Self-Efficacy Scale, and Simplified Coping Style Questionnaire. Descriptive statistics and hierarchical regression were performed. A moderated mediation model was established using the PROCESS macro. Results Poor sleep quality affects frailty directly (B = 0.193, p < .01) and indirectly via self-efficacy (B = 0.063, p < .01). The negative impact of poor sleep on frailty through self-efficacy was moderated by both positive and negative coping style (index = −0.007). The moderating effect was stronger when participants’ negative coping tendencies increased. Conclusions Poor sleep quality indirectly influences frailty by modifying self-efficacy. Effective coping strategies can help attenuate this association. Clinical Implications Timely sleep assessment and tailored strategies such as psychoeducational programs and targeted coping skills training may be beneficial for preventing frailty in older adults.

Impact of Hydraulic Developments on the Quality of Surface Water in the Mafragh Watershed, El Tarf, Algeria

The wadis are environments of great ecological and economic importance. They are the seat of several hydraulic developments. The latter disrupts the functioning of the wadi in different ways. They modify their hydrological regime, disrupt the ecological conditions upstream and downstream of the reservoir, reduce the self-purification capacities, and modify the processes of erosion and solid transport. It is in this perspective that we have carried out a study of the impact of hydraulic installations on the quality of the waters of the Mafragh watershed. The hydrographic network of the watershed receives the wastewater discharged by the localities and by the industries located along these rivers. This wastewater contributes to the degradation of the water quality of the wadis. The spatio-temporal variation of the water quality index showed a good quality at the level of the dams, while at the level of the sites, which are located downstream, the quality generally varies between bad and very bad during the study period.

Research on multiscale OpenStreetMap in China: data quality assessment with EWM-TOPSIS and GDP modeling

ABSTRACT OpenStreetMap (OSM) is a voluntary platform designed to provide free and up-to-date geographic data. Since OSM is based on multisource geographic data provided by the public, the quality of the data has become a concern of researchers. In this study, a unified measure for evaluating OSM data quality was constructed, and the entropy weight method (EWM) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model were used to evaluate the quality of multiscale OSM data in China from 2014 to 2020. In addition to evaluating the data quality, the use of OSM data quality index factors in economic modeling at different spatial scales in China was explored by using a geographic information system (GIS) analysis method and a geographically and temporally weighted regression (GTWR) model. Four machine learning models, SVM, RF, XGBoost and CatBoost, were used to simulate the grid-scale GDP, and the effectiveness of these simulations was discussed. The results showed that (1) the weights of OSM data quality indicator factors vary across different spatial scales. (2) From 2014 to 2020, the quality of national-scale OSM data first increased, then decreased and then gradually stabilized. In addition, the quality of OSM data at the provincial and municipal scales is significantly different, and the distribution is affected by the population and geographical environment. (3) Over time, the spatial clustering characteristics of OSM data quality at different spatial scales in China has continuously strengthened. In addition, the quality of Chinese OSM data displays obvious local spatial autocorrelation characteristics, which are dominated by H-H clustering and L-L clustering. (4) The GTWR model performs well in predicting and revealing the spatiotemporal correlation characteristics between GDP and OSM data quality indicators at the provincial and municipal scales in China. The correlations increase with decreasing spatial scale (provincial to municipal). Moreover, the GDP modeling ability is better in economically underdeveloped Northwest China and economically developed East China. (5) Four machine learning models coupled with road network length completeness, relative linear density, road name attribute completeness, POI name attribute completeness, road network accuracy, road network update frequency, POI update frequency, topological consistency and directional similarity yielded the best grid-scale GDP simulation values. Notably, the CatBoost model provided the best accuracy, and the results further verified that it is feasible to use the proposed OSM data quality index system to predict the regional economic development level in China.

Dietary Patterns of Pregnant Women and Their Association with Diet Quality Measures: A Comparative Analysis.

Healthy dietary patterns during pregnancy are crucial for ensuring maternal and foetal health outcomes. Numerous methodologies exist for assessing the diet of pregnant women, including dietary patterns and various appraisal tools of diet quality. This study aimed to assess the dietary patterns and diet quality of pregnant women and to investigate the relationship between dietary patterns, diet quality estimators, and the adequacy of nutrient intake. EPIC FFQ was applied to a sample of 251 pregnant women, and questionnaires were interpreted with the FETA program. Dietary patterns were then determined by means of principal component analysis. Our results showed a substantial association between dietary patterns and total diet quality, as measured by the Diet Quality Index for Pregnancy (DQI-Pc), PURE Healthy Diet Score, and FIGO Diet Quality Score. We also found correlations between certain dietary patterns and particular nutrient intakes recommended by the European Food Safety Authority during pregnancy. The most deficient intake was registered for iron (86.1%), zinc (87.3%) and magnesium (79.3%), posing a threat to normal bone development, anaemia prophylaxis, and immune status. These results highlight the importance of assessing and understanding eating habits during pregnancy in order to achieve optimal outcomes for both the mother and the foetus.

Protecting wilderness or rewilding? An ecoregion-based approach to identifying priority areas for the protection and restoration of natural processes for biodiversity conservation

Amidst the global decline in biodiversity, there are growing calls for more ambitious conservation targets and practices, including a renewed focus on protecting and restoring natural processes. However, little is known about suitable areas for process-oriented conservation and its different strategies. In this paper, we identify priority areas for process-oriented conservation following an ecoregion-based approach. Using the Alpine Space programme area as a pilot study area, a Wilderness Quality Index is calculated and mapped based on spatial indicators reflecting variations in naturalness, human impact, remoteness, and ruggedness. To identify priority areas for process-oriented conservation, the 10% of areas with the highest wilderness quality are identified for each ecoregion (‘ecoregional approach’) and compared with the identification of the 10% wildest areas of the entire study area (‘conventional approach’). The results show significant differences in priority areas between the two approaches, with those identified by the ecoregional approach being of lower wilderness quality, more dispersed across the study region and different elevation classes, and smaller in size. The ecoregional approach results in a greater coverage of ecosystem- and species-level diversity, yet it highlights a greater need for complementing the protection of wilderness in less modified regions with rewilding initiatives and the expansion of the protected area network in ecoregions with significant human activity. Based on these findings, we discuss the potential and challenges that an ecoregion-based identification of priority areas brings for biodiversity conservation, protection and restoration practice, and local communities. The ecoregion-based approach and the findings of this study can inform initiatives under the EU Biodiversity Strategy to 2030, in particular the target to ‘strictly protect’ 10% of the EU’s land and sea.

A Randomized Single-Blinded Phase II Trial Comparing Efficacy and Quality of Life of Topical Aloe Vera Gel Plus Urea Cream Versus Urea Cream Alone for Prevention of Hand Foot Syndrome in Cancer Patients Receiving Capecitabine.

Capecitabine has been widely prescribed to treat various cancers. The hand foot syndrome (HFS) is the most troublesome adverse effect. Urea cream has been pre-emptively co-prescribed, even though its efficacy is doubtful. Aloe vera gel with urea cream might potentiate each other. This trial was intended to prove the efficacy of this combination. The investigators conducted a randomized single-blinded phase II study. The participants were randomized 1:1 to receive the combination of aloe vera gel and 10% urea cream (n = 30), the experimental A+U arm and 10% urea cream alone (n = 31), the U arm. The sample size was calculated to have 90% power to show the significant 20% reduction in the incidence of HFS grade 2-3 of the combination therapy with alpha level = 0.05. Both the CTCAE criteria version 5 and the dermatology life quality index (DLQI) were assessed to determine the severity of HFS and quality of life, respectively. Most of the participants had rectal cancer (A+U: 43.3%; U: 41.9%). In the A+U group, 86.7% had grade 0-1 HFS and 13.3% had grade 2-3 HFS. In the U group, 64.5% had grade 0-1 HFS and 35.5% had grade 2-3 HFS (Mann-Whitney U test, p = 0.045). Grade 2-3 HFS was significantly lower in the combination group. Combination of aloe vera gel and 10% urea cream ameliorated the severity of HFS in participants taking capecitabine; however, no significant difference in DLQI between the groups was demonstrated.

Extrusion cooking characteristics of soy-wheat blends to produce ready to eat snacks

The snacks constitute an important part of our daily nutrient and calorie intake. Soy-cereal blends such as soy-com, soy-rice and soy-sorghum have been reported to give good quality snacks with extrusion processing. Soybean is the cheapest source of quality protein and good calorie whereas wheat is a popular cereal in India with 7085% starch. Extrusion provides expansion of starch, conversion of protein into easily digestible form at relatively lower operating costs. The experiments were conducted with full fat soy-flour blended with wheat flour in proportion of 10,20 and 30%, at 3 feed moisture levels of 15, 20 and 25% (wb) and three barrel temperatures of80, 90 and 100 °C. Analysis of various quality indices of extrudate with process variables indicated optimum condition of 10% blending of full fat soy flour (FFSF), 25% moisture content and 90 °C barrel temperature. The second set of experiment conducted on defatted soy-flour, showed optimum condition at 10 % blend, 15% moisture content and 90 °C barrel temperature.

Assessment of Soil Quality Index for Onion Cultivated Soils in a Semiarid Agricultural Ecosystem

Assessment of Soil Quality Index for Onion Cultivated Soils in a Semiarid Agricultural Ecosystem

Exploring spatiotemporal distribution characteristics of air quality and driving factors: empirical evidence of 288 cities in China.

Excellent air quality is important for China to achieve high quality economic development. The paper analyses the spatial and temporal distribution characteristics of the air quality index (AQI) in 288 Chinese cities, and further investigates the driving factors affecting air quality using the spatial Durbin model (SDM) based on the panel data of 288 Chinese cities from 2014 to 2021. The results of the study show that: (1) China's air quality level has improved in general, but there are large differences in air quality between regions; (2) China's AQI has significant spatial positive autocorrelation, and the Moran's scatter plot shows a high-high and low-low agglomeration; (3) The driving factors of air quality have different effects, and regional heterogeneity is obvious. Some developed regions in China have already crossed the inflexion point of the environmental Kuznets curve (EKC); promoting industrial upgrading and reducing pollutant emissions can significantly improve urban PM2.5 concentrations; and the "Three-Year Strategy for Conquering the Blue Sky War" policy has lowered the AQI in North China and improved PM2.5 concentrations nationwide. Based on the above findings, the paper puts forward corresponding policy recommendations.

Comparison of Two Multiparameter Acoustic Voice Outcome Indices in the Treatment of Hyperfunctional Voice Disorders: Dysphonia Severity Index and Acoustic Voice Quality Index

IntroductionThe Dysphonia Severity Index (DSI) and Acoustic Voice Quality Index (AVQI) are the two widely used multiparameter acoustic instrumented indices that estimate dysphonia severity and track treatment outcomes. This study compared the performance of these two indices in identifying voice quality changes with eclectic voice therapy in individuals with Hyperfunctional Voice Disorders (HFVD). Method20 individuals with HFVD including 8 males and 13 females in the age range of 20-55 years received an Eclectic voice therapy program named the Comprehensive Voice Habilitation Program (CVHP). All the participants attended 15 sessions of voice therapy. DSI and AVQI measures were obtained at the baseline, immediate post-therapy, 15 days post-therapy (follow-up 1), and 60 days post-therapy (follow-up 2). Repeated Measures Analysis of Variance was performed to verify whether there were any differences between the time points for dependent variables DSI and AVQI. The effect sizes obtained for the DSI and AVQI measures were also noted. ResultsA significant difference was obtained between the baseline and post-therapy, follow-up 1 and follow-up 2 for AVQI measure with a very large effect size, eta2 =0.451. In contrast, DSI showed significant difference only between the baseline and follow up 1 with effect size, eta2=0.187. ConclusionThe results of this study confirmed that both DSI and AVQI were effective in tracking the changes in the severity of dysphonia. However, when compared, AVQI appeared to be more sensitive than DSI in potentially reflecting the effect of eclectic voice therapy in HFVD.

Association of higher baseline stress and pain with clinical outcomes: Secondary analysis from Alliance A011502.

11016 Background: A011502 is a phase 3 randomized double-blind clinical trial that enrolled high-risk nonmetastatic breast cancer (BC) patients (pts) and randomized pts to aspirin 300 mg daily vs. placebo. There was no significant difference in invasive disease-free survival (iDFS) between the two arms. A secondary objective was to determine the association of inflammation-affiliated factors (stress, depression, poor sleep quality and pain) with iDFS and overall survival (OS). We hypothesized that these baseline factors are associated with worse clinical outcomes. Methods: At baseline, 2735, 2720, 2422 and 2610 pts completed Perceived Stress Scale (PSS), Brief Pain Inventory (BPI), Pittsburgh Sleep Quality Index (PSQI) and Center for Epidemiologic Studies Depression Scale Revised (CESD-R) respectively. Stress was categorized with PSS scores: low (0-13), moderate (14-26) or high stress (27-40). Pain was categorized with BPI scores: none/mild (0-3) or moderate/severe (≥4). Sleep quality was categorized with PSQI scores: good (0-5) or poor ( &gt; 5).Depression was categorized with CESD-R scores: no depression (0-15) or depression (≥16). Associations between the measures of interest and outcomes were performed with multivariable Cox models controlling for age, body mass index, time since diagnosis, race, ethnicity, hormone receptor status and treatment arm. Results: Median follow up was 35 months. The associations from multivariable Cox model are shown in Table 1. Pts who reported high PSS had significantly worse iDFS and (non-significant) worse OS. Moderate/severe average (avg) pain was significantly associated with worse iDFS and OS. Poor sleep quality and depression were associated with worse iDFS and OS but not statistically significant. Conclusions: Pts reporting higher stress and pain at baseline had worse outcomes. We acknowledge that both pain and stress may be related to other non-cancer issues (chronic comorbidities). Our study highlights the need for clinical trials to consider including questionnaires to assess pt-reported outcomes. Future studies are warranted to determine if measures to decrease pain and stress would improve BC outcomes. U10CA180821, U10CA180882, UG1CA233196; https://acknowledgments.alliancefound.org . NCT02927249: Clinical trial information: NCT02927249 . [Table: see text]