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Symptom and functional assessment is challenging in geriatric oncology care. This multicenter cross-sectional study examined the use of a multiple-symptom assessment tool, the MD Anderson Symptom Inventory (MDASI), on Chinese patients with cancer aged 65 years and older.Patient-rated symptoms and functioning were assessed using MDASI and the European Organization for Research and Treatment of Cancer quality-of-life questionnaire.The most severe symptoms were fatigue and poor appetite. The older group (75-84 years old, n = 224) reported a more severe difficulty remembering (effect size [ES] 0.32; P.001), shortness of breath (ES 0.20; P = .020), and interference with general activity (ES 0.14; P = .027), with significantly worse physical functioning (ES -0.33; P.001) and cognitive functioning on the European Organization for Research and Treatment of Cancer quality-of-life questionnaire (ES 0.20; P .001) than the younger group (65-74 years old, n = 555). For MDASI measures of the core symptoms and total interference with daily activity, Cronbach α coefficients were 0.90 and 0.93, respectively, for the younger group; and 0.93 and 0.94 for the older group, respectively. Moderate to severe (score ≥4) interference with general activity and walking on MDASI accurately indicated poor performance status (area under the curve 0.8089 and 0.7969, respectively) and lack of independence status of Activities of Daily Living (area under the curve 0.7993 and 0.8304, respectively).MDASI is psychometrically reliable, valid, and clinically sensitive for the measuring symptom burden and functional status of Chinese patients with cancer aged 65 years and older. MDASI could be adopted to measure multiple symptoms and physical functioning outcomes in geriatric oncology practice as well as for research on treatment benefits.

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Purpose:On the basis of strong preclinical rationale, we sought to confirm recommended phase II dose (RP2D) for olaparib, a PARP inhibitor, combined with the AKT inhibitor capivasertib and assess molecular markers of response and resistance.Patients and Methods:We performed a safety lead-in followed by expansion in endometrial, triple-negative breast, ovarian, fallopian tube, or peritoneal cancer. Olaparib 300 mg orally twice daily and capivasertib orally twice daily on a 4-day on 3-day off schedule was evaluated. Two dose levels (DL) of capivasertib were planned: 400 mg (DL1) and 320 mg (DL-1). Patients underwent biopsies at baseline and 28 days.Results:A total of 38 patients were enrolled. Seven (18%) had germline BRCA1/2 mutations. The first 2 patients on DL1 experienced dose-limiting toxicities (DLT) of diarrhea and vomiting. No DLTs were observed on DL-1 (n = 6); therefore, DL1 was reexplored (n = 6) with no DLTs, confirming DL1 as RP2D. Most common treatment-related grade 3/4 adverse events were anemia (23.7%) and leukopenia (10.5%). Of 32 evaluable subjects, 6 (19%) had partial response (PR); PR rate was 44.4% in endometrial cancer. Seven (22%) additional patients had stable disease greater than 4 months. Tumor analysis demonstrated strong correlations between response and immune activity, cell-cycle alterations, and DNA damage response. Therapy resistance was associated with receptor tyrosine kinase and RAS-MAPK pathway activity, metabolism, and epigenetics.Conclusions:The combination of olaparib and capivasertib is associated to no serious adverse events and demonstrates durable activity in ovarian, endometrial, and breast cancers, with promising responses in endometrial cancer. Importantly, tumor samples acquired pre- and on-therapy can help predict patient benefit.

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Based on the traditional Chinese medicine theory, Renshen Yangrong Tang (RSYRT), which is a mixture of 12 herbs, was commonly used as a pharmacological option in China for fatigue management by correcting Qi deficiency.This randomized controlled Phase II trial investigated the efficacy of RSYRT for reducing cancer-related fatigue.Cancer survivors with moderate or severe fatigue (rated ≥4 on a 0-10 scale) for more than two months were randomized to take herbal extract granules of RSYRT or a low dose of a single herb (huangqi) twice a day for six weeks. Patient-reported fatigue was measured using the MD Anderson Symptom Inventory. Efficacy of RSYRT was evaluated using mixed model to test the differences over time among groups. We also conducted responder analyses and examined time to effect of symptom reduction.None of the 83 evaluable patients (control group 42; intervention group 41) had discomfort or Grade 3 or 4 toxicity. We observed a significantly greater MD Anderson Symptom Inventory-fatigue score reduction in the intervention group than that in the control group (time-by-group interaction: estimate = -0.61 [0.10]; P 0.0001). More patients in the intervention group had a two-point reduction on fatigue than that of the control group (90.2% vs. 52.4%). By Week 4, between-group differences of fatigue reduction on mean severity reached large effect size (intervention group vs. control group: -2.66 vs. -1.36; Cohen's d = 1.0; P 0.0001).Compared with control therapy, RSYRT therapy elicits a statistical and clinical improvement of fatigue severity and functioning. The effectiveness of RSYRT in managing cancer-related fatigue warrants further study in the real world.

BACKGROUND While women diagnosed with breast cancer have increased survival when compared with other cancers, survivorship may include residual symptom burden from treatment and continuing endocrine therapies. OBJECTIVE The objective of this study was to identify subgroups of breast cancer survivors experiencing similar symptom severity. METHODS Participants were 498 women with breast cancer, not on active treatment. Symptom severity was self-reported using the MD Anderson Symptom Inventory. Target symptoms were included in a latent profile analysis. Factors related to subgroup membership and differences in quality of life (QOL) and functioning were explored using logistic regression. RESULTS Mean age was 60.11 (SD, 11.32) years, 86.1% were white, and 79.1% were receiving endocrine therapy. Target symptoms included fatigue (reported at ≥5 by 22.8% of women), sleep disturbance (24.8%), and trouble remembering (17.2%). Two subgroups were identified: low symptom severity (77.0% of women) and high (23.0%). Older women (odds ratio [OR], 0.971; 95% confidence interval [CI], 0.952-0.989) and employed women (OR, 0.621; 95% CI, 0404-0.956) were less likely to be in the high subgroup; women with poorer performance status (OR, 1.653; 95% CI, 1.188-2.299) were more likely to be in the high subgroup. Women in the high subgroup reported lower QOL (P = .000) and greater interference with functioning (P = .000). CONCLUSIONS Two subgroups of women with distinct symptom severity were identified. IMPLICATIONS FOR PRACTICE Identification of women at risk for high symptoms during survivorship may allow clinicians to intensify their approach to symptom management, thereby mitigating poor outcomes and impairments in QOL.

Cold weather has been identified as a major cause of weather-related deaths in the U.S. Although the effects of cold weather on mortality has been investigated extensively, studies on how cold weather affects hospital admissions are limited particularly in the Southern United States. This study aimed to examine impacts of cold weather on emergency hospital admissions (EHA) in 12 major Texas metropolitan statistical areas (MSAs) for the 10-year period, 2004–2013. A two-stage approach was employed to examine the associations between cold weather and EHA. First, the cold effects on each MSA were estimated using distributed lag non-linear models (DLNM). Then a random effects meta-analysis was applied to estimate pooled effects across all 12 MSAs. Percent increase in risk and corresponding 95% confidence intervals (CIs) were estimated as with a 1 °C (°C) decrease in temperature below a MSA-specific threshold for cold effects. Age-stratified and cause-specific EHA were modeled separately. The majority of the 12 Texas MSAs were associated with an increased risk in EHA ranging from 0.1% to 3.8% with a 1 ⁰C decrease below cold thresholds. The pooled effect estimate was 1.6% (95% CI: 0.9%, 2.2%) increase in all-cause EHA risk with 1 ⁰C decrease in temperature. Cold wave effects were also observed in most eastern and southern Texas MSAs. Effects of cold on all-cause EHA were highest in the very elderly (2.4%, 95% CI: 1.2%, 3.6%). Pooled estimates for cause-specific EHA association were strongest in pneumonia (3.3%, 95% CI: 2.8%, 3.9%), followed by chronic obstructive pulmonary disease (3.3%, 95% CI: 2.1%, 4.5%) and respiratory diseases (2.8%, 95% CI: 1.9%, 3.7%). Cold weather generally increases EHA risk significantly in Texas, especially in respiratory diseases, and cold effects estimates increased by elderly population (aged over 75 years). Our findings provide insight into better intervention strategy to reduce adverse health effects of cold weather among targeted vulnerable populations.

BackgroundCombining poly (ADP-ribose) polymerase (PARP) with phosphatidylinositol-3-kinase (PI3K) pathway inhibitors is supported by strong preclinical rationale. We sought to assess safety and determine a recommended phase 2 dose (RP2D) for PARP inhibitor olaparib combined with the AKT inhibitor, capivasertib, and evaluate molecular markers of response and resistance.MethodsAs part of a larger phase 1b trial, we performed a safety lead in of olaparib and capivasertib followed by expansion (n=24) in endometrial, triple negative breast, ovarian, fallopian tube, or peritoneal cancer. Olaparib 300mg orally twice daily and capivasertib orally twice daily on a four day on three day off schedule was evaluated. Two dose levels (DL) were planned: capivasertib 400mg (DL1); capivasertib 320mg (DL-1). Patients underwent biopsies at baseline and after 28 days.Findings38 patients were enrolled. 7 (18%) patients had known germlineBRCA1/2mutations. The first two patients on DL1 experienced dose limiting toxicities (DLTs) of diarrhea and vomiting in absence of maximum supportive care. No DLTs were observed on DL-1 (n=6), therefore, DL1 was re-explored (n=6) with no DLTs, confirming this as RP2D. Most common treatment-related grade 3 or 4 adverse events were anemia (23.7%) and leukopenia (10.5%).Of 32 subjects evaluable for response, 6 (19%) had partial response (PR) with a PR rate of 44.4% in endometrial cancer. Seven (22%) additional patients had stable disease greater than 4 months. Tumor analysis demonstrated strong correlation between response and immune activity, as well as alterations in cell cycle and DNA damage response genes. Therapy resistance was associated with receptor tyrosine kinase (RTK) and RAS-MAPK pathway activity, as well as metabolism and epigenetics.InterpretationThe combination of olaparib and capivasertib is well tolerated and demonstrates evidence of durable activity in women’s cancers, with particularly promising response in endometrial cancer. Importantly, tumor samples acquired pre and on-therapy can help predict patient benefit.FundingAstraZeneca, MDACC Moonshots Program, MDACC Support Grant CA016672 NCI SPOREs in Ovarian (CA217685) and Uterine (CA098258) Cancer and a kind gift from the Miriam and Sheldon Medical Research Foundation. AZD5363 was discovered by AstraZeneca subsequent to a collaboration with Astex Therapeutics (and its collaboration with the Institute of Cancer Research and Cancer Research Technology Limited).

OBJECTIVE: To evaluate the utility of patient-reported outcomes (PROs) to measure physical functioning in perioperative care for patients with gynecological (GYN) tumors. METHODS: 180 patients with GYN tumors undergoing open surgery participated in this longitudinal study. The physical functioning was measured by a subjective PRO tool, the Interference subscales of the MD Anderson Symptom Inventory (MDASI-I); as well as by an objective tool, the Timed Up & Go test (TUGT), perioperatively. Longer time (>20 seconds) needed to complete the TUGT was defined as “Prolonged”. Patients completed EuroQoL-5D as well. The association between the scores of MDASI-I items and TUGT was assessed via the Spearman correlation coefficient. The known-group validity was assessed using the t-test and Cohen’s D effect size. RESULTS: Compliance rates at preoperative, discharge and postoperative time points of MDASI-I were 98%, 95%, 96%; while TUGT completion rates were 92%, 75%, and 80%, respectively. Patients who had refused TUGT at discharge reported a significantly worse “MDASI-general activity” score compared to patients who completed TUGT (mean score of 7.00 vs. 5.38, P=0.020). Patient-reported “Walking” on MDASI-I significantly differentiated patients with prolonged vs. those with frail/normal TUGT at discharge (mean score of 4.89 vs. 2.79, Cohen’s d effect size = 0.82, P < 0.001) MDASI-I demonstrated excellent known-group validity per performance status and for the EuroQoL-5D subscales. CONCLUSION: Patient-reported physical functioning impairment after GYN surgery correspond with observed worse scores of the objective functioning measure test (TUGT). MDASI-I assessment represents a feasible and valid tool to evaluate functional status and warrants further implementation in the perioperative setting.

Chimeric antigen receptor (CAR) T cell therapy is being increasingly used to treat patients with advanced hematologic malignancies; however, the symptoms related to standard of care CAR T cell therapy during the first year after treatment have not been assessed using patient-reported outcome (PRO) measurements. This study aimed to quantify patients' perspectives of symptom burden and functional status using PROs during the first year after CAR T cell therapy for hematologic malignancies, especially in patients who experienced grade 2-4 toxicities. Sixty patients were enrolled in this observational cross-sectional study at any time during their first 12 months post-treatment. All 60 had received CAR T cell therapy as standard of care at MD Anderson Cancer Center in 2019. PROs were measured using the MD Anderson Symptom Inventory (MDASI), the PROs Measurement Information System 29 (PROMIS-29), the global health tool EQ5D-5L, and the single-item health-related quality of life scale (HRQoL). Twenty-two additional symptoms related to CAR T cell therapy, as identified by an expert panel, were also evaluated. CAR T cell therapy-related toxicities were rated according to the ASTCT consensus grading criteria. The majority of patients (52 of 60; 87%) received axicabtagene ciloleucel (Yescarta). One-third of the patients developed grade 2-4 cytokine release syndrome or neurotoxicity. The first 90 days after infusion represented the most symptomatic period, in which >10% of patients rated 18 symptoms as severe (ie, MDASI symptom score of 7 to 10 on scale of 0 to 10), strongly indicating the need for effective symptom management. Physical functioning, measured by interference on the "general activity" item on the MDASI and this domain on the PROMIS-29, were significantly worse in patients who underwent therapy during the first 30 days compared with those who underwent therapy over 90 days (all P < .05 with the Hochberg step-up procedure), whereas the EQ5D-5L and single-item HRQoL did not detect such differences. Compared with patients who had mild cytokine release syndrome or neurotoxicity (grade 0-1), patients who developed grade 2-4 toxicities persistently reported multiple severe symptoms after 30 days following therapy (all P < .05). Furthermore, although using a different recall period, patient-reported scores on several PROMIS-29 domains were significantly correlated with the scores of corresponding MDASI symptom items. This real-world quantitative PRO symptoms study provides evidence of unique profiles of the physical, psychological, and cognitive symptom burden in patients undergoing CAR T cell therapy that varies within the first year after infusion and demonstrates differences among PRO measurement scales. These results support the need for validation of fit-for-purpose PRO measurements for routinely monitoring symptom and toxicity burdens in CAR T cell therapy care settings.

Kriging interpolation and land use regression (LUR) have characterized the spatial variability of long-term nitrogen dioxide (NO

Background: Cardiovascular disease (CVD) has been estimated to account for nearly 50% of total deaths during cold seasons, and cold weather has been shown to have a significant impact on CVD. More importantly, detrimental health effects of cold were particularly pronounced in regions with mild winter climate. Texas is the second largest state in the U.S. and is associated with varying climates. This study aims to improve the understanding of how cold weather affects CVD-related mortality and morbidity in Texas. Methods: We obtained mortality data (1990-2013) and emergency hospital admissions (EHA) data (2003-2014) from the Texas Department of State Health Services and weather data from the National Climate Data Center. Our analysis included cases diagnosed as cardiovascular disease (CVD, ICD-9 390-429; ICD-10 I01-I52), ischemic heart disease (IHD, ICD-9 410-414; ICD-10 I20-I52), myocardial infarction disease (MI, ICD-9 410; ICD-10 I21, I22) and stroke (ICD-9 430-438; ICD-10 I60-I69). We first applied Poisson regression models to 12 Texas major Metropolitan Areas (MSAs) to estimate cold effects on deaths and hospital admissions related to CVDs. A random effects meta-regression analysis was then used to estimate pooled effects for the entire state. Results: With a 1°C decrease in temperature below a MSA-specific threshold, increased death risks were observed in CVDs (1.8% [95%CI: 1.1%, 2.6%]), stroke (1.2% [95%CI: -0.2%, 2.6%]), IHD 2.5% [95%CI: 1.1%, 4.0%], and MI 4.3% [95%CI: 1.2%, 7.5%]). Estimates of cold effects were lower for EHA risks, and they were 1.1% (95%CI: 0.4%, 1.8%) for CVDs, 2.3% (95%CI: -0.3%, 4.9%) for stroke, 1.7% (95%CI: -0.1%, 3.6%) for IHD, and 0.3% (95%CI: -3.5%, 4.2%) for MI. Conclusion: This is the first multi-city study in the U.S. that examined the effect of cold weather on CVD using both mortality and hospital admission data. Cold weather increases mortality risk significantly but less in EHA risk in Texas, and effects vary geographically. Our findings can provide insights to design better intervention strategies for targeted vulnerable populations towards reducing adverse health effects of cold weather.

Background The prevalence of allergic rhinitis (AR) continues to increase, and the greatest increases were observed mostly in non-Western regions, particularly Asian and Pacific regions; however, only a few studies have been conducted in Asia. Objectives Using Taiwan as an example of a typical Asian country, this study aimed to evaluate the association between green areas and the frequency of clinical visits for AR among children in Asia. Methods We used the Longitudinal Health Insurance Database to identify subjects diagnosed with AR at four years old in 2003, who were then followed up with until 2011. Greenness exposure was assessed using the MODIS Normalized Difference Vegetation Index (NDVI). The Generalized Additive Mixed Model (GAMM) was applied to examine the association between green areas and the rate of AR after controlling for confounders. Results The major results indicate a positive correlation, as green areas significantly increased the risk of AR by up to 8.4%. Further, sensitivity test analyses confirmed the robustness of the model estimates, even after adjusting for confounders. Stratified analysis results also display areas with high humidity and low temperatures increasing the risk of AR by up to 14% and 27%, respectively. In contrast, areas with low humidity and high temperatures decreased the risk of AR by up to 4% and 22%, respectively. Moreover, the positive relationship between greenness and AR among children was consistent across different sub-populations. Conclusions Greenness exposure contributes to an increased risk of allergic rhinitis (AR). This finding could serve as a reference for designing green landscapes, especially in residential areas.

Kriging interpolation and land use regression (LUR) have characterized the spatial variability of long-term nitrogen dioxide (NO2), but there has been little research on combining these two methods to capture small-scale spatial variation. Furthermore, studies predicting NO2 exposure are almost exclusively based on traffic-related variables, which may not be transferable to Taiwan, a typical Asian country with diverse local emission sources, where densely distributed temples and restaurants may be important for NO2 levels. To advance the exposure estimates in Taiwan, a hybrid kriging/LUR model incorporates culture-specific sources as potential predictors. Based on 14-year NO2 observations from 73 monitoring stations across Taiwan, a set of interpolated NO2 values were generated through a leave-one-out ordinary kriging algorithm, and this was included as an explanatory variable in the stepwise LUR procedures. Kriging interpolated NO2 and culture-specific predictors were entered in the final models, which captured 90% and 87% of NO2 variation in annual and monthly resolution, respectively. Results from 10-fold cross-validation and external data verification demonstrate robust performance of the developed models. This study demonstrates the value of incorporating the kriging-interpolated estimates and culture-specific emission sources into the traditional LUR model structure for predicting NO2, which can be particularly useful for Asian countries.

Airborne fungal spores, a type of bioaerosols, are significant air pollutants. We conducted a study to determine the spatiotemporal distributions of ambient fungi in the Greater Taipei area and develop land use regression (LUR) models for total and major fungal taxa. Four seasonal sampling campaigns were conducted over a year at 44 representative sites. Multiple regressions were performed to construct the LUR models. Ascospores were the most prevalent category, followed by Aspergillus/Penicillium, basidiospores, and Cladosporium. The highest fungal concentrations were found in spring. According to the LUR models, higher concentrations of Aspergillus/Penicillium and basidiospores were respectively present in residential/commercial areas and in areas with shorter road lengths. Various meteorological factors, particulates with aerodynamic diameters of ≤10 μm, and elevation also had significant relationships with fungal concentrations. The LUR models developed in this study can be used to assess spatiotemporal fungal distribution in the Greater Taipei area.

Ambient bacteria and endotoxins are components of bioaerosols, which are abundant in ambient air. Exposure to ambient bacteria and endotoxins has been associated with respiratory symptoms. We monitored the spatiotemporal distributions of ambient bioaerosols in the Greater Taipei area by using multisite sampling and developed regression models for ambient bacterial and endotoxin concentrations. Forty-four representative sampling sites were selected from the Greater Taipei area. Samples were collected in 4 seasons throughout a 1-y study period. Ambient bacteria were quantified using acridine orange staining, and endotoxins were analyzed using Limulus amebocyte lysate assays. Land-use types and major determinants of the bioaerosols were used to develop regression models. Ambient bacteria ranged from < limit of detection (LOD) to 1.68 × 105 cells/m3, whereas endotoxins ranged from < LOD to 20.62 EU/m3. Significant seasonal variations were observed for both bioaerosols, with the highest concentrations observed in spring. Regression analyses revealed temperature, relative humidity, and particulate matter as the major predictors of ambient bacteria and endotoxins. No land-use type was correlated with any of the bioaerosols. The number of schools and gas stations was positively associated with both bioaerosols. The leave-one-out cross-validation R2 of the final models for ambient bacteria and endotoxins were 0.11 and 0.31, respectively. The results of this study revealed high spatiotemporal variations in the distributions of ambient bacteria and endotoxins in the Greater Taipei area. Additional potential predictors should be included in future studies to develop better predictive models for ambient bacteria and endotoxins.

Effects of land use on temperatures during severe heat waves have been rarely studied. This paper examines land use-temperature associations during the 2011 heat wave in Greater Houston. We obtained high resolution of satellite-derived land use data from the US National Land Cover Database, and temperature observations at 138 weather stations from Weather Underground, Inc (WU) during the August of 2011, which was the hottest month in Houston since 1889. Land use regression and quantile regression methods were applied to the monthly averages of daily maximum/mean/minimum temperatures and 114 land use-related predictors. Although selected variables vary with temperature metric, distance to the coastline consistently appears among all models. Other variables are generally related to high developed intensity, open water or wetlands. In addition, our quantile regression analysis shows that distance to the coastline and high developed intensity areas have larger impacts on daily average temperatures at higher quantiles, and open water area has greater impacts on daily minimum temperatures at lower quantiles. By utilizing both land use regression and quantile regression on a recent heat wave in one of the largest US metropolitan areas, this paper provides a new perspective on the impacts of land use on temperatures. Our models can provide estimates of heat exposures for epidemiological studies, and our findings can be combined with demographic variables, air conditioning and relevant diseases information to identify 'hot spots' of population vulnerability for public health interventions to reduce heat-related health effects during heat waves. Language: en

Cold weather was estimated to account for more than half of weather-related deaths in the U.S. during 2006–2010. Studies have shown that cold-related excessive mortality is especially relevant with decreasing latitude or in regions with mild winter. However, only limited studies have been conducted in the southern U.S. The purpose of our study is to examine impacts of cold weather on mortality in 12 major Texas Metropolitan Areas (MSAs) for the 22-year period, 1990–2011. Our study used a two-stage approach to examine the cold-mortality association. We first applied distributed lag non-linear models (DLNM) to 12 major MSAs to estimate cold effects for each area. A random effects meta-analysis was then used to estimate pooled effects. Age-stratified and cause-specific mortalities were modeled separately for each MSA. Most of the MSAs were associated with an increased risk in mortality ranging from 0.1% to 5.0% with a 1 °C decrease in temperature below the cold thresholds. Higher increased mortality risks were generally observed in MSAs with higher average daily mean temperatures and lower latitudes. Pooled effect estimate was 1.58% (95% Confidence Interval (CI) [0.81, 2.37]) increase in all-cause mortality risk with a 1 °C decrease in temperature. Cold wave effects in Texas were also examined, and several MSAs along the Texas Gulf Coast showed statistically significant cold wave-mortality associations. Effects of cold on all-cause mortality were highest among people over 75 years old (1.86%, 95% CI [1.09, 2.63]). Pooled estimates for cause-specific mortality were strongest in myocardial infarction (4.30%, 95% CI [1.18, 7.51]), followed by respiratory diseases (3.17%, 95% CI [0.26, 6.17]) and ischemic heart diseases (2.54%, 95% CI [1.08, 4.02]). In conclusion, cold weather generally increases mortality risk significantly in Texas, and the cold effects vary with MSAs, age groups, and cause-specific deaths.

Background Heat waves have been linked to increased risk of mortality and morbidity, and are projected to increase in frequency and intensity in a changing climate. Houston and other areas in Texas experienced an exceptional heat wave in the summer of 2011 producing the hottest August on record. This study aims to assess the health-related impact of this heat wave. Methods Distributed lag models were used to estimate associations between the 2011 heat wave and all-cause mortality and emergency department (ED) visits from May 1 through September 30 for the five-year period 2007–2011. The 2011 heat wave is defined as a continuous period from August 2 through 30, 2011 according to the heat advisories issued by the local National Weather Service office, and is included in the models as a dummy variable. We compared the estimated excess risk among the models with and without adjustment of continuous temperature and ozone. Results The 2011 heat wave in Houston was associated with a 3.6% excess risk in ED visits (95% CI: 0.6%, 6.6%) and 0.6% increase in mortality risk (95% CI: -5.5%, 7.1%). The elderly over 65 years of age were at the greatest risk in ED visits. These patterns are consistent across different heat-wave definitions, and results are similar when adjusting for continuous temperature and ozone. Conclusions The 2011 heat wave in Houston had a substantial impact on ED visits and no significant impact on mortality. Our findings provide insights into local heat-wave and health preparations and interventions. Electronic supplementary material The online version of this article (doi:10.1186/1476-069X-14-11) contains supplementary material, which is available to authorized users.