| 1. |
- Elsawy, Mahmoud, et al.
(författare)
-
Patient-reported outcomes in ZUMA-7, a phase 3 study of axicabtagene ciloleucel in second-line large B-cell lymphoma
- 2022
-
Ingår i: Blood. - : American Society of Hematology. - 0006-4971 .- 1528-0020. ; 140:21, s. 2248-2260
-
Tidskriftsartikel (refereegranskat)abstract
- Here, we report the first comparative analysis of patient-reported outcomes (PROs) with chimeric antigen receptor T-cell therapy vs standard-of-care (SOC) therapy in second-line relapsed/refractory large B-cell lymphoma (R/R LBCL) from the pivotal randomized phase 3 ZUMA-7 study of axicabtagene ciloleucel (axi-cel) vs SOC. PRO instruments were administered at baseline, day 50, day 100, day 150, month 9, and every 3 months from randomization until 24 months or an event-free survival event. The quality of life (QoL) analysis set comprised patients with a baseline and >= 1 follow-up PRO completion. Pre-specified hypotheses for Quality of Life Questionnaire-Core 30 (QLQ-C30) physical functioning, global health status/QoL, and EQ-5D-5L visual analog scale (VAS) were tested using mixed-effects models with repeated measures. Clinically meaningful changes were defined as 10 points for QLQ-C30 and 7 for EQ-5D-5L VAS. Among 359 patients, 296 (165 axi-cel, 131 SOC) met inclusion criteria for QoL analysis. At day 100, statistically significant and clinically meaningful differences in mean change of scores from baseline were observed favoring axi-cel over SOC for QLQ-C30 global health status/QoL (estimated difference 18.1 [95% confidence interval (CI), 12.3-23.9]), physical functioning (13.1 [95% CI, 8.0-18.2]), and EQ-5D-5L VAS (13.7 [95% CI, 8.5-18.8]; P < .0001 for all). At day 150, scores significantly favored axi-cel vs SOC for global health status/QoL (9.8 [95% CI, 2.6-17.0]; P = .0124) and EQ-5D-5L VAS (11.3 [95% CI, 5.4-17.1]; P = .0004). Axi-cel showed clinically meaningful improvements in QoL over SOC. Superior clinical outcomes and favorable patient experience with axi-cel should help inform treatment choices in second-line R/ R LBCL.
|
|
| 2. |
|
|
| 3. |
- Holmfeldt, Linda, et al.
(författare)
-
The genomic landscape of hypodiploid acute lymphoblastic leukemia
- 2013
-
Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 45:3, s. 242-252
-
Tidskriftsartikel (refereegranskat)abstract
- The genetic basis of hypodiploid acute lymphoblastic leukemia (ALL), a subtype of ALL characterized by aneuploidy and poor outcome, is unknown. Genomic profiling of 124 hypodiploid ALL cases, including whole-genome and exome sequencing of 40 cases, identified two subtypes that differ in the severity of aneuploidy, transcriptional profiles and submicroscopic genetic alterations. Near-haploid ALL with 24-31 chromosomes harbor alterations targeting receptor tyrosine kinase signaling and Ras signaling (71%) and the lymphoid transcription factor gene IKZF3 (encoding AIOLOS; 13%). In contrast, low-hypodiploid ALL with 32-39 chromosomes are characterized by alterations in TP53 (91.2%) that are commonly present in nontumor cells, IKZF2 (encoding HELIOS; 53%) and RB1 (41%). Both near-haploid and low-hypodiploid leukemic cells show activation of Ras-signaling and phosphoinositide 3-kinase (PI3K)-signaling pathways and are sensitive to PI3K inhibitors, indicating that these drugs should be explored as a new therapeutic strategy for this aggressive form of leukemia.
|
|
| 4. |
- Lozano, Rafael, et al.
(författare)
-
Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
- 2018
-
Ingår i: The Lancet. - : Elsevier. - 1474-547X .- 0140-6736. ; 392:10159, s. 2091-2138
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59·4 (IQR 35·4–67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6–14·0) to a high of 84·9 (83·1–86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030.
|
|
| 5. |
- Ma, Christina Zong-Hao, et al.
(författare)
-
A Newly-Developed Smart Insole System with Instant Reminder: Paves the Way towards Integrating Artificial Intelligence (AI) Technology to Improve Balance and Prevent Falls
- 2019
-
Ingår i: Age and Ageing. - : Oxford University Press. - 0002-0729 .- 1468-2834. ; 48:Issue Supplement_4, s. iv28-iv33
-
Tidskriftsartikel (refereegranskat)abstract
- BackgroundFalls in senior people have high incidence& lead to severe injuries [1]. Application of smart wearable systems (with sensors to monitor user’s balance and corresponding instant reminder to let tusers adjust posture/motion) can effectively improve static standing balance [2], reduce reaction time and body sway in response to balance perturbation [3], improve walking pattern [4], and reduce the risk of falls [5, 6]. However, previous systems have not considered the daily monitor of user’s balance and falling risks, and the personalized reminder. Artificial intelligence (AI) and big data analytics have been widely used to monitor the daily physical activity [7], while few studies have utilized them to improve balance/gait and prevent falls.MethodsThis study has optimized previous devices by integrating AI technology and developed a new smart insole system. The system consisted of insoles with embedded sensors that can capture the foot motion and plantar pressure, smart watch that connected with insoles wirelessly and then transmitted the foot motion and force data to Cloud server via Wi-Fi, central Cloud server for big data transmission and storage, workstation for big data analytics and machine learning, and user interface for data visualization (e.g. smartphone, tablet, and/or laptop).Results & DiscussionThe system transmission rate was up to 30 Hz. The collected big data contained all sensor signals captured before and after delivering reminder, and from day-to-day monitoring of users. The customized reminder varied in the type, frequency, magnitude, and amount/dosage. This AI smart insole system enabled the monitor of daily balance and falling risks and the provision of timely-updated and customized reminder to users, which could potentially reduce the risk of falls and slips. It can also act as a balance-training device.
|
|
| 6. |
- Ma, Christina Zong-Hao, et al.
(författare)
-
Smart Insole and Smartwatch System with Big Data Analytics to Improve Balance Training and Walking Ability
- 2019
-
Konferensbidrag (refereegranskat)abstract
- BACKGROUND Applying wearable motion sensors to capture balance/gait performance and provide the corresponding biofeedback/reminder have been proved effective in improving users’ balance/gait [1-5]. Unfortunately, previous approach of providing pre-set biofeedback did not consider user’s individual balance performance or training process during various tasks. Big data analytics and machine learning technologies have been widely used to monitor the daily physical activity [6-8]. However, few previous studies have utilized these technologies to improve balance/gait training.AIM This study aimed to develop a foot-motion based smart insole and smartwatch system integrated with big data analytics, and investigate its effect on improvement of balance training in patients with stroke.METHOD The newly-developed system with big data analytics can collect and store patients’ balance performance and their response to the reminder/biofeedback during each session of balance/gait training. With the collected huge amount of data (big data) of patients’ balance and response to the biofeedback, the system can identify and extract the feature of patients’ response upon receiving the biofeedback, and further deliver the customized biofeedback (that gradually changed according to the balance improvement) for patients to further improve balance and gait training outcomes (machine learning).A randomized controlled trial will be conducted on 12 patients with stroke by evaluating patient’s balance/gait training outcomes with and without using the developed system.RESULTSThe development of hardware of the system were completed, and the development of software were in progress. The system contained: 1) personal unit with force and motion sensors placed at both feet to capture the foot motion, and a smartwatch at wrist to collect data from both feet via Bluetooth and then transmit the data to the central cloud server via WiFi; 2) central cloud servers for data transmission and storage; 3) user interface for data analysis, which included a smartphone, tablet, and/or laptop; and 4) workstation for big data analytics (Figure 1). The collected data involved all sensor signals the system received before and after delivering biofeedback, and from day to day monitoring of patients. The customized biofeedback pattern included various type, frequency, magnitude, and amount/dosage of biofeedback.DISCUSSION AND CONCLUSION The introduced system adopted big data and machine learning technologies to provide the repetitive targeted balance and gait training based on each patient’s condition. With further optimization, this system can also be applied in elderly and other patients with balance disorders for various daily tasks, including standing, walking, and obstacle crossing. This will enhance the balance training outcomes and potentially reduce the risk of falls in the future.REFERENCES Ma, C.Z.-H.; 2018 Top Stroke Rehabil.Ma, C.Z.-H.; 2017 Hum Mov Sci.Ma, C.Z.-H.; 2016 Sensors.Ma, C.Z.-H.; 2015 Sensors.Wan, A.-H.; 2016 Arch Phys Med Rehabil.Wu, J.; 2017 INT J PROD RES.Badawi, H.F.; 2017 Future Gener Comput Syst.Gravina, R.; 2017 Future Gener Comput Syst. ACKNOWLEDGEMENTS This work was partially supported by The Hong Kong Polytechnic University [grant number: G-YBRN].
|
|
| 7. |
- Ma, Christina Zong-Hao, et al.
(författare)
-
Towards Wearable Comprehensive Capture and Analysis of Skeletal Muscle Activity during Human Locomotion
- 2019
-
Ingår i: Sensors. - Basel, Switzerland : MDPI. - 1424-8220. ; 19:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Motion capture and analyzing systems are essential for understanding locomotion. However, the existing devices are too cumbersome and can be used indoors only. A newly-developed wearable motion capture and measurement system with multiple sensors and ultrasound imaging was introduced in this study. Methods: In ten healthy participants, the changes in muscle area and activity of gastrocnemius, plantarflexion and dorsiflexion of right leg during walking were evaluated by the developed system and the Vicon system. The existence of significant changes in a gait cycle, comparison of the ankle kinetic data captured by the developed system and the Vicon system, and test-retest reliability (evaluated by the intraclass correlation coefficient, ICC) in each channel’s data captured by the developed system were examined. Results: Moderate to good test-retest reliability of various channels of the developed system (0.512 ≤ ICC ≤ 0.988, p < 0.05), significantly high correlation between the developed system and Vicon system in ankle joint angles (0.638R ≤ 0.707, p < 0.05), and significant changes in muscle activity of gastrocnemius during a gait cycle (p < 0.05) were found. Conclusion: A newly developed wearable motion capture and measurement system with ultrasound imaging that can accurately capture the motion of one leg was evaluated in this study, which paves the way towards real-time comprehensive evaluation of muscles and joint motions during different activities in both indoor and outdoor environments.
|
|
| 8. |
- Palkopoulou, Eleftheria, et al.
(författare)
-
A comprehensive genomic history of extinct and living elephants
- 2018
-
Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : NATL ACAD SCIENCES. - 0027-8424 .- 1091-6490. ; 115:11, s. E2566-E2574
-
Tidskriftsartikel (refereegranskat)abstract
- Elephantids are the world's most iconic megafaunal family, yet there is no comprehensive genomic assessment of their relationships. We report a total of 14 genomes, including 2 from the American mastodon, which is an extinct elephantid relative, and 12 spanning all three extant and three extinct elephantid species including an similar to 120,000-y-old straight-tusked elephant, a Columbian mammoth, and woolly mammoths. Earlier genetic studies modeled elephantid evolution via simple bifurcating trees, but here we show that interspecies hybridization has been a recurrent feature of elephantid evolution. We found that the genetic makeup of the straight-tusked elephant, previously placed as a sister group to African forest elephants based on lower coverage data, in fact comprises three major components. Most of the straight-tusked elephant's ancestry derives from a lineage related to the ancestor of African elephants while its remaining ancestry consists of a large contribution from a lineage related to forest elephants and another related to mammoths. Columbian and woolly mammoths also showed evidence of interbreeding, likely following a latitudinal cline across North America. While hybridization events have shaped elephantid history in profound ways, isolation also appears to have played an important role. Our data reveal nearly complete isolation between the ancestors of the African forest and savanna elephants for similar to 500,000 y, providing compelling justification for the conservation of forest and savanna elephants as separate species.
|
|
