Real-world evidence research based on big data: Motivation-challenges-success factors

Real-world study on the application of enhanced recovery after surgery protocol in video-assisted thoracoscopic day surgery for pulmonary nodule resection

OBJECTIVE

This study aims to evaluate the real-world effectiveness of applying different levels of Enhanced Recovery After Surgery (ERAS) guidelines to video-assisted thoracic day surgery (VATS). The goal is to determine the optimal degree of ERAS protocols and management requirements to improve postoperative recovery outcomes.

METHODS

It was designed as a single-centre, prospective pragmatic randomized controlled trial (PRCT), including patients who underwent VATS at the Day Surgery Center of West China Hospital, between January 2021 and November 2022. Patients were divided into Group A and Group B through convenience sampling to implement different levels of ERAS management protocols. Data collection included the baseline characteristics (gender, age, marital status, education level, BMI, PONV risk score, ASA classification), surgery-related indicators (type of surgery, pathological results, hospitalization costs, duration of surgery, intraoperative blood loss, intraoperative rehydration volume), postoperative recovery indicators (postoperative chest tube duration time, time to first postoperative ambulation and urination, postoperative complications, follow-up condition), pain-related indicators (pain threshold score, pain score at 6 h postoperatively, bedtime, and predischarge), psychological state indicators (anxiety level), Athens Insomnia Scale (AIS) scores, and social support scores. Propensity score matching (PSM) was utilized and statistical analyses were conducted using R version 4.4.1. Comparisons of categorical variables were performed using the χ² test, while comparisons of continuous variables were conducted using ANOVA or the Kruskal-Wallis rank-sum test. A significance level of α = 0.05 was set for statistical tests.

RESULT

A total of 340 patients were included, with 187 in Group A and 153 in Group B. After propensity score matching (PSM), there were 142 patients in Group A and 105 in Group B, with no significant baseline differences. Group A had a significantly higher proportion of chest tube removals within 24 h postoperatively (P < 0.001) and earlier mobilization (P < 0.001). Despite a higher pain threshold in Group A (P = 0.016), their postoperative pain scores were not higher than those in Group B. Additionally, Group A had a lower incidence of postoperative complications.

CONCLUSION

The more comprehensive ERAS protocol significantly improved postoperative recovery, confirming its value in day-case VATS and supporting its clinical adoption. However, the study has limitations; future research should focus on standardizing ERAS protocols and expanding their application to a broader patient population to validate these findings further.

TRAIL REGISTRATION

This study underwent review by the Ethics Committee of West China Hospital of Sichuan University under No. 2020 (1001). It has been officially registered with the China Clinical Trial Registry, TRN: ChiCTR2100051372 and registration date is Sept. 22, 2021.

Real-World Incidence and Severity of Hypertension Caused by Abiraterone Acetate in Patients With Metastatic Prostate Cancer

BACKGROUND

Abiraterone acetate (AA) is used in treatment of patients with metastatic prostate cancer. Despite the survival advantage, AA is associated with hypertension due to mineralocorticoid excess syndrome.

OBJECTIVE

We conducted a single-center retrospective analysis to evaluate the real-world incidence and severity of AA-induced hypertension.

METHODS

Electronic health records were used to collect baseline characteristics and prostate cancer history. Patient data, including blood pressure at each 4 (±2)-week interval, were collected for 24 weeks after the initiation of AA therapy. The primary endpoint was the incidence and severity of AA-induced hypertension. The secondary endpoints include effect of different prednisone dosing regimens and prostate cancer types on hypertensive incidence and the impact of clinical pharmacists' involvement in managing AA-induced hypertension.

RESULTS

A total of 142 patients who met our inclusion criteria received AA for metastatic prostate cancer, 73 (51.4%) with metastatic castration-resistant prostate cancer (mCRPC), and 69 (48.6%) with metastatic castration-sensitive prostate cancer (mCSPC). Of all, 43.7% experienced all-grade hypertension, and 28.2% experienced grade 3-4 hypertension. There was no difference in incidence of hypertension between patients receiving 5 mg of prednisone daily and those receiving 5 mg of prednisone twice daily. All-grade hypertension occurred in 39.7% of mCRPC and 47.8% of mCSPC patients (P = 0.33). Thirty-two percent of patients were actively managed by a clinical pharmacist and had an overall trend of reduced hypertension severity after 12 weeks.

CONCLUSION AND RELEVANCE

This single-center, retrospective cohort study found that real-world metastatic prostate cancer patients who received AA had substantially higher incidence and severity of hypertension compared with clinical trials regardless of prednisone dose. In patients with mCRPC and mCSPC, the role of prednisone dose in hypertension incidence and severity warrants further investigation. Overall, results indicate the need for closely monitoring hypertension and optimization of anti-hypertensive therapy by multidisciplinary teams in metastatic prostate cancer patients receiving AA.

Views and opinions of patients with glaucoma and age-related macular degeneration on vision home-monitoring: a UK-based focus group study

OBJECTIVE

To investigate the views, hopes and concerns of patients living with glaucoma and age-related macular degeneration (AMD) regarding vision home-monitoring.

DESIGN

Qualitative study using focus groups and questionnaires. Participants were given three disease-relevant home-monitoring tests to try. The tests consisted of three visual field tests for the glaucoma groups (Melbourne Rapid Fields, Eyecatcher, Visual Fields Fast) and three acuity and/or contrast-sensitivity tests for AMD groups (Alleye, PopCSF, SpotChecks). Focus group data were thematically analysed.

SETTING

University meeting rooms in London, UK.

PARTICIPANTS

Eight people with glaucoma (five women, median age 74) and seven people with AMD (four women, median age 77) volunteered through two UK-based charities. Participants were excluded if they did not self-report a diagnosis of glaucoma or AMD or if they lived further than a 1-hour travel distance from the university (to ensure minimal travel burden on participants).

RESULTS

Six themes emerged from focus groups, the two most frequently referenced being: 'concerns about home-monitoring' and 'patient and practitioner access to results'. Overall, participants believed home-monitoring could provide patients with a greater sense of control, but also expressed concerns, including: the possibility of home-monitoring replacing face-to-face appointments; the burden placed on clinicians by the need to process additional data; struggles to keep up with requisite technologies; and potential anxiety from seeing worrying results. Most devices were scored highly for usability, though several practical improvements were suggested.

CONCLUSION

Patients with mild-to-moderate glaucoma/AMD expect vision home-monitoring to be beneficial, but have significant concerns about its potential implementation.

Generalizability in real-world trials

Real-world evidence (RWE) trials have a key advantage over conventional randomized controlled trials (RCTs) due to their potentially better generalizability. High generalizability of study results facilitates new biological insights and enables targeted therapeutic strategies. Random sampling of RWE trial participants is regarded as the gold standard for generalizability. Additionally, the use of sample correction procedures can increase the generalizability of trial results, even when using nonrandomly sampled real-world data (RWD). This study presents descriptive evidence on the extent to which the design of currently planned or already conducted RWE trials takes sampling into account. It also examines whether random sampling or procedures for correcting nonrandom samples are considered. Based on text mining of publicly available metadata provided during registrations of RWE trials on clinicaltrials.gov, EU-PAS, and the OSF-RWE registry, it is shown that the share of RWE trial registrations with information on sampling increased from 65.27% in 2002 to 97.43% in 2022, with a corresponding increase from 14.79% to 28.30% for trials with random samples. For RWE trials with nonrandom samples, there is an increase from 0.00% to 0.95% of trials in which sample correction procedures are used. We conclude that the potential benefits of RWD in terms of generalizing trial results are not yet being fully realized.

Energy landscape analysis and time-series clustering analysis of patient state multistability related to rheumatoid arthritis drug treatment: The KURAMA cohort study

Rheumatoid arthritis causes joint inflammation due to immune abnormalities, resulting in joint pain and swelling. In recent years, there have been considerable advancements in the treatment of this disease. However, only approximately 60% of patients achieve remission. Patients with multifactorial diseases shift between states from day to day. Patients may remain in a good or poor state with few or no transitions, or they may switch between states frequently. The visualization of time-dependent state transitions, based on the evaluation axis of stable/unstable states, may provide useful information for achieving rheumatoid arthritis treatment goals. Energy landscape analysis can be used to quantitatively determine the stability/instability of each state in terms of energy. Time-series clustering is another method used to classify transitions into different groups to identify potential patterns within a time-series dataset. The objective of this study was to utilize energy landscape analysis and time-series clustering to evaluate multidimensional time-series data in terms of multistability. We profiled each patient's state transitions during treatment using energy landscape analysis and time-series clustering. Energy landscape analysis divided state transitions into two patterns: "good stability leading to remission" and "poor stability leading to treatment dead-end." The number of patients whose disease status improved increased markedly until approximately 6 months after treatment initiation and then plateaued after 1 year. Time-series clustering grouped patients into three clusters: "toward good stability," "toward poor stability," and "unstable." Patients in the "unstable" cluster are considered to have clinical courses that are difficult to predict; therefore, these patients should be treated with more care. Early disease detection and treatment initiation are important. The evaluation of state multistability enables us to understand a patient's current state in the context of overall state transitions related to rheumatoid arthritis drug treatment and to predict future state transitions.

Using "Real-World Data" to Study Cleft Lip/Palate Care: An Exploration of Speech Outcomes from a Multi-Center US Learning Health Network

OBJECTIVE

To assess the ability of a cleft-specific multi-site learning health network registry to describe variations in cleft outcomes by cleft phenotypes, ages, and treatment centers. Observed variations were assessed for coherence with prior study findings.

DESIGN

Cross-sectional analysis of prospectively collected data from 2019-2022.

SETTING

Six cleft treatment centers collected data systematically during routine clinic appointments according to a standardized protocol.

PARTICIPANTS

714 English-speaking children and adolescents with non-syndromic cleft lip/palate.

INTERVENTION

Routine multidisciplinary care and systematic outcomes measurement by cleft teams.

OUTCOME MEASURES

Speech outcomes included articulatory accuracy measured by Percent Consonants Correct (PCC), velopharyngeal function measured by Velopharyngeal Competence (VPC) Rating Scale (VPC-R), intelligibility measured by caregiver-reported Intelligibility in Context Scale (ICS), and two CLEFT-Q™ surveys, in which patients rate their own speech function and level of speech distress.

RESULTS

12year-olds exhibited high median PCC scores (91-100%), high frequency of velopharyngeal competency (62.50-100%), and high median Speech Function (80-91) relative to younger peers parsed by phenotype. Patients with bilateral cleft lip, alveolus, and palate reported low PCC scores (51-91%) relative to peers at some ages and low frequency of velopharyngeal competency (26.67%) at 5 years. ICS scores ranged from 3.93-5.0 for all ages and phenotypes. Speech Function and Speech Distress were similar across phenotypes.

CONCLUSIONS

This exploration of speech outcomes demonstrates the current ability of the cleft-specific registry to support cleft research efforts as a source of "real-world" data. Further work is focused on developing robust methodology for hypothesis-driven research and causal inference.

Lung Function and Asthma Clinical Control in N-ERD Patients, Three-Year Follow-Up in the Context of Real-World Evidence

Purpose

To describe the lung function and clinical control of asthma in patients with N-ERD during three years of medical follow-up using GINA guidelines.

Methods

We evaluated 75 N-ERD and 68 asthma patients (AG). Clinical control, lung function, and asthma treatment were evaluated according to GINA-2014. We compared all variables at baseline and one, two, and three years after treatment.

Results

At baseline, the N-ERD group had better basal lung function (LF) than the AG group (p<0.01), and the AG group used higher doses of inhaled corticosteroids than the N-ERD group (52.4% vs 30.5%, p=0.01) and short-term oral corticosteroid (OCS) use (52.4% vs 30.5%, p<0.01). Instead, N-ERD patients needed more use of leukotriene receptor antagonists (LTRA) (29.3% vs 5.9%, p<0.01). This group had better clinical control than the AG group (62.1% vs 34.1%, p<0.01). During the medical follow-up, the LF of the N-ERD group remained at normal values; however, these parameters improved in AG from one year (p<0.01). Likewise, there was a diminished use of high doses of ICS (52.4% vs 33%, p<0.05) and short-term OCS (67.6% vs 20.6%, p<0.01) in asthma patients. However, N-ERD patients still needed more use of LTRAs (p<0.02) during the study. In this context, one-third of N-ERD patients had to use a combination of two drugs to maintain this control. From the second year on, clinical control of asthma was similar in both groups (p>0.05).

Conclusion

According to GINA guidelines, only one-third of patients with N-ERD can gradually achieve adequate lung function and good asthma control with a high ICS dosage. Only a very small portion of patients will require the continued use of a second medication as an LTRA to keep their asthma under control.

Bevacizumab-induced proteinuria and its association with antihypertensive drugs: A retrospective cohort study using a Japanese administrative database

Proteinuria is a major side-effect of the anti-tumor drug bevacizumab, although its incidence and risk factors in the real world are still unclear. Although renin-angiotensin-aldosterone system inhibitors are used clinically to prevent proteinuria, their efficacy remains unclear. The aim of the present study was to reveal the incidence and risk factors of bevacizumab-induced proteinuria and examine the effectiveness of antihypertensive drugs in preventing proteinuria. We conducted a retrospective cohort study using the National Hospital Organization Clinical Data Archives and Medical Information Analysis Databank. Hospitalized patients who received bevacizumab between January 1, 2016, and June 30, 2019, were included. The study outcome was proteinuria within 12 months of bevacizumab administration. Patient characteristics, laboratory tests, and medications were compared between patients with and without proteinuria using multivariable logistic regression analysis. Among the 2,458 patients, 27% developed proteinuria after bevacizumab administration. Nursing dependence (odds ratio [OR], 2.40; 95% confidence interval [CI], 1.89-3.05; P<0.001) and systolic blood pressure ≥140 mmHg (OR, 1.44; 95% CI, 1.17-1.79; P<0.001) were identified as risk factors. Patients with an estimated glomerular filtration rate (eGFR) of 60-89, 45-59, and <45 mL/min/1.73 m2 had 29.7%, 76.8%, and 66.0% higher odds of proteinuria, respectively, than those with an eGFR ≥90 mL/min/1.73 m2. No significant relationship was observed between antihypertensive drugs and the occurrence of proteinuria. More patients may suffer from proteinuria after bevacizumab administration than previously reported. Nursing dependence and systolic blood pressure are predictive risk factors for bevacizumab-induced proteinuria. Patients at risk of proteinuria should be closely monitored.

Generating fit-for-purpose real-world evidence in Asia: How far are we from closing the gaps?

Evidence generated by randomized controlled trials (RCTs) does not often represent the patient journey and clinical outcomes in the real world due to limited external validity or generalizability. Studies based on real-world data are intended to generalize results to the broader population; however, if the influence of external factors or confounders is not effectively managed, the cause-and-effect relationship and internal validity may be challenged, resulting in flawed results. The collection of quality real-world evidence (RWE) is crucial in Asia as there is often an underrepresentation of Asian populations in RCTs. In addition, few countries in Asia are catching up with the Western world in issuing practical foundational principles and guidance for conducting and adopting evidence for regulatory and reimbursement decisions. However, privacy and data protection laws are generally lagging behind technological developments in electronic medical records. While leveraging RWE in clinical and regulatory decision-making holds excellent potential, collective efforts across industry, governments, and research institutions are required for generating standardized practices and building capabilities for developing fit-for-purpose RWE in Asia.

Data Governance for Real-World Data Management: A Proposal for a Checklist to Support Decision Making

OBJECTIVES

Real-world data (RWD) and real-world evidence (RWE) can provide extensive information on healthcare for use in health technology assessment and decision making. Nevertheless, there is a lack of consensus surrounding the appropriate data governance (DG) practices for RWD/RWE. Data sharing is also a large concern, especially considering evolving data protection regulations. Our objective is to propose recommendations for international standards of evaluating the acceptability of RWD governance practices.

METHODS

After reviewing the literature, we created a checklist targeting DG practices for RWD/RWE. We then carried out a 3-round Delphi panel, including European policy makers, health technology assessment experts, and hospital managers. The consensus for each statement was measured and the checklist adjusted accordingly.

RESULTS

The literature review identified the main topics regarding RWD/RWE DG practices: data privacy and security, data management and linkage, data access management, and the generation and use of RWE. Members of the Delphi panel (21 experts/25 invited) were presented a total of 24 statements related to each of the topics. Experts demonstrated a progressive level of consensus and importance ratings in all topics and to most statements. We suggest a refined checklist in which the statements rated less important or with less consensus have been removed.

CONCLUSIONS

This study suggests how the DG of RWD/RWE could be qualitatively evaluated. We propose checklists that could be used by all RWD/RWE users to help ensure the quality and integrity of RWD/RWE governance and complement data protection law.

Prevalence Patterns and Onset Prediction of High Myopia for Children and Adolescents in Southern China via Real-World Screening Data: Retrospective School-Based Study

BACKGROUND

Patients with high myopia have an increased lifetime risk of complications. The prevalence patterns of high myopia in children and adolescents in southern China are unclear. Early identification of high-risk individuals is critical for reducing the occurrence and development of high myopia and avoiding the resulting complications.

OBJECTIVE

This study aimed to determine the prevalence of high myopia in children and adolescents in southern China via real-world screening data and to predict its onset by studying the risk factors for high myopia based on machine learning.

METHODS

This retrospective school-based study was conducted in 13 cities with different gross domestic products in southern China. Through data acquisition and filtering, we analyzed the prevalence of high myopia and its association with age, school stage, gross domestic product, and risk factors. A random forest algorithm was used to predict high myopia among schoolchildren and then assessed in an independent hold-out group.

RESULTS

There were 1,285,609 participants (mean age 11.80, SD 3.07, range 6-20 years), of whom 658,516 (51.2%) were male. The overall prevalence of high myopia was 4.48% (2019), 4.88% (2020), and 3.17% (2021), with an increasing trend from the age of 11 to 17 years. The rates of high myopia increased from elementary schools to high schools but decreased at all school stages from 2019 to 2021. The coastal and southern cities had a higher proportion of high myopia, with an overall prevalence between 2.60% and 5.83%. Age, uncorrected distance visual acuity, and spherical equivalents were predictive factors for high myopia onset in schoolchildren. The random forest algorithm achieved a high accuracy of 0.948. The area under the receiver operator characteristic curve (AUC) was 0.975. Both indicated sufficient model efficacy. The performance of the model was validated in an external test with high accuracy (0.971) and a high AUC (0.957).

CONCLUSIONS

High myopia had a high incidence in Guangdong Province. Its onset in children and adolescents was well predicted with the random forest algorithm. Efficient use of real-world data can contribute to the prevention and early diagnosis of high myopia.

Real World Analysis of Quality of Life and Toxicity in Cancer Patients Treated with Hyperthermia Combined with Radio(chemo)therapy

Hyperthermia (HT) in combination with radio(chemo)therapy (RCT) is a well-established cancer treatment strategy. This report analyses the quality of life (QoL), toxicity and survival outcomes in patients with different tumor entities who received HT in combination with RCT. The primary endpoint of this study was the assessment of QoL scale items 3 and 12 months after treatment in patients who were treated with palliative intent and curative intent, respectively. The secondary endpoints of this study were acute toxicities, 1-year overall survival (OS), and local progression-free survival (LPFS). Patients treated with curative intent experienced significant improvement in emotional functioning (EF), social functioning (SF), financial difficulties (FI) and insomnia (SL) 12 months after treatment. Patients had significantly improved FI and pain (PA) three months after palliative treatment. Acute toxicity of grade 3 or more was 26% during treatment and 4% after three months. The 1-year OS rates were 90% (95% CI: 79-96%) and 44% (95% CI: 31-59%) for patients treated with curative and palliative RCT combined with HT, respectively. Moreover, the 1-year LPFS rates were 94% (95% CI: 84-98%) for patients treated with curative intent and 64% (95% CI: 50-77%) for palliative patients. In summary, combined RCT and HT stabilized or improved QoL scale items for both curative and palliative indications.

Assessment and Improvement of Drug Data Structuredness From Electronic Health Records: Algorithm Development and Validation

BACKGROUND

Digitization offers a multitude of opportunities to gain insights into current diagnostics and therapies from retrospective data. In this context, real-world data and their accessibility are of increasing importance to support unbiased and reliable research on big data. However, routinely collected data are not readily usable for research owing to the unstructured nature of health care systems and a lack of interoperability between these systems. This challenge is evident in drug data.

OBJECTIVE

This study aimed to present an approach that identifies and increases the structuredness of drug data while ensuring standardization according to Anatomical Therapeutic Chemical (ATC) classification.

METHODS

Our approach was based on available drug prescriptions and a drug catalog and consisted of 4 steps. First, we performed an initial analysis of the structuredness of local drug data to define a point of comparison for the effectiveness of the overall approach. Second, we applied 3 algorithms to unstructured data that translated text into ATC codes based on string comparisons in terms of ingredients and product names and performed similarity comparisons based on Levenshtein distance. Third, we validated the results of the 3 algorithms with expert knowledge based on the 1000 most frequently used prescription texts. Fourth, we performed a final validation to determine the increased degree of structuredness.

RESULTS

Initially, 47.73% (n=843,980) of 1,768,153 drug prescriptions were classified as structured. With the application of the 3 algorithms, we were able to increase the degree of structuredness to 85.18% (n=1,506,059) based on the 1000 most frequent medication prescriptions. In this regard, the combination of algorithms 1, 2, and 3 resulted in a correctness level of 100% (with 57,264 ATC codes identified), algorithms 1 and 3 resulted in 99.6% (with 152,404 codes identified), and algorithms 1 and 2 resulted in 95.9% (with 39,472 codes identified).

CONCLUSIONS

As shown in the first analysis steps of our approach, the availability of a product catalog to select during the documentation process is not sufficient to generate structured data. Our 4-step approach reduces the problems and reliably increases the structuredness automatically. Similarity matching shows promising results, particularly for entries with no connection to a product catalog. However, further enhancement of the correctness of such a similarity matching algorithm needs to be investigated in future work.

Rildo: Real-World Multicenter Study on the Effectiveness and Safety of Single-Tablet Regimen of Dolutegravir plus Rilpivirine in Treatment-Experienced People Living with HIV

Two-drug regimens (2DRs) are emerging in clinical practice guidelines as treatment option for both naive and treatment-experienced people living with HIV (PLHIV). Objectives: To determine the real-life effectiveness of 2DR with 25 mg RPV plus 50 mg DTG in a single-tablet regimen (RPV/DTG_STR) and its impact on viral and immune status, lipid profile, and inflammatory markers. Methods: This observational study included 291 treatment-experienced PLHIV, starting 2DR with RPV/DTG_STR between 29 January 2019 and 2 February 2022, who were followed up for at least six months. Participants gave verbal informed consent for the switch in antiretroviral therapy (ART) to RPV/DTG_STR. Results: The mean age of the 291 participants was 51.3 years; 77.7% were male; and 42.9% were in the AIDS stage with a CD4 nadir of 283.5 ± 204.6 cells/uL. The median time since HIV diagnosis was 19.7 years (IQR: 10.6-27). Before 2DR, patients received a median of five ART lines (IQR: 3-7) for 22.2 years (IQR: 14-26), with 34.4% (n = 100) receiving a three-drug regimen (3DR), 31.3% (n = 91) receiving monotherapy, and 34.4% (n = 100) receiving 2DR. The median time on RPV/DTG_STR was 14 months (IQR: 9.5-21); 1.4% were lost to the follow-up. Effectiveness was 96.2% by intention-to-treat (ITT) analysis, 97.5% by modified ITT, and 99.3% by per-protocol analysis. Virological failure was observed in 0.69%, blips in 3.5%, and switch to another ART in 1.4%. The mean lipid profile improved, with reductions in TC/HDLc ratio (3.9 ± 0.9 vs. 3.6 ± 0.9; p = 0.0001), LDLc (118.3 ± 32.2 mg/dL vs. 106.2 ± 29.8 mg/dL, p = 0.0001), TG (130.9 ± 73.9 mg/dL vs. 115.9 ± 68.5 mg/dL, p = 0.0001), and CD4/CD8 ratio increase (0.99 ± 0.58 vs. 1.01 ± 0.54; p = 0.0001). The cost-effectiveness of 2DR with RPV/DTG_STR was similar to that of DTG/3TC and superior to those of BIC/TAF/FTC and DRV/c/TAF/FTC, with higher virological suppression and lower annual costs. Conclusions: The switch to RPV plus DTG in STR is a cost-effective, long-lasting, and robust strategy for PLHIV, with a very long experience of treatment, which improves the lipid profile without affecting inflammatory markers.

Applying process mining in health technology assessment

Objective

Propose a process mining-based method for Health Technology Assessment.

Methods

Articles dealing with prior studies in Health Technology Assessment using Process Mining were identified. Five research questions were defined to investigate these studies and present important points and desirable characteristics to be addressed in a proposal. The was defined method with five steps and was submitted to a case study for evaluation.

Results

The Literature search identified six main characteristics. As a result, the five-step method proposed was applied in the radical prostatectomy surgical procedure between the robot assisted technique and laparoscopy.

Conclusion

It was demonstrated in this article the creation of the proposal of an efficient method with its replication for other health technologies, coupled with the good interpretation of the specialists in terms of comprehensibility of the discovered patterns and their correlation with clinical protocols and guidelines.

Patterns of Care for Breast Radiotherapy in Italy: Breast IRRadiATA (Italian Repository of Radiotherapy dATA) Feasibility Study

Aim. Breast IRRADIATA (Italian Repository of RADIotherapy dATA) is a collaborative nationwide project supported by the Italian Society of Radiotherapy and Clinical Oncology (AIRO) and the Italian League Against Cancer (LILT). It focuses on breast cancer (BC) patients treated with radiotherapy (RT) and was developed to create a national registry and define the patterns of care in Italy. A dedicated tool for data collection was created and pilot tested. The results of this feasibility study are reported here. Methods. To validate the applicability of a user-friendly data collection tool, a feasibility study involving 17 Italian Radiation Oncology Centers was conducted from July to October 2021, generating a data repository of 335 BC patients treated between January and March 2020, with a minimum follow-up time of 6 months. A snapshot of the clinical presentation, treatment modalities and radiotherapy toxicity in these patients was obtained. A Data Entry Survey and a Satisfaction Questionnaire were also sent to all participants. Results. All institutions completed the pilot study. Regarding the Data Entry survey, all questions achieved 100% of responses and no participant reported spending more than 10 min time for either the first data entry or for the updating of follow-up. Results from the Satisfaction Questionnaire revealed that the project was described as excellent by 14 centers (82.3%) and good by 3 (17.7%). Conclusion. Current knowledge for the treatment of high-prevalence diseases, such as BC, has evolved toward patient-centered medicine, evidence-based care and real-world evidence (RWE), which means evidence obtained from real-world data (RWD). To this aim, Breast IRRADIATA was developed as a simple tool to probe the current pattern of RT care in Italy. The pilot feasibility of IRRADIATA encourages a larger application of this tool nationwide and opens the way to the assessment of the pattern of care radiotherapy directed to other cancers.

Use of algorithms for identifying patients in a German claims database: learnings from a lung cancer case

BACKGROUND

The analysis of statutory health insurance (SHI) data is a little-used approach for understanding treatment and care as well as resource use of lung cancer (LC) patients in Germany. The aims of this observational, retrospective, longitudinal analysis of structured data were to analyze the healthcare situation of LC patients in Germany based on routine data from SHI funds, to develop an algorithm that sheds light on LC types (non-small cell / NSCLC vs. small cell / SCLC), and to gain new knowledge to improve needs-based care.

METHODS

Anonymized billing data of approximately four million people with SHI were analyzed regarding ICD-10 (German modification), documented medical interventions based on the outpatient SHI Uniform Assessment Standard Tariff (EBM) or the inpatient Operations and Procedure Code (OPS), and the dispensing of prescription drugs to outpatients (ATC classification). The study included patients who were members of 64 SHI funds between Jan-1st, 2015 and Dec-31st, 2016 and who received the initial diagnosis of LC in 2015 and 2016.

RESULTS

The analysis shows that neither the cancer type nor the cancer stage can be unambiguously described by the ICD-10 coding. Furthermore, an assignment based on the prescribed medication provides only limited information: many of the drugs are either approved for both LC types or are used off-label, making it difficult to assign them to a specific LC type. Overall, 25% of the LC patients were unambiguously identifiable as NSCLC vs SCLC based on the ICD-10 code, the drug therapy, and the billing data.

CONCLUSIONS

The current coding system appears to be of limited suitability for drawing conclusions about LC and therefore the SHI patient population. This makes it difficult to analyze the healthcare data with the aim of gathering new knowledge to improve needs-based care. The approach chosen for this study did not allow for development of a LC differentiation algorithm based on the available healthcare data. However, a better overview of patient specific needs could make it possible to modify the range of services provided by the SHI funds. From this perspective, it makes sense, in a first step, to refine the ICD-10 system to facilitate NSCLC vs. SCLC classification.

Real-world evidence to assess the effectiveness of platelet-rich plasma in the treatment of knee degenerative pathology: a prospective observational study

Objective:

The present work aims to analyse the effectiveness of platelet-rich plasma (PRP) in degenerative knee pathology based on real-world data and to evaluate possible factors influencing the response to treatment.

Methods:

In total, 531 cases were analysed collecting data on gender, age, body mass index, pathology location, severity, number of cycles and route of administration. Clinical outcome was evaluated at 6 and 15 months after treatment, using the Knee injury and Osteoarthritis Outcome Score (KOOS) and obtaining percentages of Minimal Clinically Important Improvement (MCII). Blood and PRP samples were randomly tested as a quality control measure to ensure the correct properties. Comparative statistical tests and multivariate regression were performed for the analysis of the variables.

Results:

The PRP applied had a platelet concentration factor of 1.67, with no leukocytes or erythrocytes. The percentage of patients with MCII at 6 and 15 months after PRP application was 59.32% and 70.62%, respectively. Patients with MCII were younger (p = 0.0246) and with lower body mass index (p = 0.0450). The treatment had a better response in mild/moderate cases than in severe cases (p = 0.0002). Intraosseous PRP application in severe cases improved the effect of intraarticular PRP (p = 0.0358). The application of a second cycle of PRP only improved the response in patients without MCII at 6 months (p = 0.0029), especially in mild/moderate cases (p = 0.0357).

Conclusion:

The applications of PRP in degenerative knee pathologies is an effective treatment, but this effectiveness nonetheless depends on several variables. Real-world data can complement that from clinical trials to provide valuable information.

Methodological Issues in Analyzing Real-World Longitudinal Occupational Health Data: A Useful Guide to Approaching the Topic

Ever greater technological advances and democratization of digital tools such as computers and smartphones offer researchers new possibilities to collect large amounts of health data in order to conduct clinical research. Such data, called real-world data, appears to be a perfect complement to traditional randomized clinical trials and has become more important in health decisions. Due to its longitudinal nature, real-world data is subject to specific and well-known methodological issues, namely issues with the analysis of cluster-correlated data, missing data and longitudinal data itself. These concepts have been widely discussed in the literature and many methods and solutions have been proposed to cope with these issues. As examples, mixed and trajectory models have been developed to explore longitudinal data sets, imputation methods can resolve missing data issues, and multilevel models facilitate the treatment of cluster-correlated data. Nevertheless, the analysis of real-world longitudinal occupational health data remains difficult, especially when the methodological challenges overlap. The purpose of this article is to present various solutions developed in the literature to deal with cluster-correlated data, missing data and longitudinal data, sometimes overlapped, in an occupational health context. The novelty and usefulness of our approach is supported by a step-by-step search strategy and an example from the Wittyfit database, which is an epidemiological database of occupational health data. Therefore, we hope that this article will facilitate the work of researchers in the field and improve the accuracy of future studies.

NeuroBlu, an electronic health record (EHR) trusted research environment (TRE) to support mental healthcare analytics with real-world data

PURPOSE

NeuroBlu is a real-world data (RWD) repository that contains deidentified electronic health record (EHR) data from US mental healthcare providers operating the MindLinc EHR system. NeuroBlu enables users to perform statistical analysis through a secure web-based interface. Structured data are available for sociodemographic characteristics, mental health service contacts, hospital admissions, International Classification of Diseases ICD-9/ICD-10 diagnosis, prescribed medications, family history of mental disorders, Clinical Global Impression-Severity and Improvement (CGI-S/CGI-I) and Global Assessment of Functioning (GAF). To further enhance the data set, natural language processing (NLP) tools have been applied to obtain mental state examination (MSE) and social/environmental data. This paper describes the development and implementation of NeuroBlu, the procedures to safeguard data integrity and security and how the data set supports the generation of real-world evidence (RWE) in mental health.

PARTICIPANTS

As of 31 July 2021, 562 940 individuals (48.9% men) were present in the data set with a mean age of 33.4 years (SD: 18.4 years). The most frequently recorded diagnoses were substance use disorders (1 52 790 patients), major depressive disorder (1 29 120 patients) and anxiety disorders (1 03 923 patients). The median duration of follow-up was 7 months (IQR: 1.3 to 24.4 months).

FINDINGS TO DATE

The data set has supported epidemiological studies demonstrating increased risk of psychiatric hospitalisation and reduced antidepressant treatment effectiveness among people with comorbid substance use disorders. It has also been used to develop data visualisation tools to support clinical decision-making, evaluate comparative effectiveness of medications, derive models to predict treatment response and develop NLP applications to obtain clinical information from unstructured EHR data.

FUTURE PLANS

The NeuroBlu data set will be further analysed to better understand factors related to poor clinical outcome, treatment responsiveness and the development of predictive analytic tools that may be incorporated into the source EHR system to support real-time clinical decision-making in the delivery of mental healthcare services.

Nationwide Real-Life Safety and Treatment Exposure Data on Durvalumab After Concurrent Chemoradiotherapy in Unresectable Stage III, Locally Advanced, Non-small Cell Lung Cancer: Analysis of Patients Enrolled in the French Early Access Program

PURPOSE

Consolidation immunotherapy with the PD-L1 inhibitor durvalumab following concurrent chemoradiotherapy (cCRT) has shown a significant survival improvement and is now a standard of care in patients with unresectable stage III or non-operable non-small cell lung cancer (NSCLC).

METHODS

In this early access program cohort, demographic, disease characteristics and safety data were collected for 576 patients from 188 centers, who received durvalumab 10 mg/kg intravenous infusion every 2 weeks, until disease progression or unacceptable toxicity or for a maximum of 12 months following cCRT. Durvalumab exposure data were available for 402 patients.

RESULTS

Overall, 576 patients were included, 72.9% were men, median age 64.0 years, 52.3% had a stage IIIB disease. PD-L1 status captured in 445 (77%) patients was positive (48.1%), negative (32.6%), unknown (19.3%). At the end of cCRT, adverse events (AEs) all grade ≤ 2, were reported in 22.7% of patients, mainly esophagitis (6.3%). The main reasons of discontinuation were completion of the planned 12 months of consolidation treatment (42.1% patients), disease progression (28.6%) and adverse events (19.5%). Treatment completion was similar in PDL-1 positive and PDL-1 negative patients groups. 20.7% patients had a SAE drug reaction and 17.7% stopped treatment mainly due to SAE. ADR rate and early treatment discontinuation were higher in patients > 70 years old. Death due to AEs occurred in 7 patients, 2 had interstitial lung disease.

CONCLUSION

Safety data with durvalumab consolidation after cCRT in a large cohort of patients with stage III NSCLC are reported in this real-life cohort. Consistent data were reported both in the PD-L1 positive and PD-L1 negative NSCLC patients in daily practice.

The future of research in hematology: Integration of conventional studies with real-world data and artificial intelligence

Most national health-care systems approve new drugs based on data of safety and efficacy from large randomized clinical trials (RCTs). Strict selection biases and study-entry criteria of subjects included in RCTs often do not reflect those of the population where a therapy is intended to be used. Compliance to treatment in RCTs also differs considerably from real world settings and the relatively small size of most RCTs make them unlikely to detect rare but important safety signals. These and other considerations may explain the gap between evidence generated in RCTs and translating conclusions to health-care policies in the real world. Real-world evidence (RWE) derived from real-world data (RWD) is receiving increasing attention from scientists, clinicians, and health-care policy decision-makers - especially when it is processed by artificial intelligence (AI). We describe the potential of using RWD and AI in Hematology to support research and health-care decisions.

Risk of arterial and venous thromboembolic events among patients with colorectal carcinoma: a real-world, population-based study

Objective: To assess real-world patterns of arterial and venous thromboembolism among patients with colorectal carcinoma. Methods: The Alberta provincial cancer registry and other provincial medical records were used to identify patients with colorectal cancer (2004-2018) with no preceding or succeeding cancer diagnosis. The incidence of both arterial and venous thromboembolism in this patient population as well as factors associated with these thromboembolic events were examined through logistic regression analysis. Results: A total of 17,296 patients were found eligible and were included into the current study. We observed that 1564 patients (9%) experienced a thromboembolic event and 15,732 patients (91%) did not. The following factors were associated with any thromboembolic event: male sex (odds ratio [OR]: 1.20; 95% CI: 1.08-1.34), higher comorbidity (OR: 1.36; 95% CI: 1.31-1.41), metastatic disease (OR for nonmetastatic vs metastatic disease: 0.53; 95% CI: 0.47-0.60), living within North zone (OR for Edmonton zone vs North zone: 0.70; 95% CI: 0.59-0.84), treatment with fluoropyrimidines (OR for no fluoropyrimidines vs fluoropyrimidines: 0.53; 95% CI: 0.47-0.60) and treatment with bevacizumab (OR: for no bevacizumab vs bevacizumab: 0.53; 95% CI: 0.47-0.60). Factors associated with venous thromboembolism include, younger age (continuous OR with increasing age: 0.99; 95% CI: 0.98-0.99), higher comorbidity (OR: 1.10; 95% CI: 1.04-1.17), metastatic disease (OR for nonmetastatic disease vs metastatic disease: 0.40; 95% CI: 0.35-0.47), North zone (OR for Edmonton zone vs North zone: 0.70; 95% CI: 0.56-0.86), treatment with fluoropyrimidines (OR for no fluoropyrimidines vs fluoropyrimidines: 0.45; 95% CI: 0.39-0.53) and treatment with bevacizumab (OR for no bevacizumab vs bevacizumab: 0.73; 95% CI: 0.58-0.93). Conclusion: Thromboembolic events are not uncommon among colorectal cancer patients, and the risk is increased with male sex, higher comorbidity, presence of metastatic disease, living within the North zone of the province (where there is limited access to tertiary care centers) and treatment with fluoropyrimidines or bevacizumab.

Evaluation of Three Feasibility Tools for Identifying Patient Data and Biospecimen Availability: Comparative Usability Study

BACKGROUND

To meet the growing importance of real-word data analysis, clinical data and biosamples must be timely made available. Feasibility platforms are often the first contact point for determining the availability of such data for specific research questions. Therefore, a user-friendly interface should be provided to enable access to this information easily. The German Medical Informatics Initiative also aims to establish such a platform for its infrastructure. Although some of these platforms are actively used, their tools still have limitations. Consequently, the Medical Informatics Initiative consortium MIRACUM (Medical Informatics in Research and Care in University Medicine) committed itself to analyzing the pros and cons of existing solutions and to designing an optimized graphical feasibility user interface.

OBJECTIVE

The aim of this study is to identify the system that is most user-friendly and thus forms the best basis for developing a harmonized tool. To achieve this goal, we carried out a comparative usability evaluation of existing tools used by researchers acting as end users.

METHODS

The evaluation included three preselected search tools and was conducted as a qualitative exploratory study with a randomized design over a period of 6 weeks. The tools in question were the MIRACUM i2b2 (Informatics for Integrating Biology and the Bedside) feasibility platform, OHDSI's (Observational Health Data Sciences and Informatics) ATLAS, and the Sample Locator of the German Biobank Alliance. The evaluation was conducted in the form of a web-based usability test (usability walkthrough combined with a web-based questionnaire) with participants aged between 26 and 63 years who work as medical doctors.

RESULTS

In total, 17 study participants evaluated the three tools. The overall evaluation of usability, which was based on the System Usability Scale, showed that the Sample Locator, with a mean System Usability Scale score of 77.03 (SD 20.62), was significantly superior to the other two tools (Wilcoxon test; Sample Locator vs i2b2: P=.047; Sample Locator vs ATLAS: P=.001). i2b2, with a score of 59.83 (SD 25.36), performed significantly better than ATLAS, which had a score of 27.81 (SD 21.79; Wilcoxon test; i2b2 vs ATLAS: P=.005). The analysis of the material generated by the usability walkthrough method confirmed these findings. ATLAS caused the most usability problems (n=66), followed by i2b2 (n=48) and the Sample Locator (n=22). Moreover, the Sample Locator achieved the highest ratings with respect to additional questions regarding satisfaction with the tools.

CONCLUSIONS

This study provides data to develop a suitable basis for the selection of a harmonized tool for feasibility studies via concrete evaluation and a comparison of the usability of three different types of query builders. The feedback obtained from the participants during the usability test made it possible to identify user problems and positive design aspects of the individual tools and compare them qualitatively.

Real-world big data demonstrates prevalence trends and developmental patterns of myopia in China: a retrospective, multicenter study

Background

Myopia is a complex disease caused by a combination of multiple pathogenic factors. Prevalence trends and developmental patterns of myopia exhibit substantial variability that cannot be clearly assessed using limited sample sizes. This study aims to determine the myopia prevalence over the past 60 years and trace the myopia development in a school-aged population using medical big data.

Methods

The refraction data from electronic medical records in eight hospitals in South China were collected from January 2005 to October 2018; including patients' year of birth, refraction status, and age at the exam. All optometry tests were performed in accordance with standard procedures by qualified senior optometrists. The cross-sectional datasets (individuals with a single examination) and longitudinal datasets (individuals with multiple examinations) were analyzed respectively. SAS statistical software was used to extract and statistically analyse all target data and to identify prevalence trends and developmental patterns related to myopia.

Results

In total, 1,112,054 cross-sectional individual refraction records and 774,645 longitudinal records of 273,006 individuals were collected. The myopia prevalence significantly increased among individuals who were born after the 1960s and showed a steep rise until reaching a peak of 80% at the 1980s. Regarding developmental patterns, the cross-sectional data demonstrated that the myopia prevalence increased dramatically from 23.13% to 82.83% aging from 5 to 11, and the prevalence stabilized at the age of 20. The longitudinal data confirmed the results that the age of myopic onset was 7.47±1.67 years, the age of myopia stabilized at 17.14±2.61 years, and the degree of myopia stabilized at -4.35±3.81 D.

Conclusions

The medical big data used in this study demonstrated prevalence trends of myopia over the past 60 years and revealed developmental patterns in the onset, progression and stability of myopia in China.

Improving Reporting of Clinical Studies Using the POSEIDON Criteria: POSORT Guidelines

The POSEIDON (Patient-Oriented Strategies Encompassing IndividualizeD Oocyte Number) criteria were developed to help clinicians identify and classify low-prognosis patients undergoing assisted reproductive technology (ART) and provide guidance for possible therapeutic strategies to overcome infertility. Since its introduction, the number of published studies using the POSEIDON criteria has increased steadily. However, a critical analysis of existing evidence indicates inconsistent and incomplete reporting of critical outcomes. Therefore, we developed guidelines to help researchers improve the quality of reporting in studies applying the POSEIDON criteria. We also discuss the advantages of using the POSEIDON criteria in ART clinical studies and elaborate on possible study designs and critical endpoints. Our ultimate goal is to advance the knowledge concerning the clinical use of the POSEIDON criteria to patients, clinicians, and the infertility community.

Real-world patient-reported outcomes of women receiving initial endocrine-based therapy for HR+/HER2- advanced breast cancer in five European countries

Background

Endocrine therapy (ET)-based regimens are the mainstay of treatment for patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2−) advanced breast cancer. With the introduction of new treatment classes, it is important to examine patient symptoms and health-related quality of life (HRQoL) at the start of this changing therapeutic landscape. This real-world study describes the patient-reported outcomes (PROs) of women with HR+/HER2− advanced breast cancer receiving ET-based regimens who were naïve to systemic treatment in the advanced setting across five European countries (EU5).

Methods

Data were collected between March and July 2017 from surveyed oncologists and their patients at a single time point using the multinational Adelphi Advanced Breast Cancer Disease Specific Programme™. Patients completed PRO questionnaires on HRQoL (EORTC QLQ-C30), pain severity and interference, and work and activity impairment. A multiple linear regression model explored factors associated with HRQoL.

Results

Across EU5, 226 physicians provided data on 781 women with HR+/HER2− advanced breast cancer taking their first ET-based regimen for advanced disease, of whom 252 provided PRO data. This subset had a mean age of 67.1 years, 94% were postmenopausal, 89% were diagnosed with advanced breast cancer at initial presentation, 79% had stage IV disease (66% of these patients had bone metastases and 38% had visceral metastases, including 18% with liver metastases) and 77% were on endocrine-only therapy as their initial treatment for advanced disease. The mean EORTC QLQ-C30 global health score (50.9) was worse than the reference value for patients with advanced breast cancer (60.2). Fatigue, pain, and insomnia were the most severe symptoms, and mean functioning scores were also worse than reference values. “Worst pain” and “pain interference” were moderate/severe for 42 and 80% of patients. Mean activity impairment was 44%, and greater activity impairment was associated with poorer HRQoL.

Conclusions

Despite receiving first-line ET-based regimens for advanced disease, these women had a poor HRQoL and high levels of symptoms, pain, pain interference and activity impairment. New treatments that maintain a stable disease state and reduce activity impairment may have a positive effect on the HRQoL of those living with advanced breast cancer.

How Important Is Randomization of Swallows During Kinematic Analyses of Swallow Function?

Purpose In dysphagia research involving kinematic analyses on individual swallow parameters, randomization is used to ensure judges are not influenced by judgments made for other parameters within the same swallow or by judgments made for other swallows from the same participant. Yet, the necessity of randomizing swallows to avoid bias during kinematic analyses is largely assumed and untested. This study investigated whether randomization of the order of swallows presented to judges impacts analyses of temporal kinematic events from videofluoroscopic swallow studies. Method One hundred twenty-seven swallows were analyzed from 18 healthy adults who underwent standardized videofluoroscopic swallow studies. Swallows were first analyzed by two trained raters sequentially, analyzing all kinematic events within each swallow, and then a second time in random order, measuring one kinematic event at a time. Intrarater reliability measurements were calculated between random and sequential swallow judgments for all kinematic events using intraclass correlation coefficient and percent exact agreement within a three-frame tolerance. Results Intraclass correlation coefficients (1.00) and percent exact agreement (89%) were excellent for all kinematic events between analyses methods, indicating there were no significant differences in measurements performed in random or sequential order. Conclusions This study provides preliminary evidence that randomization may be unnecessary during temporal swallow kinematic data analyses for research, which may lead to more efficient analyses and dissemination of findings, and alignment of findings with clinical interpretations. Replication of this design with swallows from people with dysphagia would strengthen the generalizability of the results.

The New FDA Real-World Evidence Program to Support Development of Drugs and Biologics

FDA has launched a Real World Evidence (RWE) Program for using real-world evidence (RWE) to help support new indications for already approved drugs or biologics and postapproval studies. The plan also includes stakeholder engagement efforts, demonstration projects, leadership activities, and development of guidance documents to assist developers interested in using real-world data (RWD) to develop RWE to support FDA regulatory decisions. This plan was mandated by the Cures Act passed in 2016. Over the 24-month period from passage of the law until FDA officially announced their program, FDA has gone to considerable efforts to educate the public about the benefits of RWE and encourage researchers to consider situations where RWE trials can generate useful information. Through a variety of stakeholder engagement projects, including publication of articles in medical journals, participation in public meetings, and development of initiatives, FDA has put more effort into preparing the medical community for its new emphasis on RWE than any other new policy that I can recall.

The Oncology Data Network (ODN): A Collaborative European Data-Sharing Platform to Inform Cancer Care

The rise of precision oncology has made clinical decision making more complex than ever before. The Oncology Data Network was established to enable the clinical community to efficiently access potentially practice‐changing insights from an extended network of cancer centers. This article describes the progress to date and calls for greater collaboration.

Trial designs using real-world data: The changing landscape of the regulatory approval process

Purpose

There is a need to develop hybrid trial methodology combining the best parts of traditional randomized controlled trials (RCTs) and observational study designs to produce real‐world evidence (RWE) that provides adequate scientific evidence for regulatory decision‐making.

Methods

This review explores how hybrid study designs that include features of RCTs and studies with real‐world data (RWD) can combine the advantages of both to generate RWE that is fit for regulatory purposes.

Results

Some hybrid designs include randomization and use pragmatic outcomes; other designs use single‐arm trial data supplemented with external comparators derived from RWD or leverage novel data collection approaches to capture long‐term outcomes in a real‐world setting. Some of these approaches have already been successfully used in regulatory decisions, raising the possibility that studies using RWD could increasingly be used to augment or replace traditional RCTs for the demonstration of drug effectiveness in certain contexts. These changes come against a background of long reliance on RCTs for regulatory decision‐making, which are labor‐intensive, costly, and produce data that can have limited applicability in real‐world clinical practice.

Conclusions

While RWE from observational studies is well accepted for satisfying postapproval safety monitoring requirements, it has not commonly been used to demonstrate drug effectiveness for regulatory purposes. However, this position is changing as regulatory opinions, guidance frameworks, and RWD methodologies are evolving, with growing recognition of the value of using RWE that is acceptable for regulatory decision‐making.

Use of targeted therapies for advanced renal cell carcinoma in the Veterans Health Administration

BACKGROUND

The objective of this study is to describe the use of targeted therapies for the treatment of advanced renal cell carcinoma (RCC) and overall survival (OS) among patients in clinical practice in the Veterans Health Administration (VHA).

METHODS

A retrospective cohort of 286 patients from 24 VHA Medical Centers diagnosed with advanced clear cell RCC between Fiscal Year (FY) 2010 and FY2014 was followed through September 30, 2016. Among patients who received targeted therapy, we described the medications taken, duration of therapy, and overall survival. We also assessed the effect of the first therapy received on overall survival using Cox Proportional Hazards models.

RESULTS

There were 66 patients who did not receive therapy for their advanced RCC. Of the 220 treated patients, the mean (sd) number of medications received was 1.9 (1.1). The medications most commonly used first were sunitinib (61.8%), pazopanib (17.3%), and temsirolimus (10.9%). The median duration of first-line therapy was 86 days (interquartile range [IQR] 42, 210). Median total duration of therapy was 159 days (IQR 58, 397). 62.3% of patients had ≥ 1 dose of therapy held or reduced, mainly due to an adverse drug event (ADE). Median survival from the start of treatment to death was 1.08 years (IQR 0.80, 1.31). Finally, receipt of temsirolimus vs sunitinib (HR 1.95 [95%CI 1.09,3.47]) as the first targeted therapy was independently associated with an increased hazard of death.

CONCLUSION

Our analysis of targeted therapies for advanced RCC in VHA suggests duration of treatment is shorter in a real-world setting than in clinical trials, and dose reductions and ADEs are more common.

Real-World Evidence Should Be Used in Regulatory Decisions About New Pharmaceutical and Medical Device Products for Diabetes

Randomized clinical trials (RCTs) are no longer the sole source of data to inform guidelines, regulatory, and policy decisions. Real-world data (RWD), collected from registries, electronic health records, insurance claims, pharmacy records, social media, and sensor outputs from devices form real-world evidence (RWE), which can supplement evidence from RCTs. Benefits of using RWE include less time and cost to produce meaningful data; the ability to capture additional information, including social determinants of health that can impact health outcomes; detection of uncommon adverse events; and the potential to apply machine learning and artificial intelligence to the delivery of health care. Overall, combining data from RCTs and RWE would allow regulators to make ongoing and more evidence-based decisions in approving and monitoring products for diabetes.

The quality of research with real-world evidence

Most of the medical practice has not been proven by controlled clinical trials, and there are no plans to conduct such trials in order to decrease clinician uncertainty. This happens partly due to the difficulty of making designs with scientific and ethical validity, the costs of this type of research and the time required to generate results, which can be several years. Clinical trials do not have the capability to generate information that allows to make decisions in some sectors of clinical care and public health, such as when an epidemic occurs. Therefore, medical science is based on observational studies, past practices and therapeutic tradition (1). Observation of clinical data that have defined a clinical behavior precedes the clinical trial. The knowledge about scurvy, the fact that this pathology is considered a nutritional deficiency and its treatment with citrus fruits, originated thanks to the collection of clinical data on sailors, soldiers and prisoners of the British Crown in the 18th and 19th centuries (2). This clinical information, which was collected uniformly and served to produce new knowledge, is what is now known as Real World Data (RWD). A modern definition of RWD would be one that talks about data obtained by any non-interventionist methodology that is collected prospectively and retrospectively from observations of routine clinical practice, and which comes from various sources including data from patients, doctors, hospitals, payers, social data, etc (3).

Precision oncology: lessons learned and challenges for the future

The decreasing cost of and increasing capacity of DNA sequencing has led to vastly increased opportunities for population-level genomic studies to discover novel genomic alterations associated with both Mendelian and complex phenotypes. To translate genomic findings clinically, a number of health care institutions have worked collaboratively or individually to initiate precision medicine programs. These precision medicine programs involve designing patient enrollment systems, tracking electronic health records, building biobank repositories, and returning results with actionable matched therapies. As cancer is a paradigm for genetic diseases and new therapies are increasingly tailored to attack genetic susceptibilities in tumors, these precision medicine programs are largely driven by the urgent need to perform genetic profiling on cancer patients in real time. Here, we review the current landscape of precision oncology and highlight challenges to be overcome and examples of benefits to patients. Furthermore, we make suggestions to optimize future precision oncology programs based upon the lessons learned from these "first generation" early adopters.

Exploration of Artificial Intelligence Use with ARIES in Multiple Myeloma Research

Background: Natural language processing (NLP) is a powerful tool supporting the generation of Real-World Evidence (RWE). There is no NLP system that enables the extensive querying of parameters specific to multiple myeloma (MM) out of unstructured medical reports. We therefore created a MM-specific ontology to accelerate the information extraction (IE) out of unstructured text. Methods: Our MM ontology consists of extensive MM-specific and hierarchically structured attributes and values. We implemented “A Rule-based Information Extraction System” (ARIES) that uses this ontology. We evaluated ARIES on 200 randomly selected medical reports of patients diagnosed with MM. Results: Our system achieved a high F1-Score of 0.92 on the evaluation dataset with a precision of 0.87 and recall of 0.98. Conclusions: Our rule-based IE system enables the comprehensive querying of medical reports. The IE accelerates the extraction of data and enables clinicians to faster generate RWE on hematological issues. RWE helps clinicians to make decisions in an evidence-based manner. Our tool easily accelerates the integration of research evidence into everyday clinical practice.

Lower-dose prescriptions in the post-marketing situation and the influencing factors thereon

The dosage of pharmaceuticals is determined through the process of clinical development and approval review based on clinical trial results; however, the information obtained from clinical trials before approval is limited. Some pharmaceutical products are used at doses lower than those approved for post-marketing use. The aim of this study was to reveal the actual state of lower-dose prescriptions for post-marketing clinical use of pharmaceuticals. We investigated the factors related to the deviation based on therapeutic area, detailed statement of the approved dosage, clinical data package, and post-marketing requirement. Among the new molecular entities approved in Japan between January 2005 and December 2014, we identified products that are orally administered and have the same daily dose for different indications, if any. For these products, we collected information on the actual daily dose from the medical information databases of Medical Data Vision Co., LTD. and JammNet Co., LTD. Products whose dose was lower than the approved dose (maintenance dose excluding the initial dose) in ≥ 30% prescriptions in 2015 were defined here as “lower-dose prescription drugs.” We identified 27 lower-dose prescription drugs out of 113 products investigated. The results of the multivariate analysis revealed that factors related to the Anatomical Therapeutic Chemical classification and the detailed statement of the approved dosage significantly influenced the occurrence of lower-dose prescription, whereas the factors related to clinical data package and post-marketing requirements did not. These results suggest the limitation in determining an optimal dosage for the actual clinical use of a drug based on the information obtained from clinical trials conducted before approval, emphasizing the importance of reexamining the optimal dosage that is applicable to a greater number of patients after marketing, if necessary. We believe that the utilization of real-world data could be of help in this regard.

I-O Optimise: a novel multinational real-world research platform in thoracic malignancies

Aim: To describe I-O Optimise, a multinational program providing real-world insights into lung cancer management. Materials & methods: Real-world data source selection for I-O Optimise followed a structured approach focused on population coverage, key variable capture, continuous/consistent data availability, record duration and data latency, and database expertise. Results: As of 31 October 2018, seven real-world data sources were included in I-O Optimise, providing data on characteristics, treatment patterns and clinical outcomes from more than 45,000 patients/year with non-small-cell lung cancer, small-cell lung cancer and mesothelioma across Denmark, Norway, Portugal, Spain, Sweden and the UK. Conclusion: The ongoing I-O Optimise initiative has the potential to provide a broad, robust and dynamic research platform to continually address numerous research objectives in the lung cancer arena.