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777 results for “older patient”
GERDAT011 Literature search for publication - Geriatric assessment in the management of older patients with cancer – a systematic review (update).xlsx
<p>Search data belonging to the publication Geriatric assessment in the management of older patients with cancer – a systematic review (update)</p>
GERDAT010 Dataset for literature search linked to publication "Information needs of older patients newly diagnosed with cancer"
<p>Dataset of the literature search belonging to the publication "Information needs of older patients newly diagnosed with cancer"</p>
Patient and GP experiences of implementing a medication review intervention in older people with multimorbidity: process evaluation of the SPPiRE trial
<p>Abstract</p> <p><strong>Background: </strong>The SPPiRE cluster randomised controlled trial (RCT) found that a GP delivered medication review that incorporated screening potentially inappropriate prescriptions (PIP), a brown bag review and a patient priority assessment, resulted in a significant but small reduction in the number of medicines and no significant reduction in PIP.</p> <p><strong>Objective: </strong>To explore the experiences of GPs and patients engaged in the SPPiRE intervention and the potential for system wide implementation.</p> <p><strong>Design: </strong>Mixed methods process evaluation; quantitative data was collected from the SPPiRE intervention website and qualitative data via semi-structured interviews.</p> <p><strong>Setting and participants:</strong> 51 general practices throughout Ireland, and 404 participants with multimorbidity aged ≥65 years, prescribed ≥15 medicines participated in the RCT. Qualitative data was collected with purposive samples of intervention GPs (18/26) and patients (27/208). </p> <p><strong>Methods: </strong>Quantitative data was analysed descriptively, qualitative data thematically and both were integrated using a triangulation protocol.</p> <p><strong>Results: </strong>The analysis generated three themes, intervention implementation, mechanisms of action, and both were underpinned by the theme of context. One fifth of patients had no review, primarily due to insufficient GP time. The brown bag review component resulted in the most deprescription of medications. GPs felt it easier to change medicines if the patient was well known to them, and patients were generally receptive to change. GPs identified lack of integration into practice software systems and resources as barriers to future implementation.</p> <p><strong>Conclusion: </strong>Consideration of implementation of successful interventions is key to informing policy and integration into clinical practice. GPs and patients viewed the intervention positively, but implementation will depend on resourcing and integration into practice software systems.</p> <p>Trial registration number: <a href="https://doi.org/10.1186/ISRCTN12752680">ISRCTN12752680</a></p>
Data set - What Defines Quality of Life for Older Patients Diagnosed with Cancer? A Qualitative Study
<p><strong>Data set from- What Defines Quality of Life for Older Patients Diagnosed with Cancer? A Qualitative Study</strong></p> <p><strong>Abstract of the study: </strong>The treatment of cancer can have a significant impact on quality of life in older patients and this needs to be taken into account in decision making. However, quality of life can consist of many different components with varying importance between individuals. We set out to assess how older patients with cancer define quality of life and the components that are most significant to them. This was a single-centre, qualitative interview study. Patients aged 70 years or older with cancer were asked to answer open-ended questions: What makes life worthwhile? What does quality of life mean to you? What could affect your quality of life? Subsequently, they were asked to choose the five most important determinants of quality of life from a predefined list: cognition, contact with family or with community, independence, staying in your own home, helping others, having enough energy, emotional well-being, life satisfaction, religion and leisure activities. Afterwards, answers to the open-ended questions were independently categorized by two authors. The proportion of patients mentioning each category in the open-ended questions were compared to the predefined questions. Overall, 63 patients (median age 76 years) were included. When asked, “What makes life worthwhile?”, patients identified social functioning (86%) most frequently. Moreover, to define quality of life, patients most frequently mentioned categories in the domains of physical functioning (70%) and physical health (48%). Maintaining cognition was mentioned in 17% of the open-ended questions and it was the most commonly chosen option from the list of determinants (72% of respondents). In conclusion, physical functioning, social functioning, physical health and cognition are important components in quality of life. When discussing treatment options, the impact of treatment on these aspects should be taken into consideration.</p> <p><strong>Reference of research paper: </strong>Seghers PAL, Kregting JA, van Huis-Tanja LH, Soubeyran P, O'Hanlon S, Rostoft S, Hamaker ME, Portielje JEA. What Defines Quality of Life for Older Patients Diagnosed with Cancer? A Qualitative Study. <em>Cancers</em>. 2022; 14(5):1123. https://doi.org/10.3390/cancers14051123</p> <p><strong>Content of the data set: </strong>The first Tab describes what questions were asked, the second tab shows all individual anonymised answers to the open questions, the fourth shows the definitions that were used to classify all answers. Q1-Q4 show how the answers were categorised. </p>
Patient Priority Care for Older Adults With Multiple Chronic Conditions
ClinicalTrials.gov study NCT04510948. IPD Sharing: YES. Countries: 1. Publications: 13.
Study protocol and data dictionary: Effectiveness of a GP delivered medication review in reducing polypharmacy and potentially inappropriate prescribing in older patients with multimorbidity in Irish primary care: a cluster randomised controlled trial (SPPiRE study)
<p><strong>Methods</strong></p> <p><strong>Study design and participants</strong></p> <p>The methods for the SPPiRE cluster RCT have been described in the trial protocol (21). This study is reported in line with the CONSORT 2010 cluster RCT checklist (22), see Appendix 1, and was approved by the Irish College of General Practitioners Research Ethics Committee. In brief, SPPiRE was a pragmatic two arm cluster RCT, with the intervention delivered to GP clusters and analysis of outcomes at the patient level. Information about the trial was publicised through a variety of GP research, teaching and training networks throughout Ireland. Eligible practices expressing an interest were formally invited. Practices were eligible to participate if they had at least 300 registered patients aged ≥65 years (based on the need to identify a sufficient number of eligible participants) and used either of the two Irish GP practice management systems (PMS) with over 80% national cover; this enabled use of a SPPiRE patient finder tool which was developed and embedded into these systems. Practices were excluded if they were currently involved in a medication management or prescribing trial or if they were unable to recruit at least five participants.</p> <p>Eligible patients were aged ≥65 years and prescribed ≥15 repeat medicines. A repeat medicine was defined as any unique item with a World Health Organisation Anatomical Therapeutic Chemical code on the patient’s current repeat prescription. Patients were excluded if they had been recruited into a practice that was unable to recruit at least four other participants, they were judged by their GP as unable to give informed consent or they were unable to attend the practice for a face to face medication review, (e.g. nursing home residents and house bound patients). Recruited GPs ran the SPPiRE patient finder tool and screened the generated list to ensure only eligible patients were invited. Practices who identified more than 40 eligible patients were supported in selecting a random sample of 30 patients to invite. All recruited practices and patients gave fully informed consent and baseline data was collected prior to practice allocation, to reduce the likelihood of selection bias.</p> <p><strong>Randomisation and masking</strong></p> <p>Recruited practices were allocated to intervention or control groups by minimisation using Minimpy software (23) by the trial statistician (FB) who had no knowledge of participating practices. Minimisation variables included practice size (number of GP sessions per week, 0-14, 14-28 and 28 or more) and location (urban, rural or mixed). Considering the nature of the intervention, it was not possible to blind GPs or patients to the intervention, however to reduce the risk of detection bias the two primary outcome measures; the number of repeat medicines and whether a PIP was present were assessed by an independent blinded pharmacist (MF).</p> <p><strong>Procedures</strong></p> <p>Intervention GPs received unique login details to the SPPiRE website where they had access to five training videos and a template for performing the SPPiRE medication review. The training videos provided background information on multimorbidity and polypharmacy, PIP, eliciting patient treatment priorities and conducting a brown bag medication review. GPs were instructed to book a double appointment and to ask their patients to bring all their medicines in to the medication review visit with them. The SPPiRE medication review process had two main components; gather and record information and then to discuss and agree changes with their patient based on the recorded information, with a focus on deprescribing medicines that were potentially inappropriate, figure 1. The website provided suggested treatment alternatives for identified PIP but all treatment decisions were ultimately at the discretion of the individual GP, based on their clinical judgement and their patients’ individual priorities.</p> <p>Control GPs delivered usual care during the six to twelve month study period. At the time of intervention delivery there was no structured chronic disease management programme in Irish primary care and many patients with multimorbidity attended multiple hospital specialists. In Ireland, the majority of people aged ≥70 years of age have access to free GP visits and medicines with some prescription charge co-payments. In the 65 – 69 year old age category a lower proportion have access to both free GP visits and prescription medicines. Access to specialists and diagnostics in secondary care is free for the entire population.</p> <p><strong>Outcomes</strong></p> <p>The two primary outcomes were the number of repeat medicines and the proportion of patients with any PIP, from a list of 34 pre-specified indicators (see Appendix 2). A series of secondary prescribing related outcome measure were pre-specified to allow a more in depth analysis of the effect of the intervention on prescribing. These were:</p> <ul> <li>The number of medicines stopped and started</li> <li>The proportion of patients with a reduction in significant polypharmacy (defined as ≥15 repeat medicines)</li> <li>The number of PIP</li> <li>The proportion of patients with a high risk PIP (see Appendix 2)</li> <li>The proportion of patients with any reduction in PIP</li> </ul> <p>Secondary patient reported outcomes measures were included to capture the effectiveness of the intervention from the patients’ perspective. These were:</p> <ul> <li>Health related Quality of life (EQ5D-5L)(24)</li> <li>Revised Patients' attitudes towards deprescribing (rPATD) (25)</li> <li>Multimorbidity Treatment Burden Questionnaire (MTBQ) (26)</li> </ul> <p>Health care utilisation data was collected to assess the effect of the intervention on health care usage and for the trial’s economic evaluation.</p> <p>Outcomes were collected at baseline and at six months after intervention delivery. Patient reported measures were collected by postal questionnaires. Data for all other measures including prescribed medicines, medical and investigations history and healthcare utilisation were collected by participating GPs and submitted to the study manager (CMC). This was a deviation from the original protocol, which indicated this data would be collected by the research team. This deviation related to changes in data protection and national health research regulations during the study period, which precluded research team access to the patients’ full clinical record.</p> <p><strong>Adverse events</strong></p> <p>Information on adverse events such as mortality, ED presentations and hospital admissions was collected at follow up. Given the deprescribing approach of the intervention a safety protocol for identifying and reporting any suspected adverse drug withdrawal events (ADWEs) was developed. An ADWE is defined as either recurrence of the condition for which the drug was prescribed (e.g. recurrence of angina after stopping a beta blocker) or a physiologic reaction to drug withdrawal (e.g. SSRI withdrawal syndrome) (27, 28). Although discontinuing medicines in older people has been demonstrated to be safe (29), given the paramount importance of the principle of “do no harm” in research ethics a vigorous and detailed method was established to ensure that any potential ADWEs precipitated by deprescribing in a SPPiRE medication review were captured. Intervention GPs were asked to report any possible ADWE following the SPPiRE medication review. The Naranjo ADR probability scale (30) has been adapted in other studies to assess the likelihood a reaction is related to drug withdrawal (27, 28). This tool was further adapted for SPPiRE and used to make an assessment on the causality of the ADWE. To ensure the patient perspective was included, self-reported possible ADWEs were also collected from patient follow up questionnaires. </p> <p> </p> <p><strong>Sample size</strong></p> <p>As outlined in the trial protocol (21), the study was designed with 90% power to detect a 20% reduction in the proportion with PIP and a mean difference of one medicine between intervention and control groups (based on a mean of 17.4 medicines SD (2.6)) and the sample size inflated to incorporate the effects of clustering (using an ICC of 0.025). The sample size was recalculated when it became apparent during early recruitment that it would not be possible to recruit clusters with an average of 15 participants, as was initially planned in the protocol. An average cluster size of eight was anticipated which inflated the original sample size from 30 practices (450 patients) to 50 practices (400 patients).</p> <p><strong>Statistical analysis</strong></p> <p>Descriptive statistics were used to describe baseline characteristics of recruited practices and participants. All analyses were conducted under the intention-to-treat principle and those lost to follow up had their baseline data carried forward. The primary analysis was carried out using multi-level modelling. The first primary outcome measure, number of repeat medications, was assessed using mixed effects Poisson regression with the individual as the unit of analysis and the practice included as the random effect to control for the effects of clustering and results presented using incidence rate ratios (IRR) and 95% confidence intervals (CI). The baseline number of medicines, GP size (number of GP sessions per week) and GP location (urban/rural) were included in the analysis as fixed effects. The second outcome measure, proportion of patients with a PIP, was analysed in a similar manner using mixed effects logistic regression, including PIP at baseline, GP size and location, and results presented using odd ratios (OR) and 95% CIs. A number of pre-specified sensitivity analyses were conducted; complete case analysis, per protocol analysis and including “presence of a repeat prescribing policy” as a covariate. All secondary outcomes were analysed in a similar manner to the primary outcomes, using appropriate mixed effects regression methods (i.e. linear, logistic, Poisson).</p> <p> </p> <p>Note: Version 3 (published 28 April 2025) updates Version 2 by removing Participant GP1P4 following consent withdrawal. This version should be used for all future analyses.</p> <p> </p>
Prescribing trends in older patients with multimorbidity and significant polypharmacy recruited to the SPPiRE trial
<p><strong>Aims</strong></p> <p>Medication count and appropriateness are often used as outcome measures to evaluate the effectiveness of deprescribing interventions. The aim of this study was to evaluate changes in prescribing, potentially inappropriate prescriptions (PIP) and use of low value medicines during the SPPiRE trial.</p> <p><strong>Methods</strong></p> <p>We retrospectively analysed trial prescription data from 51 general practices with 404 participants aged ≥65 years and prescribed ≥15 repeat medicines. A dataset was created with 7,051 ATC coded medicines at baseline. Outcomes were the most commonly prescribed and potentially inappropriately prescribed drug groups, the most frequently stopped or started drug groups and the number of changes per person between baseline and follow-up.</p> <p><strong>Results </strong></p> <p>There were 7,051 medicines prescribed to 404 participants at baseline. The most commonly prescribed drug group were proton pump inhibitors (82% participants) and statins (77%). There was a median of 17 medicines (IQR 15-19) at baseline and 16 (IQR 14-19) at follow-up. PIP represented 17.1% of prescriptions at baseline and 15.7% (n=6,777) at follow-up. There were reductions in the prescription of most drug groups with the largest reduction in antiplatelet prescriptions. Considering medication discontinuations, initiations and switches, there was a median of five medication changes per person (range 0-30, IQR 3-9) by follow-up. There were 95 low value prescriptions at baseline reducing to 78 at follow-up.</p> <p><strong>Conclusions</strong></p> <p>The number of medication changes per person was not reflected by summarising medication count at two time points, highlighting the need for repeated measurements of prescribing outcomes especially for populations with high degrees of polypharmacy.</p>
Raw Data for the article: Mortality after transjugular intrahepatic portosystemic shunt in older adult patients with cirrhosis: A validated prediction model
<p><strong>Background and aims: </strong>Implantation of a transjugular intrahepatic portosystemic shunt (TIPS) improves survival in patients with cirrhosis with refractory ascites and portal hypertensive bleeding. However, the indication for TIPS in older adult patients (greater than or equal to 70 years) is debated, and a specific prediction model developed in this particular setting is lacking. The aim of this study was to develop and validate a multivariable model for an accurate prediction of mortality in older adults.</p> <p><strong>Approach and results: </strong>We prospectively enrolled 411 consecutive patients observed at four referral centers with de novo TIPS implantation for refractory ascites or secondary prophylaxis of variceal bleeding (derivation cohort) and an external cohort of 415 patients with similar indications for TIPS (validation cohort). Older adult patients in the two cohorts were 99 and 76, respectively. A cause-specific Cox competing risks model was used to predict liver-related mortality, with orthotopic liver transplant and death for extrahepatic causes as competing events. Age, alcoholic etiology, creatinine levels, and international normalized ratio in the overall cohort, and creatinine and sodium levels in older adults were independent risk factors for liver-related death by multivariable analysis.</p> <p><strong>Conclusions: </strong>After TIPS implantation, mortality is increased by aging, but TIPS placement should not be precluded in patients older than 70 years. In older adults, creatinine and sodium levels are useful predictors for decision making. Further efforts to update the prediction model with larger sample size are warranted.</p>
GERDAT021-Dataset for "Development and testing of the Outcome Prioritization Tool adjusted to older patients with cancer: A pilot study"
<p>This dataset shows the data underlying the publication "Development and testing of the Outcome Prioritization Tool adjusted to older patients with cancer: A pilot study published in JGO on 21 July 2023, which can be found at <a href="https://doi.org/10.1016/j.jgo.2023.101590">10.1016/j.jgo.2023.101590</a>."</p>
Bortezomib, Daunorubicin, and Cytarabine in Treating Older Patients With Previously Untreated Acute Myeloid Leukemia
ClinicalTrials.gov study NCT00742625. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Efficacy/Safety of CPI-613 in Combination With HD Cyt. and Mito. vs HD Cyt. and Mito. in Older Patients With R/R AML
ClinicalTrials.gov study NCT03504410. IPD Sharing: NO. Countries: 9. Publications: 1.
A Randomized Controlled Trial to Deprescribe for Older Patients With Polypharmacy
ClinicalTrials.gov study NCT02979353. IPD Sharing: YES. Countries: 1. Publications: 5.
Assessing Patient-reported & Patient-related Outcomes in Randomized Cancer Trials for Older Adults
ClinicalTrials.gov study NCT03676218. IPD Sharing: NO. Countries: 1. Publications: 1.
Decitabine and Midostaurin in Treating Older Patients With Newly Diagnosed Acute Myeloid Leukemia
ClinicalTrials.gov study NCT01846624. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Patient-Centered Communication Tool (UR-GOAL) Versus Usual Care for Older Patients With Acute Myeloid Leukemia, Their Caregivers, and Their Oncologists
ClinicalTrials.gov study NCT05335369. IPD Sharing: YES. Countries: 1. Publications: 3.
Screening for Ovarian Cancer in Older Patients (PLCO Screening Trial)
ClinicalTrials.gov study NCT01696994. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Decitabine With or Without Bortezomib in Treating Older Patients With Acute Myeloid Leukemia
ClinicalTrials.gov study NCT01420926. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Phase II Study of Decitabine and Cytarabine for Older Patients With Newly Diagnosed Acute Myeloid Leukemia (AML)
ClinicalTrials.gov study NCT01829503. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Efficacy and Safety of Lixisenatide Versus Placebo on Top of Basal Insulin and/or Oral Antidiabetic Treatment in Older Type 2 Diabetic Patients
ClinicalTrials.gov study NCT01798706. IPD Sharing: Not stated. Countries: 13. Publications: 2.
Combination Chemo, Rituximab, and Bevacizumab in Older Patients With Stage II-IV Diffuse Large B-Cell Lymphoma
ClinicalTrials.gov study NCT00121199. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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