Treatment Options in Oncology

2018 ◽  
pp. 1-10 ◽  
Author(s):  
Cédric M. Panje ◽  
Markus Glatzer ◽  
Charlotta Sirén ◽  
Ludwig Plasswilm ◽  
Paul M. Putora
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Medical Condition ◽  
Treatment Options ◽  
Treatment Strategies ◽  
Clinical Decision ◽  
Vital Role ◽  
Patient Specific ◽  
Treatment Preferences ◽  
Multiple Treatment

Multiple treatment strategies exist for many oncologic problems. In this review, we provide a summary of various reasons for the existence of multiple treatment options in oncology, including factors that concern the treating physician (eg, treatment preferences), environmental factors (eg, financial, regulatory, and scientific aspects), and individual patient-specific factors (eg, medical condition, preferences). We demonstrate the vital role of available treatment options and their origins for clinical decision making and patient communication. These aspects are particularly helpful in the process of shared decision making, which is increasingly favored in situations where there are multiple medically reasonable options.

Abstract P214: Patient and Physician Factors Influence Decision-Making in Hypercholesterolemia

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Michel Krempf ◽  
Ross J Simpson ◽  
Dena R Ramey ◽  
Philippe Brudi ◽  
Hilde Giezek ◽  
...  
Keyword(s):  
Decision Making ◽  
Goal Attainment ◽  
Clinical Decision Making ◽  
Treatment Strategies ◽  
Treatment Decision ◽  
Clinical Decision ◽  
Treatment Recommendations ◽  
Treatment Choice ◽  
Treatment Recommendation ◽  
Double Blind

Objectives: Little is known about how patient factors influence physicians’ treatment decision-making in hypercholesterolemia. We surveyed physicians’ treatment recommendations in high-risk patients with LDL-C not controlled on statin monotherapy. Methods: Physicians completed a questionnaire pre-randomization for each patient in a double-blind trial (NCT01154036) assessing LDL-C goal attainment rates with different treatment strategies. Patients had LDL-C ≥100 mg/dL after 5 weeks’ atorvastatin 10 mg/day and before randomization. Physicians were asked about treatment recommendations for three scenarios: (1) LDL-C near goal (100-105 mg/dL), (2) LDL-C far from goal (120 mg/dL), then (3) known baseline LDL-C of enrolled patients on atorvastatin 10 mg/day. Factors considered in their choice were specified. Physicians had been informed of projected LDL-C reductions for each treatment strategy in the trial. Regression analysis identified prognostic factors associated with each scenario, and projected LDL-C values for physicians’ treatment choices were compared to actual LDL-C values achieved in the trial. Results: Physicians at 296 sites completed questionnaires for 1535 patients. The most common treatment strategies for all three scenarios were: 1) not to change therapy, 2) double atorvastatin dose, 3) add ezetimibe, 4) double atorvastatin dose and add ezetimibe. Doubling atorvastatin dose was the most common treatment recommendation in all scenarios (43-52% of patients). ‘No change in therapy’ was recommended in 6.5% of patients when LDL-C was assumed far from goal. Treatment recommendations were more aggressive if actual LDL-C was known or considered far from goal. When compared with the ‘no change in therapy’ recommendation, CV risk factors and desire to achieve a more aggressive LDL-C goal were generally considered in decision-making for each treatment choice, regardless of LDL-C scenario. Patients randomized to a more aggressive regimen than recommended by physicians had larger reductions in LDL-C: the actual reduction in LDL-C in patients randomized to ‘add ezetimibe’ was -20.8% versus a projected reduction of -10.0% when physicians recommended ‘doubling atorvastatin dose’. Conclusions: This study provides insight into physicians’ perspectives on clinical management of hypercholesterolemia and highlights a gap in knowledge translation from guidelines to clinical practice. Targeting lower LDL-C and CV risk were key drivers in clinical decision-making but, generally, physicians were more conservative in their treatment choice than guidelines recommend, which may result in poorer LDL-C reduction. When compared with actual outcomes, projected LDL-C control was better if physicians used more comprehensive strategies rather than simply doubling the statin dose.

Contemporary Heart Failure Treatment Based on Improved Knowledge and Personalized Care of Comorbidities

2019 ◽  
pp. 1565-1579
Author(s):  
Kostas Giokas ◽  
Charalampos Tsirmpas ◽  
Athanasios Anastasiou ◽  
Dimitra Iliopoulou ◽  
Vassilia Costarides ◽  
...  
Keyword(s):  
Heart Failure ◽  
Decision Making ◽  
Chronic Diseases ◽  
Clinical Decision Making ◽  
Medical Condition ◽  
Collective Intelligence ◽  
Clinical Decision ◽  
Mortality And Morbidity ◽  
Personalized Care ◽  
Care Approach

Chronic diseases are the leading cause of mortality and morbidity. A significant contribution to the burden of chronic diseases is the concurrence of co-morbidities. Heart failure (HF) is a complex, chronic medical condition frequently associated with co-morbidities. The current care approach for HF patients with co-morbidities is neither capable to deliver personalised care nor to halt the on-going increase of its socio-economic burden. Our approach aims to improve the complete care process for HF patients and related co-morbidities to improve outcome and quality of life. This will be achieved by the proposed standardised yet personalised patient-oriented ICT system that supports evidence-based clinical decision making as well as interaction and communication between all stakeholders with focus on the patients and their relatives to improve self-management. We propose that such a system should be build upon a novel European-wide data standard for clinical input and outcome and that it should facilitate decision making and outcome tracking by new collective intelligence algorithms.

scholarly journals Quantifying the Impact of Patient-Specific Factors and Disease Severity on Clinical Decision Making in Cuff Tear Arthropathy: A Case-Based Survey

2019 ◽  
Vol 15 (3) ◽  
pp. 276-285
Author(s):  
Adam P. Schumaier ◽  
Yehia H. Bedeir ◽  
Joshua S. Dines ◽  
Keith Kenter ◽  
Lawrence V. Gulotta ◽  
...  
Keyword(s):  
Decision Making ◽  
Disease Severity ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Patient Specific ◽  
Cuff Tear Arthropathy ◽  
Cuff Tear ◽  
Specific Factors ◽  
The Impact ◽  
Case Based

The ‘Number Needed to Treat’ and the ‘Adjusted NNT’ in Health Care Decision-Making

1998 ◽  
Vol 3 (1) ◽  
pp. 44-49 ◽  
Author(s):  
Jack Dowie
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Evidence Based Medicine ◽  
Clinical Decision Making ◽  
Treatment Options ◽  
Clinical Decision ◽  
Population Based ◽  
Number Needed To Treat ◽  
Evidence Based ◽  
Based Medicine

Within ‘evidence-based medicine and health care’ the ‘number needed to treat’ (NNT) has been promoted as the most clinically useful measure of the effectiveness of interventions as established by research. Is the NNT, in either its simple or adjusted form, ‘easily understood’, ‘intuitively meaningful’, ‘clinically useful’ and likely to bring about the substantial improvements in patient care and public health envisaged by those who recommend its use? The key evidence against the NNT is the consistent format effect revealed in studies that present respondents with mathematically-equivalent statements regarding trial results. Problems of understanding aside, trying to overcome the limitations of the simple (major adverse event) NNT by adding an equivalent measure for harm (‘number needed to harm’ NNH) means the NNT loses its key claim to be a single yardstick. Integration of the NNT and NNH, and attempts to take into account the wider consequences of treatment options, can be attempted by either a ‘clinical judgement’ or an analytical route. The former means abandoning the explicit and rigorous transparency urged in evidence-based medicine. The attempt to produce an ‘adjusted’ NNT by an analytical approach has succeeded, but the procedure involves carrying out a prior decision analysis. The calculation of an adjusted NNT from that analysis is a redundant extra step, the only action necessary being comparison of the results for each option and determination of the optimal one. The adjusted NNT has no role in clinical decision-making, defined as requiring patient utilities, because the latter are measurable only on an interval scale and cannot be transformed into a ratio measure (which the adjusted NNT is implied to be). In any case, the NNT always represents the intrusion of population-based reasoning into clinical decision-making.

Clinical Decision Making on Extensive Molar Restorations

2014 ◽  
Vol 39 (6) ◽  
pp. E231-E240 ◽  
Author(s):  
T Laegreid ◽  
NR Gjerdet ◽  
A Johansson ◽  
A-K Johansson
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Dietary Habits ◽  
Influencing Factor ◽  
Treatment Options ◽  
Clinical Decision ◽  
Background Information ◽  
Molar Teeth ◽  
Logistic Regressions ◽  
Indirect Technique

SUMMARY Extensive loss of posterior tooth substance, which traditionally was restored with amalgam or indirect restorations, is more commonly being restored with resin-based composite restorations. Using a questionnaire, we aimed to survey dentists' clinical decision making when restoring extensive defects in posterior molar teeth. The questionnaire, which included questions on background information from the dentists, clinical cases with treatment options, and general questions about restoring extensive posterior defects, was sent to 476 dentists. The response rate was 59%. Multiple logistic regressions were used to investigate the different associations. Most of the respondents preferred a direct composite restoration when one cusp was missing, while indirect restorations were most preferred when replacing three or four cusps. Younger dentists and dentists working in the private sector had a greater tendency to choose an indirect technique compared with older colleagues. Generally, the most important influencing factor in clinical decision making was the amount of remaining tooth substance. Factors that appeared to be less important were dental advertisements, use of fluoride, and dietary habits. Female dentists perceived factors such as oral hygiene, patient requests, and economy to be more important than did their male colleagues.

Exploring patient satisfaction of a joint-consultation clinic for trigeminal neuralgia: Enabling improved decision-making

2021 ◽  
pp. 204946372110458
Author(s):  
Jolyon Poole ◽  
Valeria Mercadante ◽  
Sanjeet Singhota ◽  
Karim Nizam ◽  
Joanna M Zakrzewska
Keyword(s):  
Decision Making ◽  
Trigeminal Neuralgia ◽  
Clinical Decision Making ◽  
Response Rate ◽  
Treatment Options ◽  
Rare Condition ◽  
Clinical Decision ◽  
Consultation Clinic ◽  
Level Of Satisfaction ◽  
Paper Survey

Background Trigeminal neuralgia (TN) is a relatively rare condition which has a profound impact not only on the patient but also on those around them. There is no cure for TN, and the management of the condition is complex. The most effective forms of treatment are either through medication, neurosurgery, or combination of the two. Each option has risks and implications for the patient. As with all clinical decisions, it is important for patients to understand and be fully informed of the treatments available to them. A London UK unit adopted a joint-consultation clinic approach where the patient meets with both physician and neurosurgeon at the same time to discuss treatment options. The purpose of this evaluation is to understand patients’ level of satisfaction with the joint-consultation clinic and evaluate utilisation of a clinical decision-making tool. Method Patients who had attended the joint-consultation clinic over a period of 12 months were invited to participate in a telephone or paper survey (N = 55). Responses were analysed using descriptive statistics and thematic analysis. Results Forty-one patients (77% response rate) participated in the survey, and the results were overwhelmingly positive for the joint-consultation clinic regarding satisfaction. The benefits were broad ranging including increased understanding, collaboration and confidence in decision-making. Conclusions A joint-consultation clinic comprising a neurosurgeon and a physician for the treatment of TN is valued by patients who become better informed and able to make decisions about their care. Positive application of clinical decision-making aids in this situation offers potential across specialities.

A 52-Year-Old Man With Progressive Weakness and Incontinence

2021 ◽  
pp. 194187442110395
Author(s):  
Ayse Altintas ◽  
Ayca Ersen Danyeli ◽  
Subutay Berke Bozkurt ◽  
Sanem Pinar Uysal ◽  
Sergin Akpek ◽  
...  
Keyword(s):  
Decision Making ◽  
Urinary Retention ◽  
Clinical Decision Making ◽  
Treatment Options ◽  
Diagnostic Testing ◽  
Clinical Decision ◽  
Diagnostic Tools ◽  
Progressive Weakness ◽  
Over Time

Here we report a challenging case of a 52-year-old man presenting with subacute constipation, urinary retention, impotence, absent Achilles reflexes, and hypoesthesia in S2-S5 dermatomes. We review the clinical decision-making as the symptoms evolved and diagnostic testing changed over time. Once the diagnosis is settled, we discuss the sign and symptoms, additional diagnostic tools, treatment options and prognosis.

scholarly journals Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Rawan AlSaad ◽  
Qutaibah Malluhi ◽  
Ibrahim Janahi ◽  
Sabri Boughorbel
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Short Term Memory ◽  
Clinical Decision ◽  
Patient Specific ◽  
Great Promise ◽  
Short Term ◽  
Children With Asthma ◽  
Correct Pattern ◽  
Long Short Term Memory

Abstract Background Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. Recently, deep learning models have achieved state-of-the-art performance for many healthcare prediction tasks. However, deep models lack interpretability, which is integral to successful decision-making and can lead to better patient care. In this paper, we build upon the contextual decomposition (CD) method, an algorithm for producing importance scores from long short-term memory networks (LSTMs). We extend the method to bidirectional LSTMs (BiLSTMs) and use it in the context of predicting future clinical outcomes using patients’ EHR historical visits. Methods We use a real EHR dataset comprising 11071 patients, to evaluate and compare CD interpretations from LSTM and BiLSTM models. First, we train LSTM and BiLSTM models for the task of predicting which pre-school children with respiratory system-related complications will have asthma at school-age. After that, we conduct quantitative and qualitative analysis to evaluate the CD interpretations produced by the contextual decomposition of the trained models. In addition, we develop an interactive visualization to demonstrate the utility of CD scores in explaining predicted outcomes. Results Our experimental evaluation demonstrate that whenever a clear visit-level pattern exists, the models learn that pattern and the contextual decomposition can appropriately attribute the prediction to the correct pattern. In addition, the results confirm that the CD scores agree to a large extent with the importance scores generated using logistic regression coefficients. Our main insight was that rather than interpreting the attribution of individual visits to the predicted outcome, we could instead attribute a model’s prediction to a group of visits. Conclusion We presented a quantitative and qualitative evidence that CD interpretations can explain patient-specific predictions using CD attributions of individual visits or a group of visits.

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