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egillax committed Oct 28, 2024
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291 changes: 291 additions & 0 deletions vignettes/BestPractices.Rmd
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---
title: "Best Practice Research"
author: "Jenna Reps, Peter R. Rijnbeek"
date: '`r Sys.Date()`'
header-includes:
- \usepackage{fancyhdr}
- \pagestyle{fancy}
- \fancyhead{}
- \fancyhead[CO,CE]{Installation Guide}
- \fancyfoot[CO,CE]{PatientLevelPrediction Package Version `r utils::packageVersion("PatientLevelPrediction")`}
- \fancyfoot[LE,RO]{\thepage}
- \renewcommand{\headrulewidth}{0.4pt}
- \renewcommand{\footrulewidth}{0.4pt}
output:
pdf_document:
includes:
in_header: preamble.tex
number_sections: yes
toc: yes
word_document:
toc: yes
html_document:
number_sections: yes
toc: yes
---

```{=html}
<!--
%\VignetteEngine{knitr::knitr}
%\VignetteIndexEntry{Best Practices}
-->
```
## Best practice publications using the OHDSI PatientLevelPrediction framework

<table>
<tr>
<th>
Topic
</th>
<th>
Research Summary
</th>
<th>
Link
</th>
</tr>


<tr>
<td>
Problem Specification
</td>
<td>
When is prediction suitable in observational data?
</td>
<td>
Guidelines needed
</td>
</tr>


<tr>
<td>
Data Creation
</td>
<td>
Comparison of cohort vs case-control design
</td>
<td>
<a href='https://journalofbigdata.springeropen.com/articles/10.1186/s40537-021-00501-2'>Journal of Big Data</a>
</td>
</tr>

<tr>
<td>
Data Creation
</td>
<td>
Addressing loss to follow-up (right censoring)
</td>
<td>
<a href='https://link.springer.com/article/10.1186/s12911-021-01408-x'>BMC medical informatics and decision makingk</a>
</td>
</tr>

<tr>
<td>
Data Creation
</td>
<td>
Investigating how to address left censoring in features construction
</td>
<td>
<a href='https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-021-01370-2'>BMC Medical Research Methodology</a>
</td>
</tr>

<tr>
<td>
Data Creation
</td>
<td>
Impact of over/under-sampling
</td>
<td>
<a href='https://link.springer.com/article/10.1186/s40537-023-00857-7'> Journal of big data</a>
</td>
</tr>

<tr>
<td>
Data Creation
</td>
<td>
Impact of phenotypes
</td>
<td>
Study Done - Paper submitted
</td>
</tr>

<tr>
<td>
Model development
</td>
<td>
How much data do we need for prediction - Learning curves at scale
</td>
<td>
<a href='https://www.sciencedirect.com/science/article/pii/S1386505622000764'>International Journal of Medical Informatics </a>
</td>
</tr>

<tr>
<td>
Model development
</td>
<td>
What impact does test/train/validation design have on model performance
</td>
<td>
<a href='https://bmjopen.bmj.com/content/11/12/e050146'>BMJ Open </a>
</td>
</tr>

<tr>
<td>
Model development
</td>
<td>
What is the impact of the classifier
</td>
<td>
<a href='https://academic.oup.com/jamia/article/25/8/969/4989437?login=true'>JAMIA</a>
</td>
</tr>

<tr>
<td>
Model development
</td>
<td>
Can we find hyper-parameter combinations per classifier that consistently lead to good performing models when using claims/EHR data?
</td>
<td>
Study needs to be done
</td>
</tr>

<tr>
<td>
Model development
</td>
<td>
Can we use ensembles to combine different algorithm models within a database to improve models transportability?
</td>
<td>
<a href='https://ebooks.iospress.nl/doi/10.3233/SHTI230080'> Caring is Sharing–Exploiting the Value in Data for Health and Innovation </a>
</td>
</tr>

<tr>
<td>
Model development
</td>
<td>
Can we use ensembles to combine models developed using different databases to improve models transportability?
</td>
<td>
<a href='https://link.springer.com/article/10.1186/s12911-022-01879-6'> BMC Medical Informatics and Decision Making </a>
</td>
</tr>

<tr>
<td>
Model development
</td>
<td>
Impact of regularization method
</td>
<td>
<a href='https://academic.oup.com/jamia/article/31/7/1514/7676584'> JAMIA </a>
</td>
</tr>

<tr>
<td>
Evaluation
</td>
<td>
Why prediction is not suitable for risk factor identification
</td>
<td>
<a href='https://proceedings.mlr.press/v182/markus22a.html'> Machine Learning for Healthcare Conference </a>
</td>
</tr>

<tr>
<td>
Evaluation
</td>
<td>
Iterative pairwise external validation to put validation into context
</td>
<td>
<a href='https://link.springer.com/article/10.1007/s40264-022-01161-8'> Drug Safety </a>
</td>
</tr>


<tr>
<td>
Evaluation
</td>
<td>
A novel method to estimate external validation using aggregate statistics
</td>
<td>
<a href=''> Study under review </a>
</td>
</tr>

<tr>
<td>
Evaluation
</td>
<td>
How should we present model performance? (e.g., new visualizations)
</td>
<td>
<a href='https://academic.oup.com/jamiaopen/article/4/1/ooab017/6168493?searchresult=1'>JAMIA Open</a>
</td>
</tr>

<tr>
<td>
Evaluation
</td>
<td>
How to interpret external validation performance (can we figure out why the performance drops or stays consistent)?
</td>
<td>
Study needs to be done
</td>
</tr>

<tr>
<td>
Evaluation
</td>
<td>
Recalibration methods
</td>
<td>
Study needs to be done
</td>
</tr>

<tr>
<td>
Evaluation
</td>
<td>
Is there a way to automatically simplify models?
</td>
<td>
<a href='https://ohdsi-studies.github.io/FeatureSelectionComparison/docs/Protocol.html'>Study protocol under development </a>
</td>
</tr>
</table>

46 changes: 46 additions & 0 deletions vignettes/ClinicalModels.Rmd
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Original file line number Diff line number Diff line change
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---
title: "Clinical Models"
author: "Jenna Reps, Peter R. Rijnbeek"
date: '`r Sys.Date()`'
header-includes:
- \usepackage{fancyhdr}
- \pagestyle{fancy}
- \fancyhead{}
- \fancyhead[CO,CE]{Installation Guide}
- \fancyfoot[CO,CE]{PatientLevelPrediction Package Version `r utils::packageVersion("PatientLevelPrediction")`}
- \fancyfoot[LE,RO]{\thepage}
- \renewcommand{\headrulewidth}{0.4pt}
- \renewcommand{\footrulewidth}{0.4pt}
output:
pdf_document:
includes:
in_header: preamble.tex
number_sections: yes
toc: yes
word_document:
toc: yes
html_document:
number_sections: yes
toc: yes
---

```{=html}
<!--
%\VignetteEngine{knitr::knitr}
%\VignetteIndexEntry{Clinical Models}
-->
```

## Clinical models developed using the OHDSI PatientLevelPrediction framework

| Title | Link |
|----------------------|-------|
| Using Machine Learning Applied to Real-World Healthcare Data for Predictive Analytics: An Applied Example in Bariatric Surgery | [Value in Health](https://www.sciencedirect.com/science/article/pii/S1098301519300737) |
| Development and validation of a prognostic model predicting symptomatic hemorrhagic transformation in acute ischemic stroke at scale in the OHDSI network | [PLoS One](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0226718) |
| Wisdom of the CROUD: development and validation of a patient-level prediction model for opioid use disorder using population-level claims data | [PLoS One](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0228632) |
| Developing predictive models to determine Patients in End-of-life Care in Administrative datasets | [Drug Safety](https://link.springer.com/article/10.1007/s40264-020-00906-7) |
| Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study | [Translational psychiatry](https://www.nature.com/articles/s41398-021-01760-6) |
| Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network | [BMC Medical Research Methodology](https://link.springer.com/article/10.1186/s12874-022-01505-z) |
| 90-Day all-cause mortality can be predicted following a total knee replacement: an international, network study to develop and validate a prediction model | [Knee Surgery, Sports Traumatology, Arthroscopy](https://link.springer.com/article/10.1007/s00167-021-06799-y) |
| Machine learning and real-world data to predict lung cancer risk in routine care | [Cancer Epidemiology, Biomarkers & Prevention](https://aacrjournals.org/cebp/article-abstract/32/3/337/718495) |
| Development and validation of a patient-level model to predict dementia across a network of observational databases | [BMC medicine](https://link.springer.com/article/10.1186/s12916-024-03530-9) |
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