Diagnostic and prognostic prediction models

Applied logistic regression

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The meaning and use of the area under a receiver operating characteristic (ROC) curve.

Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856

Applied Logistic Regression

Hosmer, D. W., & Lemeshow, S. (2000) · doi:10.1002/0471722146 · Cited by 20,302

A simulation study of the number of events per variable in logistic regression analysis

Peduzzi, P., Concato, J., Kemper, E., Holford, T. R., & Feinstein, A. R. (1996) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(96)00236-3 · Cited by 9,655

Regression Modeling Strategies

Harrell, F. E. (2001) · Springer series in statistics · doi:10.1007/978-1-4757-3462-1 · Cited by 9,270

Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis

Harrell (2015) · Springer Series in Statistics · doi:10.1007/978-3-319-19425-7 · Cited by 6,878

Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond

Pencina, M. J., D' Agostino, R. B., D' Agostino, R. B., & Vasan, R. S. (2008) · Statistics in Medicine · doi:10.1002/sim.2929 · Cited by 6,493

Consort 2010 statement: extension to cluster randomised trials

Campbell, M. K., Piaggio, G., Elbourne, D. R., Altman, D. G., & for the CONSORT Group (2012) · BMJ · doi:10.1136/bmj.e5661 · Cited by 3,510

Clinical Epidemiology: A Basic Science for Clinical Medicine.

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Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating

Steyerberg, E. W. (2019) · Statistics for Biology and Health · doi:10.1007/978-3-030-16399-0 · Cited by 3,281

A Risk Predictive Model for the Severity of Illness in Patients with Severe Fever with Thrombocytopenia SyndromePreprint

Tao, S., Wu, Y., Zhang, A., Liang, M., Wang, Z., & Yang, J. (2023) · Research Square · doi:10.21203/rs.3.rs-3135703/v1

Development of a risk prediction model for endometrial carcinoma among postmenopausal women in the Western province of Sri Lanka

Jayawickrama, W. I. U., & Abeysena, C. (2022) · Ceylon Medical Journal · doi:10.4038/cmj.v67i4.9746

Methodological Issues with Head and Neck Cancer Prognostic Risk Prediction Models

Ghanati, H., Madathil, S. A., Al-Tamimi, M., Asmar, Z. A., Morris, M., & Nicolau, B. F. (2023) · Community Dental Health · doi:10.1922/cdh_00015ghanati09

Role of microbiome and microbial extracellular vesicles in tumor microenvironment

Kim, Y. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-824040-3.00002-9

Surgical risk assessment tool for unplanned readmissions (STUR)Preprint

Snyders, P., Swart, O., & Lübbe, J. (2024) · Research Square · doi:10.21203/rs.3.rs-4767593/v1

How certainty is certain enough? Challenges in the statistical methodology for forensic age assessment of living individuals

Streeter, A., Schmeling, A., & Karch, A. (2024) · Medicina Clínica (English Edition) · doi:10.1016/j.medcle.2024.07.007

Text-based fall prediction in hospital: Development and internal validation of a model to predict in-hospital falls in older patients using free text from daily nursing records

Groeneveld, M., Leurs, W. L. M., Bouwman, R. A., Schenk, J., Lammers, L. A. S., Dierick, A., Korsten, E. H. H. M., & van der Linden, C. C. M. J. (2025) · Applied Nursing Research · doi:10.1016/j.apnr.2025.151923

The inclusion and intended use of prediction models in clinical guidelines: a systematic review of five clinical domains in four countries

de Kanter, E., Vernooij, R. W. M., Veld, L. F. H. I. ’., Schuit, E., Moons, K. G. M., Hooft, L., & Damen, J. A. (2026) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2026.112288

Predicting Outcomes of Early and Late Acute Periprosthetic Joint Infections Treated With Debridement, Irrigation, and Implant Retention: An External Validation of the CRIME80 (COPD, C-Reactive Protein, Rheumatoid Arthritis, Index Surgery, Male, Exchange of Mobile Components, Age Greater than 80 years) Score

Naufal, E. R., Babazadeh, S., Aboltins, C. A., Choong, P., Fillingham, Y. A., Higuera, C. A., Otero, J. E., Piuzzi, N. S., Shadbolt, C., Soriano, À., et al. (2025) · The Journal of Arthroplasty · doi:10.1016/j.arth.2025.11.021

Additional file 1 of Development and internal validation of prediction models for colorectal cancer survivors to estimate the 1-year risk of low health-related quality of life in multiple domains

Révész, D., van Kuijk, S. M. J., Mols, F., van Duijnhoven, F. J. B., Winkels, R. M., Hoofs, H., Kant, I., Smits, L. J. M., Breukink, S. O., van de Poll-Franse, L. V., et al. (2020) · Figshare · doi:10.6084/m9.figshare.11979024

Additional file 1 of Development of a diagnostic predictive model for determining child stunting in Malawi: a comparative analysis of variable selection approaches

Mkungudza, J., Twabi, H. S., & Manda, S. (2024) · Figshare · doi:10.6084/m9.figshare.26758715

Additional file 2 of Development and internal validation of prediction models for colorectal cancer survivors to estimate the 1-year risk of low health-related quality of life in multiple domains

Révész, D., van Kuijk, S. M. J., Mols, F., van Duijnhoven, F. J. B., Winkels, R. M., Hoofs, H., Kant, I., Smits, L. J. M., Breukink, S. O., van de Poll-Franse, L. V., et al. (2020) · Figshare · doi:10.6084/m9.figshare.11979033

Additional file 5 of Development and internal validation of prediction models for colorectal cancer survivors to estimate the 1-year risk of low health-related quality of life in multiple domains

Révész, D., van Kuijk, S. M. J., Mols, F., van Duijnhoven, F. J. B., Winkels, R. M., Hoofs, H., Kant, I., Smits, L. J. M., Breukink, S. O., van de Poll-Franse, L. V., et al. (2020) · Figshare · doi:10.6084/m9.figshare.11979060

Additional file 1 of Patient similarity analytics for explainable clinical risk prediction

Fang, H. S. A., Tan, N. C., Tan, W. Y., Oei, R. W., Lee, M. L., & Hsu, W. (2021) · Figshare · doi:10.6084/m9.figshare.14897350

Additional file 3 of Development and internal validation of prediction models for colorectal cancer survivors to estimate the 1-year risk of low health-related quality of life in multiple domains

Révész, D., van Kuijk, S. M. J., Mols, F., van Duijnhoven, F. J. B., Winkels, R. M., Hoofs, H., Kant, I., Smits, L. J. M., Breukink, S. O., van de Poll-Franse, L. V., et al. (2020) · Figshare · doi:10.6084/m9.figshare.11979042

Additional file 1 of Development, validation and effectiveness of diagnostic prediction tools for colorectal cancer in primary care: a systematic review

Grigore, B., Lewis, R., Peters, J., Robinson, S., & Hyde, C. J. (2020) · Figshare · doi:10.6084/m9.figshare.13219284

Additional file 6 of Development and internal validation of prediction models for colorectal cancer survivors to estimate the 1-year risk of low health-related quality of life in multiple domains

Révész, D., van Kuijk, S. M. J., Mols, F., van Duijnhoven, F. J. B., Winkels, R. M., Hoofs, H., Kant, I., Smits, L. J. M., Breukink, S. O., van de Poll-Franse, L. V., et al. (2020) · Figshare · doi:10.6084/m9.figshare.11979063

Additional file 4 of Development and internal validation of prediction models for colorectal cancer survivors to estimate the 1-year risk of low health-related quality of life in multiple domains

Révész, D., van Kuijk, S. M. J., Mols, F., van Duijnhoven, F. J. B., Winkels, R. M., Hoofs, H., Kant, I., Smits, L. J. M., Breukink, S. O., van de Poll-Franse, L. V., et al. (2020) · Figshare · doi:10.6084/m9.figshare.11979051

Polymorphismes des gènes associés à l’inflammation et microenvironnement tumoral lymphocytaire CD8+ : valeur pronostique dans les carcinomes urothéliaux de la vessie.

Masson-Lecomte, A. (2017) · doi:10.70675/d21e56eez7d33z4293za3f7z06097e64c862

Risk prediction models for venous thromboembolism in stroke: a systematic review and meta-analysis

Fu, L., Cui, C., Feng, K., Li, X., Wang, M., Muhammad, Z., & Liu, N. (2026) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2026.1788144

Development and Validation of a Depression Risk Prediction Model for Community Elderly IndividualsPreprint

Zhao, R., Huo, M., Tan, M., Cai, Y., Geng, X., Xia, M., Chen, Y., & Liu, X. (2026) · Research Square · doi:10.21203/rs.3.rs-9252451/v1

Prediction models in clinical guidelines: a scoping review of clinical guideline guidance development documents

de Kanter, E., Idema, D. L., Hooft, L., Moons, K. G. M., Vernooij, R. W. M., Schuit, E., & Damen, J. A. (2026) · BMJ Evidence-Based Medicine · doi:10.1136/bmjebm-2025-114164

EviCare: Enhancing Diagnosis Prediction with Deep Model-Guided Evidence for In-Context Reasoning

Zhang, H., Zhang, X., Zhan, P., Luo, L., Lv, H., Tan, Y., Pan, S., & Yang, C. (2026) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3770854.3780257

Prediction Models for Lower Limb Lymphedema after Surgery in Patients with Gynecological Malignancies: A Systematic Review

Li, H., Zhang, Y., Li, W., & Lu, Y. (2026) · Lymphatic Research and Biology · doi:10.1177/15578585261470704

Impact of a diagnostic strategy for appendicitis in children with acute abdominal pain in primary care: study protocol for a hybrid type 1 cluster randomised controlled trial

Hogervorst, E. M., Venekamp, R. P., Vries, G. E. K., Platteel, T. N., Watjer, R. M., Hurkmans, D. P., Numans, M. E., Blok, G., Naber, E. J. A. Q., de Boer, M. R., et al. (2026) · Diagnostic and Prognostic Research · doi:10.1186/s41512-026-00234-x

Principles Of developing predictive models in medicine and Their application in liver transplantation

Monakhov, A. R. (2026) · Russian Journal of Transplantology and Artificial Organs · doi:10.15825/1995-1191-2026-3-39-53

Developing a Clinical and Conventional Radiographic Tool for Vertical Root Fracture Prediction in Root‐Filled Teeth

Chalermchaicharoenkit, J., Chotvorrarak, K., Promchouy, P., Phinyo, P., & Osiri, S. (2026) · International Endodontic Journal · doi:10.1111/iej.70272

Multivariable Prognostic Models for Age‐Related Macular Degeneration: A Systematic Review

Aljied, R., Saggu, S., Chaudhary, V., Pigeyre, M., Griffith, L. E., & Raina, P. S. (2026) · Journal of Ophthalmology · doi:10.1155/joph/9231744

Systematic review of prognostic models for recurrent venous thromboembolism (VTE) post-treatment of first unprovoked VTE

Ensor, J., Riley, R. D., Moore, D., Snell, K. I. E., Bayliss, S., & Fitzmaurice, D. (2016) · BMJ Open · doi:10.1136/bmjopen-2016-011190 · Cited by 84

Predicting venous thromboembolism among hospitalized adults: a protocol for development and validation of an implementable real-time prognostic model

Domenico, H. J., Tillman, B. F., Just, S. L., Ko, Y., Mixon, A. S., Weitkamp, A. O., Schildcrout, J. S., Walsh, C. G., Ortel, T. L., & French, B. C. (2025) · Diagnostic and Prognostic Research · doi:10.1186/s41512-025-00205-8 · Cited by 2

Introduction to Clinical Prediction Models

Iwagami, M., & Matsui, H. (2022) · Annals of Clinical Epidemiology · doi:10.37737/ace.22010 · Cited by 32

Predicting the risk of venous thromboembolism in critically ill patients (PROVE-IT): a model development and validation study

Rivrud, S. C. S., Heijkoop, È. R. H., Hulshof, L., van den Oever, N. C. G., Wetterslev, M., Perner, A., Keus, F., Meijer, K., & Eck, R. J. (2025) · Journal of Thrombosis and Haemostasis · doi:10.1016/j.jtha.2025.06.026 · Cited by 4

Risk of recurrence after a first unprovoked venous thromboembolism: external validation of the Vienna Prediction Model with pooled individual patient data

Marcucci, M., Iorio, A., Douketis, J. D., Eichinger, S., Tosetto, A., Baglin, T. P., Cushman, M., Palareti, G., Poli, D., Tait, R. C., et al. (2015) · Journal of Thrombosis and Haemostasis · doi:10.1111/jth.12871 · Cited by 74