The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Understanding diagnostic tests 3: receiver operating characteristic curves
Abstract
The results of many clinical tests are quantitative and are provided on a continuous scale. To help decide the presence or absence of disease, a cut‐off point for ‘normal’ or ‘abnormal’ is chosen. The sensitivity and specificity of a test vary according to the level that is chosen as the cut‐off point. The receiver operating characteristic (ROC) curve, a graphical technique for describing and comparing the accuracy of diagnostic tests, is obtained by plotting the sensitivity of a test on the y axis against 1‐specificity on the x axis. Two methods commonly used to establish the optimal cut‐off point include the point on the ROC curve closest to (0, 1) and the Youden index. The area under the ROC curve provides a measure of the overall performance of a diagnostic test. In this paper, the author explains how the ROC curve can be used to select optimal cut‐off points for a test result, to assess the diagnostic accuracy of a test, and to compare the usefulness of tests. Conclusion: The ROC curve is obtained by calculating the sensitivity and specificity of a test at every possible cut‐off point, and plotting sensitivity against 1‐specificity. The curve may be used to select optimal cut‐off values for a test result, to assess the diagnostic accuracy of a test, and to compare the usefulness of different tests.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The AUC values ranged from .63 to .76 and were considered in acceptable range (Akobeng, 2007; Fischer et al., 2003).”
From Exercise habit formation in new gym members: a longitudinal study (2015) · cites this paper as Akobeng, 2007
Citations
Cites
Estimation of the Youden Index and its Associated Cutoff Point
Fluss, R., Faraggi, D., & Reiser, B. (2005) · Biometrical Journal · doi:10.1002/bimj.200410135 · Cited by 2,656
Greiner, M., Pfeiffer, D., & Smith, R. D. (2000) · Preventive Veterinary Medicine · doi:10.1016/s0167-5877(00)00115-x · Cited by 1,923
Perkins, N. J., & Schisterman, E. F. (2006) · American Journal of Epidemiology · doi:10.1093/aje/kwj063 · Cited by 1,794
A readers' guide to the interpretation of diagnostic test properties: clinical example of sepsis
Fischer, J. E., Bachmann, L. M., & Jaeschke, R. (2003) · Intensive Care Medicine · doi:10.1007/s00134-003-1761-8 · Cited by 890
Understanding diagnostic tests 1: sensitivity, specificity and predictive values
Akobeng, A. K. (2007) · Acta Paediatrica · doi:10.1111/j.1651-2227.2006.00180.x · Cited by 711
Self-citationStatistics Notes: Diagnostic tests 3: receiver operating characteristic plots
Altman, D. G., & Bland, J. M. (1994) · BMJ · doi:10.1136/bmj.309.6948.188 · Cited by 599
ROC Curves in Clinical Chemistry: Uses, Misuses, and Possible Solutions
Obuchowski, N. A., Lieber, M. L., & Wians, F. H. (2004) · Clinical Chemistry · doi:10.1373/clinchem.2004.031823 · Cited by 358
How to report statistics in medicine: annotated guidelines for authors, editors, and reviewers
(1997) · Choice Reviews Online · doi:10.5860/choice.35-1556 · Cited by 309
Hatherill, M., Tibby, S. M., Sykes, K., Turner, C., & Murdoch, I. (1999) · Archives of Disease in Childhood · doi:10.1136/adc.81.5.417 · Cited by 260
How to Report Statistics in Medicine
Lang, T. A., & Secic, M. (1997) · The Nurse Practitioner · doi:10.1097/00006205-199705000-00022 · Cited by 209
Research works printed but not linked: 1
- Akobeng AK, Understanding diagnostic tests 2: using likelihood ratios to estimate probability of disease, Acta Paediatr
Cited by
Sorted by citations
(2013) · Europe PMC (PubMed Central) · Cited by 2,089
Receiver operating characteristic curve: overview and practical use for clinicians
Nahm, F. S. (2022) · Korean Journal of Anesthesiology · doi:10.4097/kja.21209 · Cited by 1,680
Systematic Reviews of Diagnostic Test Accuracy
Leeflang, M. M. G., Deeks, J. J., Gatsonis, C., & Bossuyt, P. M. M. (2008) · Annals of Internal Medicine · doi:10.7326/0003-4819-149-12-200812160-00008 · Cited by 1,124
Receiver operating characteristic curve analysis in diagnostic accuracy studies
Çorbacıoğlu, Ş. K., & Aksel, G. (2023) · Turkish Journal of Emergency Medicine · doi:10.4103/tjem.tjem_182_23 · Cited by 945
On determining the most appropriate test cut-off value: the case of tests with continuous results
Habibzadeh, F., Habibzadeh, P., & Yadollahie, M. (2016) · Biochemia Medica · doi:10.11613/bm.2016.034 · Cited by 696
Sakurai, K., Nishi, A., Kondo, K., Yanagida, K., & Kawakami, N. (2011) · Psychiatry and Clinical Neurosciences · doi:10.1111/j.1440-1819.2011.02236.x · Cited by 649
Norms for Zung’s Self-rating Anxiety Scale
Dunstan, D. A., & Scott, N. (2020) · BMC Psychiatry · doi:10.1186/s12888-019-2427-6 · Cited by 576
Validation of a Korean Version of the Insomnia Severity Index
Cho, Y. W., Song, M. L., & Morinc, C. M. (2014) · Journal of Clinical Neurology · doi:10.3988/jcn.2014.10.3.210 · Cited by 472
Naccache, S. N., Federman, S., Veeraraghavan, N., Zaharia, M., Lee, D., Samayoa, E., Bouquet, J., Greninger, A. L., Luk, K.-C., Enge, B., et al. (2014) · Genome Research · doi:10.1101/gr.171934.113 · Cited by 460
Wu, Y., Ke, Y., Chen, Z., Liang, S., Zhao, H., & Hong, H. (2019) · CATENA · doi:10.1016/j.catena.2019.104396 · Cited by 401
Development of a work addiction scale
Andreassen, C. S., Griffiths, M. D., Hetland, J., & Pallesen, S. (2012) · Scandinavian Journal of Psychology · doi:10.1111/j.1467-9450.2012.00947.x · Cited by 415
Machine learning applications in epilepsy
Abbasi, B., & Goldenholz, D. M. (2019) · Epilepsia · doi:10.1111/epi.16333 · Cited by 373
Hand‐Grip Strength Cut Points to Screen Older Persons at Risk for Mobility Limitation
SALLINEN, J. M., Stenholm, S., Rantanen, T., Heliövaara, M., Sainio, P., & Koskinen, S. V. P. (2010) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2010.03035.x · Cited by 346
Leddy, A. L., Crowner, B. E., & Earhart, G. M. (2010) · Physical Therapy · doi:10.2522/ptj.20100113 · Cited by 322
Khayambashi, K., Ghoddosi, N., Straub, R. K., & Powers, C. M. (2016) · The American Journal of Sports Medicine · doi:10.1177/0363546515616237 · Cited by 308
Exercise habit formation in new gym members: a longitudinal study
Kaushal, N., & Rhodes, R. E. (2015) · Journal of Behavioral Medicine · doi:10.1007/s10865-015-9640-7 · Cited by 285
Ibrahim, H., Ertl, V., Catani, C., Ismail, A. A., & Neuner, F. (2018) · BMC Psychiatry · doi:10.1186/s12888-018-1839-z · Cited by 277
Predictive Significance of Tissue Eosinophilia for Nasal Polyp Recurrence in the Chinese Population
Lou, H., Meng, Y., Piao, Y., Wang, C., Zhang, L., & Bachert, C. (2015) · American Journal of Rhinology and Allergy · doi:10.2500/ajra.2015.29.4231 · Cited by 277
Using Resistin, glucose, age and BMI to predict the presence of breast cancer
Patrício, M., Pereira, J., Crisóstomo, J., Matafome, P. N., Gomes, M., Seiça, R. M. F., & Caramelo, F. J. (2018) · BMC Cancer · doi:10.1186/s12885-017-3877-1 · Cited by 277
A code for transcription initiation in mammalian genomesPreprint
Frith, M. C., Valen, E., Krogh, A., Hayashizaki, Y., Carninci, P., & Sandelin, A. (2007) · Genome Research · doi:10.1101/gr.6831208 · Cited by 272
A rational approach to fluid therapy in sepsis
Marik, P. E., & Bellomo, R. (2015) · British Journal of Anaesthesia · doi:10.1093/bja/aev349 · Cited by 265
Circulating microRNAs in plasma of patients with oesophageal squamous cell carcinoma
Komatsu, S., Ichikawa, D., Takeshita, H., Tsujiura, M., Morimura, R., Nagata, H., Kosuga, T., Iitaka, D., Konishi, H., Shiozaki, A., et al. (2011) · British Journal of Cancer · doi:10.1038/bjc.2011.198 · Cited by 258
Evidence Based Emergency Medicine; Part 5 Receiver Operating Curve and Area under the Curve.
Safari, S., Baratloo, A., Elfil, M., & Negida, A. (2016) · Archives of Academic Emergency Medicine · doi:10.22037/aaem.v4i2.232 · Cited by 253
Hui, D., Shamieh, O. M., Paiva, C. E., Perez‐Cruz, P. E., Kwon, J. H., Muckaden, M. A., Park, M., Yennurajalingam, S., Kang, J. H., & Bruera, E. D. (2015) · Cancer · doi:10.1002/cncr.29437 · Cited by 251
Kim, Y., Jeong, J.-E., Cho, H., Jung, D.-J., Kwak, M., Rho, M. J., Yu, H., Kim, D., & Choi, I. Y. (2016) · PLoS ONE · doi:10.1371/journal.pone.0159788 · Cited by 228
Kohler, C., Radpour, R., Barekati, Z., Asadollahi, R., Bitzer, J., Wight, E., Bürki, N., Diesch, C., Holzgreve, W., & Zhong, X. Y. (2009) · Molecular Cancer · doi:10.1186/1476-4598-8-105 · Cited by 215
Clinical impact of circulating miR-221 in plasma of patients with pancreatic cancer
Kawaguchi, T., Komatsu, S., Ichikawa, D., Morimura, R., Tsujiura, M., Konishi, H., Takeshita, H., Nagata, H., Arita, T., Hirajima, S., et al. (2013) · British Journal of Cancer · doi:10.1038/bjc.2012.546 · Cited by 212
Fang, C.-K., Chang, M.-C., Chen, P.-J., Lin, C.-C., Chen, G.-S., Lin, J., Hsieh, R.-K., Chang, Y.-F., Chen, H.-W., Wu, C.-L., et al. (2014) · Supportive Care in Cancer · doi:10.1007/s00520-014-2290-4 · Cited by 211
How early do parent concerns predict later autism diagnosis?
Ozonoff, S., Young, G. S., Steinfeld, M. B., Hill, M. M., Cook, I., Hutman, T., Macari, S., Rogers, S. J., & Sigman, M. (2009) · Journal of Developmental & Behavioral Pediatrics · doi:10.1097/dbp.0b013e3181ba0fcf · Cited by 210
Bahoura, M. (2009) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2009.06.011 · Cited by 211
Konishi, H., Ichikawa, D., Komatsu, S., Shiozaki, A., Tsujiura, M., Takeshita, H., Morimura, R., Nagata, H., Arita, T., Kawaguchi, T., et al. (2012) · British Journal of Cancer · doi:10.1038/bjc.2011.588 · Cited by 199
Clarification of the cut-off score for Zung’s self-rating depression scale
Dunstan, D. A., & Scott, N. (2019) · BMC Psychiatry · doi:10.1186/s12888-019-2161-0 · Cited by 220
Tarnanas, I., Schlee, W., Tsolaki, M., Müri, R. M., Mosimann, U. P., & Nef, T. (2013) · JMIR Serious Games · doi:10.2196/games.2778 · Cited by 195
Kroenke, K., Yu, Z., Wu, J., Kean, J., & Monahan, P. O. (2014) · Pain Medicine · doi:10.1111/pme.12537 · Cited by 187
Evaluation of a panel of 28 biomarkers for the non-invasive diagnosis of endometriosis
Vodolazkaia, A., El-Aalamat, Y., Popovic, D., Mihalyi, A., Bossuyt, X., Kyama, C. M., Fassbender, A., Bokor, A., Schols, D., Huskens, D., et al. (2012) · Human Reproduction · doi:10.1093/humrep/des234 · Cited by 189
Pieruccini‐Faria, F., Black, S. E., Masellis, M., Smith, E. E., Almeida, Q. J., Li, K., Bherer, L., Camicioli, R. M., & Montero‐Odasso, M. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12298 · Cited by 198
Chen, W., Cai, F., Zhang, B., Barekati, Z., & Zhong, X. Y. (2012) · Tumor Biology · doi:10.1007/s13277-012-0570-5 · Cited by 176
Using sensation seeking to target adolescents for substance use interventions
Sargent, J. D., Tanski, S. E., Stoolmiller, M., & Hanewinkel, R. (2010) · Addiction · doi:10.1111/j.1360-0443.2009.02782.x · Cited by 176
Using opportunistic citizen science data to estimate avian population trends
Horns, J. J., Adler, F. R., & Sekercioglu, C. H. (2018) · Biological Conservation · doi:10.1016/j.biocon.2018.02.027 · Cited by 177
Bafadhel, M., Clark, T. W., Reid, C., Medina, M. J., Batham, S., Barer, M. R., Nicholson, K. G., & Brightling, C. E. (2010) · CHEST Journal · doi:10.1378/chest.10-1747 · Cited by 180
Virhammar, J., Laurell, K., Cesarini, K. G., & Larsson, E. (2013) · Journal of neurosurgery · doi:10.3171/2013.8.jns13575 · Cited by 167
Flygare, S., Simmon, K., Miller, C., Qiao, Y., Kennedy, B., Di Sera, T., Graf, E. H., Tardif, K. D., Kapusta, A., Rynearson, S., et al. (2016) · Genome Biology · doi:10.1186/s13059-016-0969-1 · Cited by 164
Hui, D., Shamieh, O. M., Paiva, C. E., Khamash, O., Perez‐Cruz, P. E., Kwon, J. H., Muckaden, M. A., Park, M., Arthur, J. A., & Bruera, E. D. (2015) · Journal of Pain and Symptom Management · doi:10.1016/j.jpainsymman.2015.10.004 · Cited by 165
White, D. K., Tudor-Locke, C. E., Zhang, Y., Fielding, R. A., LaValley, M. P., Felson, D. T., Gross, K. D., Nevitt, M. C., Lewis, C. E., Torner, J. C., et al. (2014) · Arthritis Care & Research · doi:10.1002/acr.22362 · Cited by 165
Lu, R., Munroe, M. E., Guthridge, J. M., Bean, K. M., Fife, D. A., Chen, H., Slight-Webb, S. R., Keith, M. P., Harley, J. B., & James, J. A. (2016) · Journal of Autoimmunity · doi:10.1016/j.jaut.2016.06.001 · Cited by 162
Yang, J., Deng, Y., Chu, H., Cong, Y., Zhao, J., Pohl, D., Misselwitz, B., Fried, M., Dai, N., & Fox, M. R. (2012) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2012.11.034 · Cited by 158
Lu, W., Chen, X., Wang, L., Li, H., & Fu, Y. V. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.9b04946 · Cited by 158
Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images
Tolpadi, A., Lee, J. J., Pedoia, V., & Majumdar, S. (2020) · Scientific Reports · doi:10.1038/s41598-020-63395-9 · Cited by 161
Badin, J., Boulain, T., Ehrmann, S., Skarzynski, M., Bretagnol, A., Buret, J., Benzékri-Lefèvre, D., Mercier, E., Runge, I., Garot, D., et al. (2011) · Critical Care · doi:10.1186/cc10253 · Cited by 150
Redmond, S. M., Thompson, H. L., & Goldstein, S. (2010) · Journal of Speech Language and Hearing Research · doi:10.1044/1092-4388(2010/10-0010 · Cited by 149
New clinical diagnostic criteria for eosinophilic chronic rhinosinusitis
Sakuma, Y., Ishitoya, J., Komatsu, M., Shiono, O., Hirama, M., Yamashita, Y., Kaneko, T., Morita, S., & Tsukuda, M. (2011) · Auris Nasus Larynx · doi:10.1016/j.anl.2011.01.007 · Cited by 148
Salivary MicroRNAs as Promising Biomarkers for Detection of Esophageal Cancer
Xie, Z., Chen, G., Zhang, X., Li, D., Huang, J. J., CuiQin, Y., Zhang, P., Qin, Y., Duan, Y., Gong, B., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057502 · Cited by 146
Zhou, X., Pang, Z., Gao, W., Wang, S., Zhang, L., Ning, F., & Qiao, Q. (2010) · Diabetes Care · doi:10.2337/dc09-1410 · Cited by 146
Petersen, I. T., Bates, J. E., Dodge, K. A., Lansford, J. E., & Pettit, G. S. (2014) · Development and Psychopathology · doi:10.1017/s0954579414000789 · Cited by 164
Steenkiste, T. V., Groenendaal, W., Deschrijver, D., & Dhaene, T. (2018) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2018.2886064 · Cited by 146
Häggström, J. U., Andersson, Å. O., Falk, T., Nilsfors, L., OIsson, U., Kresken, J., Höglund, K., Rishniw, M., Tidholm, A., & Ljungvall, I. (2016) · Journal of Veterinary Internal Medicine · doi:10.1111/jvim.14569 · Cited by 140
Kierkegaard, M., Einarsson, U., Gottberg, K., von Koch, L., & Holmqvist, L. W. (2011) · Multiple Sclerosis Journal · doi:10.1177/1352458511426736 · Cited by 133
van Praag, V. M., Rueten‐Budde, A. J., Jeys, L. M., Laitinen, M., Pollock, R. C., Aston, W., van der Hage, J. A., Dijkstra, P. D. S., Ferguson, P. C., Griffin, A. M., et al. (2017) · European Journal of Cancer · doi:10.1016/j.ejca.2017.06.032 · Cited by 132
Utility and limitations of PHQ-9 in a clinic specializing in psychiatric care
Inoue, T., Tanaka, T., Nakagawa, S., Nakato, Y., Kameyama, R., Boku, S., Toda, H., Kurita, T., & Koyama, T. (2012) · BMC Psychiatry · doi:10.1186/1471-244x-12-73 · Cited by 128
Pandey, R., Chang, D., Smieja, M., Hoare, T. R., Li, Y., & Soleymani, L. (2021) · Nature Chemistry · doi:10.1038/s41557-021-00718-x · Cited by 128
Lindsay, B. R., Ochieng, J. B., Ikumapayi, U. N., Touré, A., Ahmed, D., Li, S., Panchalingam, S., Levine, M. M., Kotloff, K. L., Rasko, D. A., et al. (2013) · Journal of Clinical Microbiology · doi:10.1128/jcm.02713-12 · Cited by 127
Nhu, V., Shirzadi, A., Shahabi, H., Chen, W., Clague, J. J., Geertsema, M., Jaafari, A., Avand, M., Miraki, S., Asl, D. T., et al. (2020) · Forests · doi:10.3390/f11040421 · Cited by 127
Wei, T., Liu, P.-T., Chang, L.-W., & Liu, S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0177136 · Cited by 124
Coombes, B. K., Tucker, K. J., Vicenzino, B., Vuvan, V., Mellor, R., Heales, L., Nordez, A., & Hug, F. (2017) · Scandinavian Journal of Medicine and Science in Sports · doi:10.1111/sms.12986 · Cited by 124
Acute exacerbation of idiopathic pulmonary fibrosis: high-resolution CT scores predict mortality
Fujimoto, K., Taniguchi, H., Johkoh, T., Kondoh, Y., Ichikado, K., Sumikawa, H., Ogura, T., Kataoka, K., Takahiro, E. N. D. O., Kawaguchi, A., et al. (2011) · European Radiology · doi:10.1007/s00330-011-2211-6 · Cited by 127
Voss, C., Dean, P. H., Gardner, R. F., Duncombe, S. L., & Harris, K. C. (2017) · PLoS ONE · doi:10.1371/journal.pone.0175806 · Cited by 132
Duncan, R. P., Leddy, A. L., Cavanaugh, J. T., Dibble, L. E., Ellis, T. D., Ford, M. P., Foreman, K. B., & Earhart, G. M. (2012) · Physical Therapy · doi:10.2522/ptj.20120302 · Cited by 122
Hogan, D. B., Freiheit, E., Strain, L. A., Patten, S. B., Schmaltz, H. N., Rolfson, D. B., & Maxwell, C. J. (2012) · BMC Geriatrics · doi:10.1186/1471-2318-12-56 · Cited by 120
Kaymak, B., Özçakar, L., Çetin, A., Çetin, M. C., Akıncı, A., & Hasçelik, Z. (2008) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2007.09.041 · Cited by 118
Weber, D. R., Leonard, M. B., Justine Shults, A., & Zemel, B. S. (2014) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2014-1684 · Cited by 118
Fujiwara, T., Uotani, K., Yoshida, A., Morita, T., Nezu, Y., Kobayashi, E., Yoshida, A., Uehara, T., Omori, T., Sugiu, K., et al. (2017) · Oncotarget · doi:10.18632/oncotarget.16498 · Cited by 118
Robinson, W. P., Schanzer, A. S., Li, Y., Goodney, P. P., Nolan, B. W., Eslami, M. H., Cronenwett, J. L., & Messina, L. M. (2012) · Journal of Vascular Surgery · doi:10.1016/j.jvs.2012.08.120 · Cited by 117
Wang, C., & Chen, L. (2010) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2010.07.225 · Cited by 117
Moreton, B. J., Tew, V. J., das Nair, R., Wheeler, M., Walsh, D. A., & Lincoln, N. B. (2014) · Arthritis Care & Research · doi:10.1002/acr.22431 · Cited by 116
Skorupska, K. A., Grzybowska, M. E., Kubik-Komar, A., Rechberger, T., & Miotła, P. (2021) · Health and Quality of Life Outcomes · doi:10.1186/s12955-021-01721-z · Cited by 116
Hirajima, S., Komatsu, S., Ichikawa, D., Takeshita, H., Konishi, H., Shiozaki, A., Morimura, R., Tsujiura, M., Nagata, H., Kawaguchi, T., et al. (2013) · British Journal of Cancer · doi:10.1038/bjc.2013.148 · Cited by 116
A method to identify trace sulfated IgG N-glycans as biomarkers for rheumatoid arthritis
Wang, J., Gao, W., Grimm, R., Jiang, S., Liang, Y. Q., Ye, H., Li, Z., Yau, L., Huang, H., Liu, J., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00662-w · Cited by 113
Screening of Urine Samples by Flow Cytometry Reduces the Need for Culture
Jolkkonen, S., Paattiniemi, E.-L., Kärpänoja, P., & Sarkkinen, H. (2010) · Journal of Clinical Microbiology · doi:10.1128/jcm.00617-10 · Cited by 114
A Systematic Review of Diagnostic Biomarkers of COPD Exacerbation
Chen, Y.-W. R., Leung, J. M., & Sin, D. D. (2016) · PLoS ONE · doi:10.1371/journal.pone.0158843 · Cited by 113
Komatsu, S., Ichikawa, D., Hirajima, S., Kawaguchi, T., Miyamae, M., Okajima, W., Ohashi, T., Arita, T., Konishi, H., Shiozaki, A., et al. (2014) · British Journal of Cancer · doi:10.1038/bjc.2014.451 · Cited by 112
Accuracy of Fall Prediction in Parkinson Disease: Six-Month and 12-Month Prospective Analyses
Duncan, R. P., Leddy, A. L., Cavanaugh, J. T., Dibble, L. E., Ellis, T. D., Ford, M. P., Foreman, K. B., & Earhart, G. M. (2011) · Parkinson s Disease · doi:10.1155/2012/237673 · Cited by 110
VIP: an integrated pipeline for metagenomics of virus identification and discovery
Yang, L., Wang, H., Nie, K., Zhang, C., Zhang, Y., Wang, J., Niu, P., & Ma, X. (2016) · Scientific Reports · doi:10.1038/srep23774 · Cited by 109
Reliability and validity of K10 and K6 in screening depressive symptoms in Hong Kong adolescents
Chan, S. M., & Fung, T. W. T. (2013) · Vulnerable Children and Youth Studies · doi:10.1080/17450128.2013.861620 · Cited by 109
Inpatient Walking Activity to Predict Readmission in Older Adults
Fisher, S. R., Graham, J. E., Ottenbacher, K. J., Deer, R., & Ostir, G. V. (2016) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2015.09.029 · Cited by 108
Screening for Prediabetes Using Machine Learning Models
Choi, S. B., Kim, W. J., Yoo, T. K., Park, J. S., Chung, J. W., Lee, Y., Kang, E. S., & Kim, D. W. (2014) · Computational and Mathematical Methods in Medicine · doi:10.1155/2014/618976 · Cited by 115
Physical A ctivity Q uestionnaire for children and adolescents: E nglish norms and cut‐off points
Voss, C., Ogunleye, A. A., & SANDERCOCK, G. R. H. (2013) · Pediatrics International · doi:10.1111/ped.12092 · Cited by 126
Takahashi, M., Shigematsu, Y., Ohta, M., Tokumasu, H., Matsukura, T., & Hirai, T. (2013) · Journal of Thoracic and Cardiovascular Surgery · doi:10.1016/j.jtcvs.2013.08.058 · Cited by 106
Zhou, X., Qiao, Q., Ji, L., Ning, F., Yang, W., Weng, J., Shan, Z., Tian, H., Ji, Q., Lin, L., et al. (2013) · Diabetes Care · doi:10.2337/dc13-0593 · Cited by 104
Hyodo, T., Yada, N., Hori, M., Maenishi, O., Lamb, P., Sasaki, K., Onoda, M., Kudo, M., Mochizuki, T., & Murakami, T. (2017) · Radiology · doi:10.1148/radiol.2017160130 · Cited by 105
CXCL4 and CXCL10 Predict Risk of Fatal Cerebral Malaria
Wilson, N. O., Jain, V., Roberts, C. E., Lucchi, N. W., Joel, P. K., Singh, M. P., Nagpal, A. C., Dash, A. P., Udhayakumar, V., Singh, N., et al. (2011) · Disease Markers · doi:10.1155/2011/828256 · Cited by 104
Jacobs, F. (2011) · Critical Care · doi:10.1186/cc10417 · Cited by 15
Adamzik, M., Eggmann, M., Frey, U., Görlinger, K., Bröcker-Preuss, M., Marggraf, G., Saner, F., Eggebrecht, H., Peters, J., & Hartmann, M. (2010) · Critical Care · doi:10.1186/cc9284 · Cited by 103
Tehrani, F. R., Solaymani–Dodaran, M., & Azizi, F. (2009) · Menopause The Journal of The North American Menopause Society · doi:10.1097/gme.0b013e318193e95d · Cited by 103
Movsessian, A., Cava, D. G., & Tcherniak, D. (2021) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2021.107766 · Cited by 105
Validity of the online PREDICT tool in older patients with breast cancer: a population-based study
de Glas, N. A., Bastiaannet, E., Engels, C. C., de Craen, A. J. M., Putter, H., van de Velde, C. J. �., Hurria, A., Liefers, G., & Portielje, J. E. A. (2016) · British Journal of Cancer · doi:10.1038/bjc.2015.466 · Cited by 102
Novel Use of Pleural Ultrasound Can Identify Malignant Entrapped Lung Prior to Effusion Drainage
Salamonsen, M., Lo, A. K. C., Ng, A. C. T., Bashirzadeh, F., Wang, W. Y. S., & Fielding, D. I. (2014) · CHEST Journal · doi:10.1378/chest.13-2876 · Cited by 101
Measurement and interpretation of skin prick test results
van der Valk, J. P. M., van Wijk, R. G., Hoorn, E. J., Groenendijk, L., Groenendijk, I. M., & de Jong, N. W. (2015) · Clinical and Translational Allergy · doi:10.1186/s13601-016-0092-0 · Cited by 99
Risks and clinical implications of perineural invasion in T1‐2 oral tongue squamous cell carcinoma
Tai, S., Li, W.-Y., Chu, P., Chang, S., Tsai, T.-L., Wang, Y., & Huang, J.-L. (2011) · Head & Neck · doi:10.1002/hed.21846 · Cited by 99
Miyamae, M., Komatsu, S., Ichikawa, D., Kawaguchi, T., Hirajima, S., Okajima, W., Ohashi, T., Imamura, T., Konishi, H., Shiozaki, A., et al. (2015) · British Journal of Cancer · doi:10.1038/bjc.2015.366 · Cited by 101
Early Migration Predicts Aseptic Loosening of Cementless Femoral Stems: A Long-term Study
Streit, M. R., Häussler, D., Bruckner, T. M., Proctor, T., Innmann, M. M., Merle, C., Gotterbarm, T., & Weiss, S. (2016) · Clinical Orthopaedics and Related Research · doi:10.1007/s11999-016-4857-5 · Cited by 98
Metadata
- Authors
- Akobeng, A. K.
- Corresponding author
- Akobeng, Anthony K
- ORCID
- Akobeng, Anthony K
- Venue
- Acta Paediatrica
- Publisher
- Wiley
- Published
- 2007-03-21
- Volume
- 96
- Issue
- 5
- Pages
- 644-647
- ISSN
- 0365-1436 (ISSN-L)
- 0803-5253
- 1651-2227
- OpenAlex
- W2073887351
- Cited by
- 1,882
- References
- 17
- Citations by year
- 2026: 53 · 2025: 95 · 2024: 135 · 2023: 138 · 2022: 167 · 2021: 156 · 2020: 131 · 2019: 116 · 2018: 102 · 2017: 120 · 2016: 113 · 2015: 117 · 2014: 117 · 2013: 98 · 2012: 76
- FWCI
- 29.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Acta Paediatrica (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Health Sciences › Health Professions › Medical Laboratory Technology › Clinical Laboratory Practices and Quality Control
- Keywords
- receiver operating characteristic, diagnostic accuracy, cut-point selection, sensitivity, specificity, Youden index, area under the ROC curve, diagnostic test comparison
- MeSH terms
- C-Reactive Protein, Calcitonin, Humans, Leukocyte Count, Protein Precursors, ROC Curve, Sensitivity and Specificity, Shock, Septic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
