The DOI matches its Crossref record; 39 of the 40 references it cites were found in a registry or an index.
Do observational studies using propensity score methods agree with randomized trials? A systematic comparison of studies on acute coronary syndromes
Open accessAbstract
AIMS: Randomized controlled trials (RCTs) are the gold standard for assessing the efficacy of therapeutic interventions because randomization protects from biases inherent in observational studies. Propensity score (PS) methods, proposed as a potential solution to confounding of the treatment-outcome association, are widely used in observational studies of therapeutic interventions for acute coronary syndromes (ACS). We aimed to systematically assess agreement between observational studies using PS methods and RCTs on therapeutic interventions for ACS. METHODS AND RESULTS: We searched for observational studies of interventions for ACS that used PS methods to estimate treatment effects on short- or long-term mortality. Using a standardized algorithm, we matched observational studies to RCTs based on patients' characteristics, interventions, and outcomes ('topics'), and we compared estimates of treatment effect between the two designs. When multiple observational studies or RCTs were identified for the same topic, we performed a meta-analysis and used the summary relative risk for comparisons. We matched 21 observational studies investigating 17 distinct clinical topics to 63 RCTs (median = 3 RCTs per observational study) for short-term (7 topics) and long-term (10 topics) mortality. Estimates from PS analyses differed statistically significantly from randomized evidence in two instances; however, observational studies reported more extreme beneficial treatment effects compared with RCTs in 13 of 17 instances (P = 0.049). Sensitivity analyses limited to large RCTs, and using alternative meta-analysis models yielded similar results. CONCLUSION: For the treatment of ACS, observational studies using PS methods produce treatment effect estimates that are of more extreme magnitude compared with those from RCTs, although the differences are rarely statistically significant.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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
“Such methods often yield results similar to those in controlled treatment trials (133, 134).”
From Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System (2020) · cites this paper as [133]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Meta-analysis in clinical trials
DerSimonian, R., & Laird, N. (1986) · Controlled Clinical Trials · doi:10.1016/0197-2456(86)90046-2 · Cited by 39,552
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association
Tsao, C. W., Aday, A. W., Almarzooq, Z. I., Anderson, C. A. M., Arora, P., Avery, C. L., Baker-Smith, C. M., Beaton, A. Z., Boehme, A. K., Buxton, A. E., et al. (2023) · Circulation · doi:10.1161/cir.0000000000001123 · Cited by 8,300
Sterne, J. A. C., Sutton, A. J., Ioannidis, J. P. A., Terrin, N., Jones, D. R., Lau, J., Carpenter, J., Rucker, G., Harbord, R. M., Schmid, C. H., et al. (2011) · BMJ · doi:10.1136/bmj.d4002 · Cited by 7,709
Heart Disease and Stroke Statistics—2011 Update: A Report From the American Heart Association
Roger, V. L., Go, A. S., Lloyd-Jones, D. M., Adams, R. J., Berry, J. D., Brown, T. M., Carnethon, M. R., Dai, S., de Simone, G., Ford, E. S., et al. (2011) · Circulation · doi:10.1161/cir.0b013e3182009701 · Cited by 6,149
Braunwald, E., Antman, E. M., Beasley, J. W., Califf, R. M., Cheitlin, M. D., Hochman, J. S., Jones, R. H., Kereiakes, D. J., Kupersmith, J., Levin, T. N., et al. (2000) · Circulation · doi:10.1161/01.cir.102.10.1193 · Cited by 4,475
Randomized, Controlled Trials, Observational Studies, and the Hierarchy of Research Designs
Concato, J., Shah, N., & Horwitz, R. I. (2000) · New England Journal of Medicine · doi:10.1056/nejm200006223422507 · Cited by 3,563
A comparison of observational studies and randomized, controlled trials.
Benson, K., & Hartz, A. J. (2000) · New England Journal of Medicine · doi:10.1056/nejm200006223422506 · Cited by 2,347
What is meant by intention to treat analysis? Survey of published randomised controlled trials
Hollis, S., & Campbell, F. (1999) · BMJ · doi:10.1136/bmj.319.7211.670 · Cited by 2,160
A critical appraisal of propensity‐score matching in the medical literature between 1996 and 2003
Austin, P. C. (2007) · Statistics in Medicine · doi:10.1002/sim.3150 · Cited by 1,249
Flagged first, then by citations
1 of the 40 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- 2002, Observational Studies
Cited by
Sorted by citations
Items 101–200 of 203
Treatment Effects in Randomized and Nonrandomized Studies of Pharmacological Interventions
Salcher‐Konrad, M., Nguyen, M., Savović, J., Higgins, J. P. T., & Naci, H. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.36230 · Cited by 15
Clinical disease registries in acute myocardial infarction
Ashrafi, R. (2014) · World Journal of Cardiology · doi:10.4330/wjc.v6.i6.415 · Cited by 14
Adamus, C., Mötteli, S., Jäger, M., & Richter, D. (2020) · BMC Psychiatry · doi:10.1186/s12888-020-02712-y · Cited by 8
Comparative effectiveness research methodology using secondary data: A starting user’s guide
Sun, M., & Lipsitz, S. R. (2017) · Urologic Oncology Seminars and Original Investigations · doi:10.1016/j.urolonc.2017.10.011 · Cited by 13
Reduced Prevalence of Alcoholic Gastritis in Hospitalized Individuals Who Consume Cannabis
Adejumo, A., Li, J., Akanbi, O. H., Adejumo, K. L., & Bukong, T. N. (2018) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.13930 · Cited by 12
Impact of the matching algorithm on the treatment effect estimate: A neutral comparison study
Heinz, P., Wendel‐Garcia, P. D., & Held, U. (2022) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-223417 · Cited by 12
Hoshino, N., Sakamoto, T., Hida, K., Takahashi, Y., Okada, H., Obama, K., & Nakayama, T. (2021) · BJS Open · doi:10.1093/bjsopen/zraa067 · Cited by 11
Osigwe, P. C., Agomoh, C. E., Osigwe, I. S., & Akumiah, F. K. (2024) · Cureus · doi:10.7759/cureus.63379 · Cited by 11
“RR was directly converted to HR in analyses because, in practical terms, both are similar [65].”
MethodIoannidis, I., Ismail, A. M., Forssten, M. P., Ahl, R., Cao, Y., Borg, T., & Mohseni, S. (2021) · European Journal of Trauma and Emergency Surgery · doi:10.1007/s00068-021-01640-0 · Cited by 11
Longer-term effects of school-based counselling in UK primary schools
Finning, K., White, J., Tóth, K., Golden, S., Meléndez‐Torres, G. J., & Ford, T. J. (2021) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-021-01802-w · Cited by 12
“However, a comparison of results from RCTs and observational studies using propensity scores in the field of cardiovascular disease found that while the magnitude of effects were often more extreme in observational studies, they were rarely different to a statistically significant degree from those reported in RCTs [3…”
ResultLi, J., Rumrill, P. D., Iwanaga, K., Zhang, H., Chan, F., & Strauser, D. (2023) · Journal of Vocational Rehabilitation · doi:10.3233/jvr-230006 · Cited by 10
Yao, M., Wang, Y., Busse, J. W., Briel, M., Mei, F., Li, G., Zou, K., Li, L., & Sun, X. (2023) · BMJ Open · doi:10.1136/bmjopen-2023-073232 · Cited by 11
Dahabreh, I. (2018) · Social Science & Medicine (1967) · doi:10.1016/j.socscimed.2018.05.012 · Cited by 12
Adejumo, A., Ajayi, T. O., Adegbala, O. M., & Bukong, T. N. (2019) · European Journal of Gastroenterology & Hepatology · doi:10.1097/meg.0000000000001382 · Cited by 10
Çelik, M., Milojevic, M., Durko, A. P., Oei, F. B. S., Bogers, A. J. J. C., & Mahtab, E. A. F. (2020) · Interactive Cardiovascular and Thoracic Surgery · doi:10.1093/icvts/ivaa179 · Cited by 10
“icantly different, and consistency is evident [37, 38].”
Li, M., Zhang, B., Chen, Q., Zhang, L., Mo, X., Chen, Z., Jin, Z., Chen, L., You, J., & Zhang, S. (2021) · Head & Neck · doi:10.1002/hed.26664 · Cited by 10
Immortal Time Bias and the Use of IVC Filters
Fernandes, T. M., & White, R. H. R. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2014.04.075 · Cited by 10
Wang, C. H., Tang, D., von Dadelszen, P., Ju, C., Liu, L., Wang, Y., & Magee, L. A. (2026) · BMJ · doi:10.1136/bmj-2025-086810 · Cited by 9
“19 Additionally, we used Bland-Altman plots as a visual measure of consistency.”
Off-pump versus on-pump coronary artery bypass grafting: comparative effectiveness
Raja, S. G. (2015) · Comparative Effectiveness Research · doi:10.2147/cer.s62637 · Cited by 9
“7 Observational studies are often a practical alternative to efficiently obtain estimates of the effectiveness of treatment in nonexperimental, routinecare settings.”
Willems, E., D’Hondt, M., Kingham, T. P., Fuks, D., Choi, G. H., Syn, N. L. X., Sucandy, I., Marino, M. V., Prieto, M., Chong, C. C. N., et al. (2022) · Journal of the American College of Surgeons · doi:10.1097/xcs.0000000000000394 · Cited by 9
Birkhead, J. S., Weston, C. F. M., Timmis, A., & Chen, R. (2014) · European Heart Journal Acute Cardiovascular Care · doi:10.1177/2048872614549733 · Cited by 9
Ke, C., Morgan, S., Smolina, K., Gašević, D., Qian, H., & Khan, N. A. (2017) · BMJ Open · doi:10.1136/bmjopen-2016-013808 · Cited by 9
Hoshino, N., Fukui, Y., Hida, K., & Obama, K. (2020) · Annals of Gastroenterological Surgery · doi:10.1002/ags3.12409 · Cited by 9
Messinger, C. J., Bateman, B. T., & Wanis, K. N. (2025) · Anesthesiology · doi:10.1097/aln.0000000000005308 · Cited by 9
Nichol, G., Dickert, N. W., Moeller, J. E., Hochman, J. S., Facemire, C. S., Adams, K. N., Stone, G. W., Morrow, D. A., Thiele, H., Henry, T. D., et al. (2025) · Journal of the American Heart Association · doi:10.1161/jaha.124.037946 · Cited by 9
“75,76 The risk profile of patients with NSTEMI ACS who consent for enrollment in clinical research appears to differ from those who do not, 77 so preferential enrollment of consenting patients with ACS could yield biased estimates of treatment effect.”
Siudak, Z., Mielecki, W., Dziewierz, A., Rakowski, T., Legutko, J., Bartuś, S., Bryniarski, K. L., Partyka, Ł., & Dudek, D. (2014) · Catheterization and Cardiovascular Interventions · doi:10.1002/ccd.25572 · Cited by 8
“It has been observed that especially for the treatment of ACS, registry studies using propensity score matching methods reveal treatment effects that are of more extreme magnitude than those observed in regular randomized clinical trials (RCT) [19].”
BackgroundCardiac rehabilitation mortality trends: how far from a true picture are we?
Doherty, P., & Rauch, G. (2013) · Heart · doi:10.1136/heartjnl-2012-303365 · Cited by 8
Systemic lupus erythematous and clinical outcomes in peritoneal dialysis
de Moraes, T. P., Massignan, B., Figueiredo, A. E., Barretti, P., Olandoski, M., Kirk, A., & Pecoits‐Filho, R. (2014) · Lupus · doi:10.1177/0961203314555353 · Cited by 7
The European Heart Journal on the move: can scientific publishing be further improved?
Lüscher, T. F., Gersh, B. J., Hindricks, G., Landmesser, U., Nallamothu, B. K., Ruschitzka, F. T., & Wijns, W. C. (2012) · European Heart Journal · doi:10.1093/eurheartj/ehs360 · Cited by 7
Wändell, P. E., Carlsson, A. C., Sundquist, J., Johansson, S., Bottai, M., & Sundquist, K. (2014) · Diabetology & Metabolic Syndrome · doi:10.1186/1758-5996-6-2 · Cited by 7
“The mortality reduction associated with statins was more pronounced compared to a meta-analysis of randomized trials [12], as is commonly the case in observational studies using propensity scores [23].”
BackgroundResultPropensity Score–Based Methods in Comparative Effectiveness Research on Coronary Artery Disease
Ellis, A. G., Trikalinos, T. A., Wessler, B. S., Wong, J. B., & Dahabreh, I. J. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx214 · Cited by 7
“Although such cross-study comparisons can be informative when the compared studies are very carefully matched (95, 96), the data we collected could not support such matching.”
ResultShibao, K., Fujino, Y., Joden, F., Tajima, T., Nagata, J., Sato, N., Fujimoto, K., Shin'ya, M., & Hirata, K. (2020) · World Journal of Surgery · doi:10.1007/s00268-020-05709-6 · Cited by 7
Broman, J., Aarnio, K., But, A., Marinković, I., Rodríguez-Pardo, J., Kaste, M., Tatlisumak, T., & Putaala, J. (2022) · Annals medicus · doi:10.1080/07853890.2022.2089729 · Cited by 5
“Compared with randomized controlled trials, use of the propensity score method may also overestimate the effect, although the differences are suggested to be rarely statistically significant [33].”
MethodWändell, P. E., Carlsson, A. C., Sundquist, J., Johansson, S.-E., Bottai, M., & Sundquist, K. (2014) · Age and Ageing · doi:10.1093/ageing/afu153 · Cited by 7
“age group, cardiovascular co-morbidities (hypertension, CHD, CHF, CVDs and diabetes) and all other prescribed cardiovascular drugs, as well as socio-economic variables (educational level and marital status) [13].”
BackgroundCoscia, C., Oriol, A. J., Quezada, C. A., Muriel, A., Monréal, M., Villén, T., Barbero, E., Chiluiza, D., Yusen, R. D., & Jiménez, D. (2018) · CHEST Journal · doi:10.1016/j.chest.2018.10.016 · Cited by 7
Jiménez, D., Muriel, A., Monréal, M., & Yusen, R. D. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2014.05.046 · Cited by 7
Predictors as well as surrogate and hard endpoints in cardiovascular disease
Lüscher, T. F. (2015) · European Heart Journal · doi:10.1093/eurheartj/ehv327 · Cited by 6
Cannabis use and risk of Clostridioides difficile infection: Analysis of 59,824 hospitalizations
Adejumo, A., & Bukong, T. N. (2019) · Anaerobe · doi:10.1016/j.anaerobe.2019.102095 · Cited by 6
Zubizarreta, J. R., Umhau, J. C., Deuster, P. A., Brenner, L. A., King, A. J., Petukhova, M. V., Sampson, N. A., Tizenberg, B., Upadhyaya, S. K., RachBeisel, J. A., et al. (2021) · International Journal of Methods in Psychiatric Research · doi:10.1002/mpr.1897 · Cited by 5
“It has been shown that analyses of such balanced databases often yield aggregate results very similar to those obtained in experimental trials (Anglemyer et al., 2014; Dahabreh et al., 2012).”
ResultCano, S., Mantovani, L. G., Folkerts, K., Gebel, M., Şahin, K., Zell, E. R., Monje, D., Schneider, J., van Eickels, M., Haas, S. K., et al. (2018) · TH Open · doi:10.1055/s-0038-1641679 · Cited by 6
“12,13 Matchedpairs based onthe propensityscores were created using the greedy algorithm.”
Chegondi, M., Devarashetty, S., Balakumar, N., Sendi, P. R., & Totapally, B. (2020) · Pediatric Nephrology · doi:10.1007/s00467-020-04703-3 · Cited by 6
“Although, there have been inconsistencies in the ability of propensity scoring to estimate treatment effects, with some studies showing propensity scoring to both over and underestimate treatment effects [31, 32], the findings of propensity score studies are generally in-line with those from randomized controlled tria…”
ResultCrandell, I., Rockwell, M. S., Whitehead, P. B., CARTER, K. F., & Hanlon, A. L. (2021) · Journal of the American Nutrition Association · doi:10.1080/07315724.2021.1948932 · Cited by 6
Kitsios, G. D. (2014) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2014.10.012 · Cited by 6
Hypoxia-associated genes predicting future risk of myocardial infarction: a GEO database-based study
Li, S., Zhang, J., Ni, J., & Cao, J. (2023) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2023.1068782 · Cited by 5
“ACS is the most serious medical emergency caused by myocardial ischemia/hypoxia following coronary atherosclerotic plaque formation, with clinical manifestations of UA and acute MI (45).”
BackgroundMorfaw, F., Miregwa, B., Ayaba, B., Mbuagbaw, L. C. E., Anderson, L. N., & Thabane, L. (2021) · Journal of Evidence-Based Medicine · doi:10.1111/jebm.12440 · Cited by 5
Otsuka, R., Hayashi, H., Uesato, M., Hayano, K., Murakami, K., Kano, M., Toyozumi, T., Suito, H., Matsumoto, Y., Isozaki, T., et al. (2022) · Langenbeck s Archives of Surgery · doi:10.1007/s00423-022-02454-3 · Cited by 5
“In addition, it has been reported that observational studies such as case-matched studies and cohort studies may overestimate treatment effects [44].”
BackgroundEffect of cardiovascular drugs on mortality in atrial fibrillation and chronic heart failure
Wändell, P. E., Carlsson, A. C., Sundquist, J., Johansson, S., Bottai, M., & Sundquist, K. (2014) · Scandinavian Cardiovascular Journal · doi:10.3109/14017431.2014.941002 · Cited by 5
Zhang, K., Cao, L., Xuan, N., Huang, T., Tian, B., Cui, W., Zhang, G., & Zhang, S. (2022) · Journal of Intensive Medicine · doi:10.1016/j.jointm.2022.05.004 · Cited by 5
Ghotbi, J., Aghayan, D. L., Fretland, Å. A., Edwin, B., Syn, N. L. X., Cipriani, F., Alzoubi, M., Lim, C., Scatton, O., Long, T. C. D., et al. (2023) · European Journal of Surgical Oncology · doi:10.1016/j.ejso.2023.01.014 · Cited by 5
‘Known unknowns and unknown unknowns': electroencephalographic burst suppression and mortality
Short, T. G., & Leslie, K. (2014) · British Journal of Anaesthesia · doi:10.1093/bja/aeu147 · Cited by 5
Symptomatic Low-Gradient Severe Aortic Stenosis With Preserved Left Ventricular Ejection Fraction
Wiegers, S. E. (2013) · Circulation · doi:10.1161/circulationaha.113.004193 · Cited by 5
Natori, T., Komiyama, K., Sonoda, K., Utsunomiya, T., Fujimura, K., Jinbayashi, H., Kabayama, H., Miura, T., Hamasaki, A., Kai, Y., et al. (2022) · Journal of the American Geriatrics Society · doi:10.1111/jgs.18058 · Cited by 4
“Age and sex were entered as the covariates in the propensity scores.(3) Fischer's exact probability test and the t-test were used.”
MethodA Two‐Step Framework for Validating Causal Effect Estimates
Shen, L., Visser, E., van Erning, F. N., Geleijnse, G., & Kaptein, M. C. (2024) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.5873 · Cited by 3
Li, J., Rumrill, P. D., Iwanaga, K., Zhang, H., Chan, F. H., & Strauser, D. G. (2025) · Journal of Vocational Rehabilitation · doi:10.1177/10522263241310033 · Cited by 3
“To strengthen causal inference, the study utilized propensity score matching (PSM) technique to create matched samples of state VR consumers who received college or university training (the treatment group) and those who did not (the comparison group; Dahabreh et al., 2012; Rosenbaum & Rubin, 1983).”
Gómez-Rice, A., Núñez-Pereira, S., Haddad, S., Raganato, R., Charles, Y. P., Pérez-Grueso, F., Kleinstück, F. S., Obeid, I., Alanay, A., Pellisé, F., et al. (2025) · European Journal of Orthopaedic Surgery & Traumatology · doi:10.1007/s00590-025-04215-6 · Cited by 3
Luthra, S., & Taggart, D. P. (2015) · Expert Review of Cardiovascular Therapy · doi:10.1586/14779072.2016.1125291 · Cited by 3
“ferences except that PSA studies overestimated treatment effects.[30,31] Selective reporting of only positive studies and publication bias prejudice observational data to account for this overestimation as RCTs with even small”
BackgroundGuo, G., Sun, M., Li, Y., Yang, W., Wang, X., Yu, Z., Li, C., Hui, Y., Fan, X., Jiang, K., et al. (2022) · Laboratory Medicine · doi:10.1093/labmed/lmac064 · Cited by 3
Score de propension : intérêts, utilisation et limites. Un guide pratique pour le clinicien
Moulis, G., & Lapeyre‐Mestre, M. (2018) · La Revue de Médecine Interne · doi:10.1016/j.revmed.2018.02.012 · Cited by 3
“[2] Dahabreh IJ, Sheldrick RC, Paulus JK, Chung M, Varvarigou V, Jafri H, et al.”
MethodPasupathy, S., Tavella, R., & Beltrame, J. F. (2018) · Circulation · doi:10.1161/circulationaha.117.032512 · Cited by 3
Hoogteijling, T. J., Hilal, M. A., Zimmitti, G., Aghayan, D. L., Wu, A. G. R., Cipriani, F., Gruttadauria, S., Scatton, O., Long, T. C. D., Herman, P., et al. (2024) · European Journal of Surgical Oncology · doi:10.1016/j.ejso.2024.108309 · Cited by 2
Zhang, X., Xu, J., He, Q., Wang, Y., Xie, S., Zhang, X., Zou, K., Wang, W., & Sun, X. (2025) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2025.111936 · Cited by 2
Satti, S. R., Fan, X., Kottenmeier, E., Khanna, R., & Rai, A. (2022) · Interventional Neuroradiology · doi:10.1177/15910199221103325 · Cited by 2
“19 The patient population in this study only represents bAVM patients who received healthcare services from hospitals which provided data to PHD.”
BackgroundLi, G., Qi, X., Tan, X., Wu, M., Wang, H., Wen, P., Huang, X., & Li, Y. (2022) · Frontiers in Pediatrics · doi:10.3389/fped.2022.1022291 · Cited by 2
“Many studies have reported that PSM produces results similar to those of RCTs (9).”
ResultGómez-Rice, A., Capdevila-Bayo, M., Núñez-Pereira, S., Haddad, S., Pérez-Grueso, F., Kleinstück, F. S., Obeid, I., Alanay, A., Pellisé, F., Pizones, J., et al. (2024) · Spine Deformity · doi:10.1007/s43390-024-00821-2 · Cited by 2
“To address potential confounding variables [29] and ensure alignment with effect measures from randomized clinical trials [30], we employed propensity index matching.”
Paulmani, G. (2017) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt.2017.88 · Cited by 2
“To prevent this, Propensity Score Analysis (PSA) is proposed a method used in medical field and economic policy making most often to address the same ethical concern [12].”
MethodLin, C., Chang, Y., Chi, N., Chuang, M., & Chien, L. (2018) · EuroIntervention · doi:10.4244/eij-d-16-00840 · Cited by 2
Lee, C., & So, C. H. (2020) · Chonnam Medical Journal · doi:10.4068/cmj.2020.56.2.130 · Cited by 2
Gilyarevsky, S. R. (2021) · Rational Pharmacotherapy in Cardiology · doi:10.20996/1819-6446-2021-08-01 · Cited by 2
Freemantle, N., & Pagano, D. (2018) · European Journal of Cardio-Thoracic Surgery · doi:10.1093/ejcts/ezy120 · Cited by 2
Gautier, A., Roffi, M., Laanmets, P., Munir, S. M., Malik, F. T., Íñiguez, A., Maluenda, G., Kuramitsu, S., Angioı̈, M., Wijns, W. C., et al. (2023) · American Heart Journal · doi:10.1016/j.ahj.2023.02.016 · Cited by 1
Diverse criteria and methods are used to compare treatment effect estimates: a scoping review
Brignardello‐Petersen, R., Carrasco‐Labra, A., Jadad, A. R., Johnston, B. C., & TOMLINSON, G. A. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2016.02.001 · Cited by 1
Guh, S., Grosse, S. D., Ullman, M. M., & Soucie, J. M. (2017) · Haemophilia · doi:10.1111/hae.13161 · Cited by 1
Ethical Considerations for Conducting a Randomized Controlled Trial in Transport
Reimer, A. P., & Daly, B. J. (2014) · Air Medical Journal · doi:10.1016/j.amj.2014.06.009 · Cited by 1
Chen, X., Sun, L. V., Chen, Q., Kojodjojo, P., Chen, H., Ju, W., Zhu, W., Zhu, Y., Zhao, P., Zhang, F., et al. (2020) · Pacing and Clinical Electrophysiology · doi:10.1111/pace.13935 · Cited by 1
Signals were broadly positive for months, but never definitive: the tocilizumab story
Cozzi‐Lepri, A., Smith, C. J., & Mussini, C. (2021) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2021.10.018 · Cited by 1
Cucchetti, A., & Serenari, M. (2017) · HepatoBiliary Surgery and Nutrition · doi:10.21037/hbsn.2017.05.03 · Cited by 1
Should Network Meta-analysis Become the Standard in Evidence-based Clinical Practice?
Brignardello‐Petersen, R. (2016) · TSpace (University of Toronto) · Cited by 1
The Rise of Comparative Effectiveness Research
Hochman, M. E., & McCormick, D. (2013) · Springer eBooks · doi:10.1007/978-1-4614-7735-8_7
“While concerns persist about the ability of even these newer techniques to properly control for confounding factors [ 22 ], some evidence suggests that observational study results are valid most of the time [ 23 ].”
BackgroundCan a Mendelian Randomization Study Predict the Results of a Clinical Trial? Yes and No
Abbate, A., Dinarello, C. A., Peruzzi, M., Sciarretta, S., Frati, G., & Biondi‐Zoccai, G. (2016) · International Journal of Statistics in Medical Research · doi:10.6000/1929-6029.2016.05.01.6
“From stratification to logistic regression and propensity score matching, traditional adjustment methods have become more and more refined, and in many cases carefully conducted and analyzed observational studies appear to agree with the corresponding megatrials [11].”
Hui, D. S., & Lee, R. (2016) · Journal of Thoracic and Cardiovascular Surgery · doi:10.1016/j.jtcvs.2016.09.031
Uso de estatinas em pacientes com doença isquêmica do coração: análise de custo-efetividade
Luque, A. (2016) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.5.2017.tde-06032017-102120
Habib, A. M., Hussain, A., Jarvis, M., Cale, A. R., Cowen, M. E., Ngaage, D. L., Chaudhry, M., & Loubani, M. (2018) · World Journal of Cardiovascular Surgery · doi:10.4236/wjcs.2018.82005
“Nevertheless, PSM has been assessed by other studies to validate the effect of treatment on observational data [7] [19] [20].”
MethodResult俊彦, 真., 瑠里, 首., 明日実, 椎., 直哉, 舛., 直通, 岡., 直人, 佐., 悠人, 手., 真志, 草., 倫太郎, 秋., 一平, 宮., et al. (2018) · 日本外科感染症学会雑誌 · doi:10.24679/gekakansen.15.3_242
Doherty, P., Harrison, A., Petre, C., & Onion, N. (2020) · doi:10.1002/9781119071006.ch9
Cozzi‐Lepri, A., Guaraldi, G., Meschiari, M., & Mussini, C. (2021) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2021.04.026
“, is to compare its results with those of the reference randomized trial [5,7,8].”
ResultRaman, N., Kishore, K., Rana, S., Vardhan, V., Thareja, S., Padmaprakash, K. V., Muthukrishnan, J., Rajmohan, K., Agarwal, M., Ashta, K. K., et al. (2022) · The Journal of Association of Chest Physicians · doi:10.4103/jacp.jacp_44_21
Ishizu, K., Hamai, S., Tsushima, H., Harada, T., Harada, S., Kameyama, M., Kawahara, S., Akasaki, Y., & Nakashima, Y. (2026) · Journal of Orthopaedic Reports · doi:10.1016/j.jorep.2026.100995
Drew, C. J. G., & Busse, M. E. (2022) · International review of neurobiology · doi:10.1016/bs.irn.2022.09.006 · Cited by 1
Min, S., Kim, J. S., Kim, J. Y., Park, U. J., Lee, T., Kang, J. M., Park, S. C., Choi, W.-I., Park, K. H., & Gebel, M. (2022) · Vascular Specialist International · doi:10.5758/vsi.220039
Lecuona, O. Z., Angulo-Brunet, A., Ciudad-Fernández, V., & Olmos, R. (2023) · doi:10.31234/osf.io/bpk5h
Buka, R. J., Sutton, D. J., & Nicolson, P. L. R. (2024) · Journal of Thrombosis and Thrombolysis · doi:10.1007/s11239-024-02948-5
“While it can remove most bias in some minor or medium confounding scenarios it is particularly unreliable in situations with complex or unmeasured confounding [4, 5].”
Antidepressant Remission and Manic Switch in Bipolar Depression: A Propensity Score Analysis
Vöhringer, P. A., Barroilhet, S. A., Palma, B. A., & Perlis, R. H. (2025) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13822
“While large randomized controlled trials remain the gold standard, comparing treatment effect estimators drawn from this statistical procedure with outcomes from randomized data shows that the results may be quite close to each other [22].”
Koinuma, T., & Akazawa, M. (2025) · Pragmatic and Observational Research · doi:10.2147/por.s517514
“37 In this study, the Prevalent New User Design was used as an effective method to control for ITB.”
Alves‐Cabratosa, L., López, C., García-Gil, M., Tornabell‐Noguera, È., Comas‐Cufí, M., Blanch, J., Martí‐Lluch, R., Ponjoan, A., Domínguez‐Armengol, G., Zacarías‐Pons, L., et al. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14165710
“However, this type of observational studies could tend to overestimate the effect size of certain interventions [37] if several key points are not well addressed.”
Hong, Y. D., Jansen, J. P., Guerino, J., Berger, M. L., Crown, W. H., Goettsch, W., Mullins, C. D., Willke, R. J., & Orsini, L. S. (2021) · Figshare · doi:10.6084/m9.figshare.17127300
Hong, Y. D., Jansen, J. P., Guerino, J., Berger, M. L., Crown, W. H., Goettsch, W., Mullins, C. D., Willke, R. J., & Orsini, L. S. (2021) · Figshare · doi:10.6084/m9.figshare.17127303
Hong, Y. D., Jansen, J. P., Guerino, J., Berger, M. L., Crown, W. H., Goettsch, W., Mullins, C. D., Willke, R. J., & Orsini, L. S. (2021) · Figshare · doi:10.6084/m9.figshare.17127306
Yang, Y., Peng, Y., Li, J., Cheng, W., Liang, X., Zhang, Q., Wang, X., Wang, Q., Cao, J., Cao, L., et al. (2025) · Surgical Endoscopy · doi:10.1007/s00464-025-12443-4
Metadata
- Authors
- Dahabreh, I. J., Sheldrick, R. C., Paulus, J. K., Chung, M., Varvarigou, V., Jafri, H., Rassen, J. A., Trikalinos, T. A., & Kitsios, G. D.
- Affiliations
- Tufts Medical Center (US)
- Tufts University (US)
- Harvard University (US)
- Johns Hopkins University (US)
- Brigham and Women's Hospital (US)
- Lahey Hospital and Medical Center (US)
- Corresponding author
- Dahabreh, Issa J.
- ORCID
- Venue
- European Heart Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-06-17
- Volume
- 33
- Issue
- 15
- Pages
- 1893-1901
- ISSN
- 0195-668X (ISSN-L)
- 1522-9645
- PMC
- PMC3409422
- OpenAlex
- W2162409127
- Cited by
- 204
- References
- 40
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 10 · 2023: 10 · 2022: 23 · 2021: 22 · 2020: 18 · 2019: 14 · 2018: 18 · 2017: 15 · 2016: 12 · 2015: 13 · 2014: 24 · 2013: 10 · 2012: 2
- FWCI
- 14.97
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- European Heart Journal (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Center for Research Resources (UL1RR025752)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- propensity score methods, acute coronary syndrome, observational studies, randomized controlled trials, treatment effect estimation, confounding, mortality
- MeSH terms
- Humans, Regression Analysis, Risk Factors, Reproducibility of Results, Randomized Controlled Trials as Topic, Treatment Outcome, Acute Coronary Syndrome, Propensity Score
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