Register studies from the perspective of a clinical scientist

Transcription

1 Register stdies from the perspective of a clinical scientist Sofia Sederholm Lawesson, MD, PhD Department of Cardiology, Linköping University Hospital and Department of Medical and Health Sciences, Linköping University

2 Register stdies todays scedle What is a register stdy? Some examples from PbMed Prospective vs retrospective stdies Cohort vs case-control stdies Observational vs experimental design and the hierarchical pyramid Definition of SBU RCTs vs register stdies Hypothesis generating vs hypothesis testing Advantages and disadvantages When is a register stdy design most sitable? Different types of registers In general In Sweden Core qestions when doing/analyzing register stdies Target poplation Grop for comparison Confonding and effect modification How to handle differences in baseline characteristics How to handle missing data Ethic considerations

3 Register stdy what is that??

4 Pbmed, example nr 1 Nrs Open 2015 Nov 3;3(2): Factors associated with older people's independent living from the viewpoint of health and fnctional capacity: a register-based stdy. Aim: to identify factors associated with independent living of older people from the point of view of health and fnctional capacity. DESIGN: Descriptive, cross-sectional register-based stdy METHODS: Data were collected sing the Health and Fnctional Capacity srvey by identifying the factors of health examinations of a cohort (N = 292) of 75-year old's (N = 388), in one Finnish medim-sized mnicipality. The data were analysed statistically by sing descriptive analysis, cross-tablation and logistic regression.

5 Pbmed, example nr 2 Infect Dis (Lond) Oct 4:1-8. Opioid and amphetamine dependence is associated with methicillinresistant Staphylococcs ares (MRSA): An epidemiological register stdy with Swedish in- and otpatients In this retrospective, longitdinal register stdy, we investigated MRSA epidemiology in opioid and amphetamine-dependent individals, in comparison with alcohol-dependent sbjects. METHODS: Data from the national Swedish in- and otpatients registers inclded individals from 1997, 1999, 2004, 2009 and We analyzed sbstance se disorder and demographic predictors for MRSA sing generalized estimating eqations.

6 Pbmed, example nr 3 Circ J Sep 29. Efficacy and Safety of Rivaroxaban and Warfarin in the Perioperative Period of Catheter Ablation for Atrial Fibrillation - Otcome Analysis From a Prospective Mlticenter Registry Stdy in Japan. Catheter ablation (CA) is a common treatment for atrial fibrillation (AF). Althogh rivaroxaban is increasingly sed as a sbstitte for warfarin, its safety and efficacy dring CA have not been established in Japanese patients. Methods and Reslts: We prospectively enrolled Japanese AF patients schedled for CA who had received either rivaroxaban (rivaroxaban cohort, JACRE-R) or warfarin (warfarin cohort, JACRE-W) dring the perioperative period. Primary otcome was a composite of thromboembolism and major bleeding within 30 days after CA. After adjstment for patients' characteristics, no significant difference was observed between the JACRE-R and JACRE-W cohorts for the primary otcome.

7 Pbmed, example nr 4 Acta Obstet Gynecol Scand Oct 3. doi: /aogs Maternal and fetal characteristics affect discrepancies between pregnancy dating methods: a poplation-based cross-sectional register stdy. Aim: to identify characteristics associated with discrepancies between last menstral period-based (EDD-LMP) and ltrasond-based (EDD-US) estimated delivery dates. MATERIAL AND METHODS: We identified all singleton births (n= ) recorded in the Swedish Medical Birth Register , to assess the association between maternal/fetal characteristics and large negative and large positive discrepancies. Analyses were adjsted for age, parity, height, body mass index, smoking, and employment stats.

8 Pbmed, example 5 JMIR Res Protoc Sep 27;5(3):e191. doi: /resprot Dementia and Traffic Accidents: A Danish Register-Based Cohort Stdy. OBJECTIVE: Or stdy aims to investigate the risk of road traffic-related accidents for people aged 65 years or older with a diagnosis of dementia in Denmark. METHODS: We will condct a nationwide poplation-based cohort stdy consisting of Danish people aged 65 or older living in Denmark as of Janary 1, The cohort is followed for 7 years ( ). Individal's personal data are available in Danish registers and can be linked sing a niqe personal identification nmber. Police-, hospital-, and emergency roomreported road traffic-related accidents occrred within the stdy follow-p are defined as the stdy otcome. Cox proportional hazard regression models are sed for the main analysis.

9 Pbmed, example 6 PLoS One Sep 9;11(9):e Pre-Vaccination Care-Seeking in Females Reporting Severe Adverse Reactions to HPV Vaccine. A Registry Based Case-Control Stdy BACKGROUND: The aim of the present stdy was to determine health care-seeking prior to the first HPV vaccination among females who sspected adverse reactions to HPV vaccine. METHODS: We inclded as cases vaccinated females with reports to the DMA of sspected severe adverse reactions. We selected controls withot reports of adverse reactions from the Danish vaccination registry and matched by year of vaccination, age of vaccination, and mnicipality, and obtained from the Danish National Patient Registry and The National Health Insrance Service Register the history of health care sage two years prior to the first vaccine. We analysed the data by logistic regression while adjsting for the matching variables.

10 Pbmed, example 7 Thrombs Aspiration in ST-Elevation myocardial infarction in Scandinavia (TASTE trial). A mlticenter, prospective, randomized, controlled clinical registry trial based on the Swedish angiography and angioplasty registry (SCAAR) platform. N Engl J Med Oct 24;369(17): doi: /NEJMoa Thrombs aspiration dring ST-segment elevation myocardial infarction. We aimed to evalate whether thrombs aspiration redces mortality. METHODS: We condcted a mlticenter, prospective, randomized, controlled, openlabel clinical trial, with enrollment of patients from the national comprehensive Swedish Coronary Angiography and Angioplasty Registry (SCAAR) and end points evalated throgh national registries. A total of 7244 patients with STEMI ndergoing PCI were randomly assigned to manal thrombs aspiration followed by PCI or to PCI only. The primary end point was all-case mortality at 30 days.

11 Ths we fond. A descriptive, cross-sectional register-based stdy A retrospective, longitdinal register stdy A nationwide poplation-based cohort stdy A poplation-based cross-sectional register stdy A prospective mlticenter registry stdy A registry based case-control stdy A mlticenter, prospective, randomized, controlled clinical registry trial

12 Prospective and Retrospective Prospective stdies are designed to gather data abot events that haven't happened yet; they look forward in time. Retrospective stdies are designed to gather data abot events that have already happened; they look backward in time. Registry stdies can be either prospective, retrospective, or both. If yo abstract data from existing medical records, those data are retrospective. Bt yo might also want to follow those patients into the ftre, reqesting specific data be obtained at ftre follow-p visits; these data are prospective.

13 Cohort vs. Case-Control An observational epidemiologic stdy wherein exposed and nexposed sbjects are observed ntil they develop an otcome of interest. The exposed and the non exposed cold ths be compared as regards development of the disease in interest.

14 Cohort vs. Case-Control An observational epidemiological stdy of persons with the disease of interest and a sitable control grop of persons withot the disease = comparison grop.the potential relationship of a sspected risk factor to the disease is examined by comparing the diseased and nondiseased sbjects with regard to how freqently the risk factor is present in each of the grops. For example, in a stdy trying to show smokers (the risk factor) are more likely to be diagnosed with lng cancer (the otcome), the cases wold be persons with lng cancer, the controls wold be persons withot lng cancer (not necessarily healthy), and some of each grop wold be smokers. If a larger proportion of the cases smoke than the controls, that sggests, bt does not conclsively show, that the hypothesis is valid.

15 Strength of evidence for casality between a risk factor and otcome Yotbe videos (even if yor kids tell yo so), personal anecdotes, parental instincts, gt feelings, TV news, Expressen, news from all kind of websites, some gy yo know, etc.

16 Observational vs experimental design RRCT

17 Register stdies what is that?? Registerstdie - enl SBUs ordlista: retrospektiv (eller kombinerat retro- och prospektiv) ndersökning som gör brk av data som finns i offentlig statistik, i medicinska databaser m.m.

18 RCT - hypothesis testing Ref: LT nr 8

19 Register stdy hypotheses generating Ref: LT nr 8

20 Different interpretations of the reslt.. Ref: LT nr 8

21 RCT planned after reslts from the register stdy Yo can test: 1) The hypotheses that there is no difference in srgical sccess/reslts 2) The hypotheses that there is no difference in selection of patients sitable for srgery 3) The hypothesis that the srgical sccess rate at one department is the same regardless if the patients were selected at this or the other department from the beginning. Ref: LT nr 8

22 Register stdies compared to RCTs In a RCT yo can test the hypothesis that therapy A is better than therapy B. If a significant difference is fond yo have a casal relationship. The pitfall is that this is applicable for the grop that was inclded in the RCT. Often this grop does not represent the real world poplation. Expensive! Limited nmber of inclsion. Limited length of follow-p. A register stdy is spposed to mirror the real world poplation. Informed consent is not needed to be inclded in national qality registers. When comparing different therapies or grops within a register there are several pitfalls. A casal relationship cannot be assmed. The reason to choice a certain therapy may differ between grops. There may be confonding factors i.e. other factors that affects the measred otcome and that differ in prevalence between grop.

23 Registry-based stdies vs RCTs In many sitations, nonrandomized comparisons either are sfficient to address the research qestion or, in some cases, may be necessary becase of the following isses with randomizing patients to a specific treatment: Eqipoise: Can providers ethically introdce randomization between treatments when the treatments may not be clinically eqivalent? Ethics: If reasonable sspicion abot the safety of a prodct has become known, wold it be ethical to condct a trial that deliberately exposes patients to potential harm? Practicality: Will patients enroll in a stdy where they might not receive the treatment, or might not receive what is likely to be the best treatment? How can compliance and adherence to a treatment be stdied, if not by observing what people do in real-world sitations?

24 Registries are particlarly sitable for some types of research qestions, sch as: Natral history stdies - the goal is to observe clinical practice and patient experience bt not to introdce any intervention. Measres of clinical effectiveness -where the prpose is to learn abot what patients and practitioners actally do and how their actions affect real-world otcomes. This is especially important for treatments that have poor compliance. Stdies of effectiveness and safety for which clinician training and techniqe are part of the stdy of the treatment (e.g., a procedre sch as placement of carotid stent). Stdies of heterogeneos patient poplations, since nlike randomized trials, registries generally have mch broader inclsion criteria and fewer exclsion criteria. These characteristics lead to stdies with greater generalizability (external validity) and may allow for assessment of sbgrop differences in treatment effects. Follow-p for delayed or long-term benefits or harm, since registries can extend over mch longer periods than most clinical trials (becase of their generally lower costs to rn and lesser brden on participants). Srveillance for rare events or of rare diseases.

25 Registries are also sitable for some types of research qestions, sch as: Stdies for treatments in which randomization is nethical, sch as intentional exposre to potential harm (as in safety stdies of marketed prodcts that are sspected of being harmfl). Stdies for treatments in which randomization is not possible, sch as when certain therapies are only available in certain places owing to high cost or other restrictions (e.g. proton beam therapy). Stdies for which blinding is challenging or nethical (e.g. stdies of srgical interventions, acpnctre). Stdies of rapidly changing technology. Stdies of conditions with complex treatment patterns and treatment combinations. Stdies of health care access and barriers to care. Evalations of actal standard medical practice.

26 Types of registries Registries shold be designed and evalated with respect to their intended prposes. Registry prposes can be broadly described in terms of patient otcomes. (1) describing the natral history of disease (2) determining clinical and/or cost-effectiveness (3) assessing safety or harm (4) measring or improving qality of care

27 Poplation registers (Befolkningsregister) By the cortesy of J Lyth, FoU-enheten, RÖ

28 Statistics Sweden (Statistiska central byrån) By the cortesy of J Lyth, FoU-enheten, RÖ

29 National Board of Health and Wellfare (Socialstyrelsen) By the cortesy of J Lyth, FoU-enheten, RÖ

30 The National Board of Health and Wellfares (Socialstyrelsen) Registers By the cortesy of J Lyth, FoU-enheten, RÖ

31 (Medical) National Qality Registers By the cortesy of J Lyth, FoU-enheten, RÖ

32 The prposes differ between the registers of the National Board of Health/SCB and Welfare and the National Qality Registers By the cortesy of J Lyth, FoU-enheten, RÖ

33 (Medical) National Qality Registers By the cortesy of J Lyth, FoU-enheten, RÖ

34 Local RÖ data and the connection to the national registers By the cortesy of J Lyth, FoU-enheten, RÖ

35 Local RÖ data and the connection to the national registers By the cortesy of J Lyth, FoU-enheten, RÖ

36 What to think abot when analysing or doing a register stdy?

37 Strength Uniqe personal code An opportnity to merge different registers No selection bias, real world poplation Rare otcomes cold be stdied

38 Limitations Missing vales Differences in baseline characteristics Hidden bias

39 Planning a register stdy First, yo'll need to determine how closely the actal stdy poplation represents the target poplation. Second, there shold exist a statistical analysis plan for how the data are to be analyzed and interpreted. Third, there shold exist a plan for how to handle missing data.

40 Analysis and interpretation of register data begin with a series of core qestions: Stdy prpose: Were the objectives/hypotheses predefined or post hoc? Patient poplation: Who was stdied? Data qality: How were the data collected, reviewed, and verified? Data completeness: How were missing data handled? Data analysis: How were the analyses chosen and performed?

41 The Finally, extent reason target the to poplation for analytic which sing the poplation an is intended actal defined poplation incldes by the stdy's all is those representative rather prpose. than of the patients the whole intended who accessible meet poplation the poplation criteria is generally for for analysis. the a stdy matter is of simply real-world matter To assess accessible isses of the convenience that appropriateness poplation prevent and the is practicality. defined initial of the inclsion sing target The inclsion poplation, isses of stdy to The criteria sbjects consider one mst and or in ask adeqate exclsion assessing the qestion, follow-p. how criteria. well Is the this For intended really example, the poplation if a new drg is represents that approved we need the for to reimbrsement accessible know abot? poplation only For example, for are patients similar the who to target those have The failed for poplation assessing inclsion treatment for criteria how a registry well with define the other of accessible oral the anti-inflammatory poplation contraceptive poplation that sers will prodcts, be sed the represents wold reslting for inclde the the stdy actal women target and poplation. generally of childbearing will inclde The systematically age main geographic who difference cold (e.g. is hospitals different that become the or pregnant from intended clinics the target in and poplation a are certain poplation seeking may region), be to of prevent specified demographic, potential pregnancy. by antiinflammatory sampling scheme, drg and sers. which temporal often (e.g. tries specification to strike a balance of the a disease-specific, inclded among representativeness, dates of hospital or convenience, clinic admission), and bdget. as well as other criteria.

42 Selecting sbjects and comparison grops The target poplation is all the patients with a common disease or condition or a common exposre. Then broad inclsion/exclsion criteria are sed to select a representative poplation of patients, ths enhancing their applicability to broader poplations. Selecting comparison grops is more critical in observational stdies than in clinical stdies, becase the intervention is not randomized. Key demographic factors sch as age, lifestyle, and disease advancement are collected and statistically applied to help achieve eqipoise. Comparison grops are essential when yo want to distingish between alternative procedres, assess the magnitde of differences, or determine the strength of associations between grops. Comparison grops may be "internal" (data collected simltaneosly), "external" (data were collected otside of the registry), or "historical" (data collected nder the registry protocol bt not simltaneosly). Registries do not need comparison grops when the prpose is to characterize the "natral history" of an intervention.

43 Confonding

44 Confonding

45 Confonding Randomization is an attempt to evenly distribte potential (nknown) confonders in stdy grops. Anyway, it does not garantee control of confonding. Matching is another way of achieving the same. It ensres eqal representation of sbjects with known confonders in stdy grops. It has to be copled with matched analyses. Restriction for potential confonders in stdy design also prevents confonding bt cases loss of statistical power.

46 Confonding Randomization, matching and restriction something yo do when designing a stdy in order to redce the risk of confonding Stratification or mltivariable adjstments when analyzing the data

47 Confonder vs effect modifier Effect modification occrs when an exposre has a different effect among different sbgrops. It is associated with the otcome bt not the exposre. Effect Modification is not a nisance, it provides important information. The magnitde of the effect of an exposre on an otcome will vary according to the presence of a third factor. For example, imagine yo are testing ot a new treatment that has come onto the market, Drg X. If Drg X works in females bt does not work in males, this is an example of effect modification. Confonding occrs when a factor is associated with both the exposre and the otcome bt does not lie on the casative pathway. Confonding factors are a nisance and can accont for all or part of an apparent association between an exposre and a disease and need to be eliminated/controlled for to prevent distortion of reslts. For example, if yo look for an association between coffee and lng cancer, this association may be distorted by smoking if smokers are nevenly distribted between the two grops. It may appear that there is an association between coffee and lng cancer, however if yo were to consider smokers and non-smokers separately for each grop this wold in fact show no association.

48 Effect modifier So what is an effect modifier? Different relationship between exposre and disease in sbgrops. How d yo look for it? Stratify the data and Compare stratm-specific association measres against one another What do yo do abot it? Report stratm-specific association measres and ignore the crde association measre

49 Confonding 1) Divide cohort in coffee and noncoffee drinkers 2) Explore the risk of smoking as regards CVD risk OR in coffee drinker 1.8 OR in non coffee drinkers 1.8 Smoking CVD OR 1.8 Smoking CVD OR 2.5 Effect modifier Smoking CVD OR 1.1

50 Calclate crde RR, OR Stratify and calclate stratmspecific RR, OR Calclate crde RR, OR Stratm-specific RR, OR are similar Calclate No crde effect RR, modification. OR Calclate pooled RR, OR Stratm-specific RR, OR are different Effect modification Crde RR, OR = Adjsted RR, OR. No major confonding. Crde RR, OR Adjsted RR, OR. Confonding present. Use stratm-specific RR, OR Use crde RR, OR Use adjsted RR, OR

51 To smmarize

52 How to handle differences between grops for comparision?

53 An example: Is bivalirdin (+/- GPI) sperior over UFH (+/- GPI) i STEMI-patients treated with PPCI?

54 Differences in baseline characteristics

55 Reslts in or example Baseline The incidence of cardiogenic shock at admission was 5.1% in the UFH vs 3.6% in the bivalirdin Time delay between symptom onset to prehospital ECG was 143 vs 149 mintes Higher se of DES, radial access and new ADP receptor blockers in the bivalirdin grop reflecting evolving PCI techniqes and medical treatment the last years when bivalirdin was more commonly sed

56 Differences in baseline characteristics MV analysis (logistic, Cox etc) Propensity score Propensity matching

57 MV analysis Covariates selection Bivariate analysis Selection by athors -Previos stdies -Biological plasibility Limitations One covariate for 10 events Missing vales

58 Propensity Score

59 Original vs propensity score matched poplations, table 1

60 Original vs propensity score matched poplations, table 2

61 Propensity score matched grops Smaller stdy poplation Only small differences between grops remains Yo may adjst for these variables where difference between grops still remain

62 Analysing and reporting data RCT vs register stdies RCT: No (minor) differences in baseline characteristics between the stdy and control grop. Adjstment is not needed. Jst ARR, RRR. Register stdies: Often essential differences between the grops to be compared. Adjstment is needed. Crde and adjsted OR/HR. Baseline table in the EUROMAX trial comparing biva vs UFH in STEMI patients. Steg et al. N Engl J Med 2013;369:

63 Analysing and reporting data RCT vs register stdies RCT: Time-dependent endpoints: typically KM-crves with log rank test. Register stdies: Time-dependent endpoints typically Cox proportional regression crves, crde and mltivariable adjsted. KM-crves in the EUROMAX trial comparing biva vs UFH in STEMI patients. Steg et al. N Engl J Med 2013;369:

64 How to handle missing vales?

65 Missing vales in or example

66 Missing vales Exclsion from analysis Simple missing vales imptation Mltiple missing vales imptation

67 Conclsion in or stdy Crde differences exist in the primary and secondary endpoints, bt depends to a great part to differences in baseline data that affects the endpoints (confonding). Ths we can only trst the mltivariable adjsted data logistic regression as regards non-time dependent dichotomos endpoints, Cox regression as regards time dependent dichotomos endpoints. Also propensity matched poplation as a sensitivity analysis Conclsion: In STEMI patients treated with primary PCI, bivalirdin redced the risk of major in-hospital bleeding compared with UFH ± GPI, withot a significant difference in the 30-day and 1-year risk of mortality, stent thrombosis and reinfarction.

68 Ethical considerations when doing register stdies Adeqate decoding mst be done. Informed consent is not needed bt the participants shold get information that they will be registered, and have the right to deny registering, and have the right to know what have been registered, correct data that is wrong etc. Approval from the Ethical Board (EPN) is needed also for register research! Yo have to specify the research qestion. If yo want to se yor register data for a new research qestion, yo need to apply again to the Ethical Board. Merging of data needs approval by Datainspektionen. If yo start a new register PUL-anmälan is needed.

69 Ethics to share data Sweden have a an niqe opportnity to do good register research becase of the personal identification nmbers, a long tradition of registering etc., bt sharing of data cold be better. Sharing data and merging of data saves time and money bt there are also risks inclded. Epidemiologic research stdies cold be based on hge data sets with long follow-p. Ths it cold be impossible to gather the same amont of data dring the same amont of years in order to replicate reslts. Ths data-sharing can facilitate that other research grops can replicate important findings and show that the reslts are solid. I daily life practice sharing of data is scarce many researchers do not want to share their data. Some fnders and stake holders today mandate that data is openly shared/free accessed and in the ftre this will probably be more common. An important qestion is whether the information to the registered individals has been broad enogh inclding information that data may be sed in several coming stdies. Otherwise the registered individals need to be informed that data will be sed for another stdy.

70 Ethics good qality research! Bad research is nethical! Associations between risk factors and disease are fond bt do not exist: Best case scenario: resorces cold have been sed for better research. Worst case scenario: There are conseqences where doctors change medical practice in the wrong direction or the poplation change there way of living in the wrong direction (diet recommendations, etc.) leading to worse instead of better health. Associations between risk factors and disease are not fond: An existing association is not discovered. Soltion? The Ethical Board cold demand a proper stdy design and an adeqate SAP (statistical analysis plan).

71

72