dataesr/scientific-paragraphs-categorization huggingface dataset:
The patients included might thus differ by sex, age, social and family status, degree of involvement, disease history, comorbidities, duration of treatment, and outcomes. This enables a broader understanding of the phenomenon under study. Because the analysis takes place simultaneously with the data collection, the latter continues for as long as the analysis of the material continues to provide new information useful for exploring the topic. Sample size in qualitative research is not defined in advance. It is determined by data saturation, usually defined as when the analysis of new material no longer yields new findings  [64]. Saturation is, as Morse stated, "the key to excellent qualitative work"  [65]. It is indeed an essential criterion of validity in qualitative research, especially for qualitative studies intended to lead to PRO development  [66] , as it ensures in-depth study of the phenomenon and suggests that further interviews are unlikely to produce new findings.
Stage 4: data collection, access to experience The quality of the data collection determines the quality of the results. The goal is to reach the narrative of the experience  [69]. The tool used to obtain this narrative always depends on the context, in either individual interviews or focus groups. Researchers in charge of data collection procedure should always consider the risk that face-to-face questioning might limit the subjects' ability to narrateto talk abouta subject so deeply personal, especially vulnerable persons  [70]  and adapt the data collection process to ensure they reach this narrative. Patients can find it difficult, even intrusive, to talk about their lived experience of a disease  [71]. Most of the time, the IPSE data collection procedure relies on visual narrative support for the participants, aimed at enhancing the narrative by reducing inhibitions.
This support may be a photograph, or a clinical vignette, or a short video clip directly related to the experience under study. It also facilitates the relationship and communication between the researcher and the subjects  [70]. Photo-elicitation is the visual narrative support method we use most often  [72]. This tool helps participants to think about a pictureideally one they took themselves or, sometimes chosen with caution by the research group for the purpose of introducing the object of the study without influencing the participants. The positive effects of photo-elicitation on the research process have been widely described in qualitative literature: it improves the quality of the data collected  [73] , it promotes active cognitive involvement and better participation in the research  [74]  and when the participants take the picture themselves, it empowers them, by putting them in a more active position and thereby giving them the opportunity to influence the research process more strongly  [75].
In interviews, the qualitative researchers systematically start by asking the participants to comment and react to the experience-related visual support. The latter usually begin and spontaneously continue speaking about it and especially their own experience. The researchers then move on to open-ended questions  [76] , structured by the areas to explore, developed in turn from: (i) reading two pilot interviews, which will not form any part of the data analyzed for the study, (ii) the qualitative researchers' own thoughts, each with different insights according to his or her own explicated preconceptions on the subject, and (iii) the knowledge and representations of the physicians experts in the topic. The group collectively chooses the areas, but these may be modified throughout the research process by each interview conducted.
The interviewers use an interactive conversational style  [77]. In an IPSE study, participants are considered the experts on their own experience. Qualitative researchers must conduct interviews that offer them the opportunity to recount it. In practice, they use prompts based on the "life-world"  [78] , a phenomenological concept with five dimensions (i. e. , lived body, lived time, lived space, otherness and selfhood) through which the everyday actions and thoughts of the participants can be explored. All interviews are recorded and then transcribed verbatim, including the nonverbal aspects (e. g. , pauses, hesitation, and laughs). The data are anonymized. The transcripts obtained are the object of the analysis. Stage 5: data analysis, from the structure of the experience to its translation into concrete proposals Our analytic process is rigorous, detailed, systematic, and sharable.
They can refer to these notes during the analysis and share them (or not) during the group process. Next, they read the interview transcript three times, taking notes at each reading. This process bathes the researchers in each participant's expressive style and enables an overview of the narrative. These numbers of times to listen to and read the interview are of course suggestions; these remain the decision of each researcher. For instance, some researchers prefer to transcribe their own data and do not need to listen and read as much as a researcher discovering the data for the first time. However, in our experience, for data not transcribed by the researcher, listening twice and reading three times appear to be a perfect compromise to really saturate oneself with the material without wasting too much time.
-Exploring the experience word by word: The researchers explore the interview meticulously and cut up the entire text (in units of one or several words) into segments called descriptive units (Table  1 ). These descriptive units are not preestablished and remain as close as possible to the participants' words. -Regrouping the descriptive units into categories: The units are categorized, that is, they are regrouped according to their proximity of meaning and experience, wherever they may be in the interview. This reorganization reveals the framework of the participants' experience (Fig. 4 ). These stages are carried out with the help of "QSR" NVivo12 software to create and assemble the descriptive Fig. 2  Stage 5 of IPSE. From the demonstration of the structure of the experience to its translation into concrete proposals.
a. The procedure of each researcher, initially individually, corresponds to the descriptive analysis phase, including: i) listening to and reading the interview, ii) cutting up the text in descriptive units and then regrouping them into categories, This operation is performed for each of the 20 interviews, which are analyzed transversally. b. This structuring phase involves a group procedure (at least 3 researchers) with regular pooling of the data and analysis, during which the theoretical sufficiency is assessed. During this phase, the axes of experience are produced and the group determinates the central axes of experience, which result in the proposal of a structure of the lived experience. Finally the practical phase, which leads from triangulation by the literature to concrete proposals (guidelines, PRO) units and provide graphic support for their reorganization.
I've always had the impression Have the impression that women observe more than men… Women observe more or else Or else yeah I have the impression that Have the impression the women stare at me much more than the men stare at me More the women Be stared at and the patients, all of whom have familiarized themselves with the data (by listening and reading all the interviews as many times as necessary), without performing the descriptive analysis. The group's heterogeneity has a heuristic function essential for the construction of the results: the group enables the coconstruction by all group members of important points of the experience linking a set of implicit perspectives, made up of each researcher's culture, theory, knowledge, sex, function, and background. The three researchers meet with the rest of the group after the analysis of five interviews, then 10, then 15, then 20, etc.
… to share the categories that have been uncovered and assess their theoretical sufficiency. In practice, for organizational reasons mostly, group meetings can occur after the analysis of more or less than five interviews; however, we recommend this rhythm of meetings because of our experience: we found that sharing the content of the descriptive analysis of more than five interviews can result in a superficial sharing that impairs the quality and originality of the results, while more frequent meeting appeared to be time-consuming without providing richer data analysis. The structuring phase In practice, during these twohour meetings, the group must: Regroup the categories into axes of experience: The reorganization of the categories must uncover the framework of the participants' experience, which we call its axes.
Accordingly, the results will propose, for example, supports for interviews or practical recommendations that physicians can use directly with these patients. A process of triangulation with the data in the literature completes the analytic process. This is not a process original to IPSE, of course, but rather a good practice that should be followed in all qualitative health research  [20, 22]. The physicians experts in the topic and responsible for the literature review now share with the group their in-depth analysis of the literature from several databases (PubMed, PsycINFO, CINALH, and Web-of-Science (SSCI)) to identify the original aspects of the results and their differences and similarities with the literature. The completed study is then reported in a scientific article that meets the COREQ criteria  [80].
Triangulation This concept refers to the use of multiple methods or data sources as a rigorous procedure to ensure a global understanding of the phenomenon under study  [81]. There are four types of triangulation: "method triangulation, investigator triangulation, theory triangulation, and data source triangulation"  [82]. In an IPSE study, at least three researchers are involved with data collection and individual analytical procedures; several data collection techniques can be used in the same study (for instance, individual interview and focus group); and triangulation with the literature is systematically carried out.
Stage 3 The research group defined the inclusion and exclusion criteria, intended to attain this exemplarity. All patients provided informed written consent before inclusion. Because patients had several consultations a month, a large amount of clinical and paracliniclal data were available: clinical elements, psychometric assessments, and additional examinations. Social and demographic data, Rodnan scores (of skin thickening), the Cochin Hand Function Scale (measuring functional involvement of the hand), and scores on the specific Scleroderma Health Assessment Questionnaire (SHAQ) QoL scale were collected for all included patients. These data were not to be analyzed but collected to present the clinical characteristics of the sample in detail. We used our purposive sampling strategy and included patients differing by age, social and family status, hand involvement, disease history, and comorbidities, continuously looking for potential heterogeneity.
Stage 4 A researcher first met each participant to obtain his or her written consent and to collect social and demographic data and any relevant clinical scores. This facilitated the subsequent research interview, a few days later. It was clear that data for this study had to be collected in individual interviews as we wanted to reach an individual lived experience. We were nonetheless aware that patients might find it difficult, even intrusive, to talk about parts of their sick bodies. We therefore chose to provide them with visual narrative support: a photograph of a hand with Raynaud's phenomenon, a characteristic disabling manifestation in 95% of SSc cases (Fig. 4 ). Photo-elicitation has not previously been used in any qualitative study of patients with SSc. The interview systematically began by asking participants for their reaction to the photograph.
Findings: We obtained data from 14 of 19 RCTs (8,278 of 10,041 participants). Meta-analysis revealed an adjusted relative risk (RR) of mortality at one year of 0. 99 (95% CI: 0. 93, 1. 06) and a hazard ratio of 0. 99 (95% CI: 0. 94, 1. 05). The adjusted RR for VTE was 0. 58 (95% CI: 0. 47, 0. 071), for major bleeding 1. 27 (95% CI: 0. 92, 1. 74), and for minor bleeding 1. 34 (95% CI: 1. 19, 1. 51). Subgroup analysis of VTE occurrence by cancer type identified the most certain benefit from heparin treatment in patients with lung cancer RR=0. 59 (95% CI: 0. 42, 0. 81) which dominated the overall reduction in VTE. Certainty of the evidence for the outcomes ranged from moderate to high. Interpretation: LMWH reduces risk of VTE without importantly increasing risk of major bleeding but does not prolong survival.
Evidence before this study We previously conducted a study-level systematic review and meta-analysis suggesting that cancer patients may experience a survival benefit from prophylactic heparin, in addition to the reduction in venous thromboembolism. There also was uncertainty if antithrombotic effect differs by cancer subtype. These analyses were based on a search of MEDLINE, EMBASE, and the Cochrane Library databases for randomized controlled trials comparing parenteral anticoagulants to placebo or standard care among patients with solid cancer until February 2016. Patients had no indications for prophylactic or therapeutic anticoagulation and were ambulatory. Search terms included "heparin", "cancer", "clinical trial" as well as the names of various types of low-molecular weight heparin.
Literature search We conducted a search of the following electronic bibliographic databases (Table  S1 ):(  16 ) MEDLINE, EMBASE, and the Cochrane Library (including Cochrane Central Register of Controlled Trials/CENTRAL, Clinical Trials, DARE and NHS EED) from inception until January 2017. An updated search was completed in May of 2020, studies published during this period are included in sensitivity analysis which compares study-level meta-analysis to our individual participant data meta-analysis. To identify additional studies, we also used the 'related article' feature in PubMed and reviewed references of identified studies, narrative review articles, and conference proceedings of the American Society of Clinical Oncology as well as the American Society of Hematology. We applied no date or language restrictions to included trials.
Two reviewers independently assessed titles and abstracts of all identified citations for potential eligibility (Figure  1 ). Two reviewers screened full texts for eligibility using a standardised pilot tested form with explicit inclusion and exclusion criteria. Decisions were compared and agreement was measured using the Kappa (κ) statistic. ( 20 ) Disagreements were resolved by consensus and, when needed, with the help of a third reviewer. Reasons for exclusion were recorded. We contacted authors and sponsors of eligible trials by email, fax, or telephone, to invite them to share their data. When necessary, we placed data sharing requests through clinicalstudydatarequest. com. In addition to the study protocol and complete analysis plans, a detailed list of all variables of interest was provided to contacted trialists in order to maintain analytical transparency, to avoid data driven analysis and to encourage authors to share relevant trial data.
The study protocol, case report forms and corresponding datasets with all patient identifiers removed were requested. Requested baseline data included participant's anonymized demographic information, cancer diagnosis, concomitant therapies, history of VTE and bleeding, inflammatory markers as well as platelet and haemoglobin measurements. Requested follow-up information included randomisation, treatment start/stop, censoring, and outcome (mortality, VTE, bleeding, thrombocytopenia and health related quality of life) occurrence dates. We required DVT events be diagnosed using an objective diagnostic test such as: venography, or compression ultrasound and included any DVT events recorded in shared data regardless of their occurrence in lower or upper extremities. Pulmonary embolism events had to be diagnosed using an objective diagnostic test such as: pulmonary perfusion/ventilation scans, computed tomography pulmonary angiography or autopsy.
Assessment of risk of bias and overall certainty of evidence Two review authors assessed, in duplicate and independently, the risk of bias according to Cochrane methods. Disagreements were resolved by discussion or with the help of a third reviewer. We used the following criteria to assess the risk of bias: allocation concealment; blinding of participants, healthcare providers, data collectors, outcome adjudicators, and data analysts; completeness of available data; and stopping early for benefit. We assessed selective outcomes and other reporting bias by comparing outcomes in published protocols and in the methods section to the outcomes reported in the published paper. We assessed statistical heterogeneity by calculating the Chi 2 and its p-value, and the I 2. We recorded and reported the sponsorship of included trials (whether sponsored by a for-profit or not-for-profit organisation or government agency) and assessed financial and intellectual conflicts of interest.
Inverted funnel plots were generated for each comparison to detect possible publication bias. We used Grading of Recommendations Assessment, Development and Evaluation (GRADE) evidence profiles to summarise the intervention effects following the GRADE approach  (21, 22)  to provide support for decision makers. We used GRADE's GRADEpro software. (23)  To perform the GRADE assessment, we assessed publication bias and heterogeneity by using study-level identifiers. We conducted this assessment for the relative estimates of effect as well as baseline risk estimates in various patient subgroups.
Datasets and data extraction Two review authors independently extracted individual participant data and aggregate level data in duplicate using standardised pre-piloted data extraction forms. We standardised variable names and value labels across trials. Data were initially entered into an Excel database and converted to SAS for analysis. Finally, we synthesized data sets and assigned a coded trial variable for each participant. The percentage of missing data in analyses relevant variables was calculated and Little's method was used to assess the missing completely at random (MCAR) assumption in the variables with at least 5% of missing data. If the MCAR assumption was violated, we further examined the MAR pattern by comparing the outcome in the variable with and without missing values.
Data analysis All analyses followed the intention-to-treat (ITT) principle. We summarised categorical data using frequencies alongside percentages and continuous data with mean or median, depending on the distribution, together with standard deviation (SD) or interquartile range (IQR). For dichotomous outcomes, we expressed the intervention effects in relative risk (RR). A one-stage approach was used to analyze data. In the regression analyses, we used multilevel models  (24) (25) (26)  to incorporate data at trial level and patient level. We included four adjustment variables -age, time to cancer diagnosis prior to baseline, cancer type and stage of cancer -as fixed effects and trial as a random effect. Therefore, heterogeneity among trials was modelled with the frailty random effect. The regression modeling was based on the joint distribution of the treatment effect and trial with a bivariate normal distribution (i.
(29)  We also calculated the anticipated absolute effects based on the adjusted RR, and three assumed baseline risks, in terms of the median or mean difference in survival. In addition, we performed the following pre-specified sensitivity analyses to investigate differences in summary effect estimates related to the conduct of our methods: 1. We compared the main IPDMA results with the results of study-level meta-analysis using the studies we received the original datasets for. 2. We evaluated if higher risk of bias in the original study compared to lower risk of bias may be associated with a greater effect. We also explored the heterogeneity in the summary effect estimates related to different patient subgroups. We tested the subgroup effect on an interaction term with the treatment in the mixed-effect Poisson regression model with the five adjustment variables including trial as random effect listed as above.
This approach is preferred to separate subgroup group-specific analyses. (30, 31)  The subgroup factors considered were: As described in our study protocol  (19) , we initially planned to examine differences in LMWH dose and schedule but due to the high number of variations between studies, we were unable to perform these subgroup analyses. We used SAS V. 9. 4 (Cary, North Carolina, USA) to analyse data. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Study authors with access to shared clinical trial data included HJS, MV, and QZ. The corresponding author had full access to all of the data and the final responsibility to submit for publication.
27 (95% CI: 0. 92, 1. 74) for a risk difference of 0. 4% more in LMWH patients (95% CI: 0. 3 fewer to 1. 3 more, Table  3 ). Minor bleeding events occurred in   2 ). We found no significant interaction effects for major bleeding, minor bleeding, or thrombocytopenia (Appendix p  23 -25). A study-level meta-analysis, including the same studies we obtained individual participant data for, comparing LMWH to no LMWH for each outcome is available in the supplementary material (Appendix p 26 -34). A funnel plot for the primary outcome of mortality at 12 months indicates no publication bias is present (Appendix p 35). Results resemble analysis using individual participant data with no differing conclusions. Additional study-level meta-analysis including all studies eligible for inclusion for the primary outcome of mortality at 1 year depicts similar results to our IPDMA (Appendix p 36).
Acknowledgments This work was supported by a grant from the  Canadian Institutes of Health Research  ( CIHR knowledge synthesis grant ,  KRS 126594  to HJS), a government organization that supports health research, and the  Michael G. DeGroote Cochrane Canada  and McMaster GRADE centres. CIHR had no role in designing the study, gathering, analyzing, or interpreting the data. We would also like to thank the research organizations and authors responsible for sharing clinical trial data:  Sanofi ,  Novartis Pharma GmbH ,  GlaxoSmithKline ,  Instituto Científico y Tecnológico, University of Navarra, Velindre National Health Service Trust, Charité-Universitätsmedizin Berlin ,  Sunnybrook Health Sciences Centre, Hull and East Yorkshire Hospitals Trust ,  The Mayo Clinic , and the  Hospital Saint-Antoine.
This meta-analysis included a heterogeneous population in terms of types of cancer. However, with slightly more than half of the patients having lung cancer only 4 specific types of cancer demonstrated sufficient representation to support specific analysis. Due to the numerous permutations in type, dose and schedule of LMWH treatment, we were unable to complete all pre-planned subgroup analyses. Additionally, the trial data did not include sufficiently comparable data describing health related quality of life. (19)  Although we could not obtain data from six trials, these individual patient data (n=2,153 participants) represent only 20. 6% of participants in all potentially eligible studies and, thus, their inclusion would have been unlikely to alter the results. In addition, study level results from these studies do not differ from our findings.