筆者在不久之前簡單地介紹幾種比較常見的報告指引 (goo.gl/LMl97H),其中有一個RECORD statement(REporting of studies Conducted using Observational Routinely-collected Data)是觀察型研究的STROBE statement(STrengthening the Reporting of OBservational studies in Epidemiology)的延伸,剛於2015年正式發表在PLoS Medicine。
RECORD statement主要是針對例行性蒐集資料的觀察型研究,例如近幾年開始國內幾家大型醫學中心開始建置自家醫院的醫學資料庫、社區的長期追蹤研究(例如知名的Framingham study)、各家醫院的健檢資料或是目前炙手可熱的健保資料庫等,都屬於此類重複性蒐集資料的研究類型。
RECORD statement在既有STROBE statement的22條檢核項目(Checklist item)新增了幾個項目,關於STROBE statement的內容除了官網以外(www.strobe-statement.org),也有簡體中文的翻譯(goo.gl/jY9Dt1)。讀者可於http://www.equator-network.org/reporting-guidelines/record/下載到全整的檢核表,本篇文章旨在介紹這些新增的項目。
表一列出RECORD新增項目,第一項是標題或摘要,包括三個子項目:
- RECORD 1.1:在標題或摘要中,應該載明資料的類型。如果可能的話,要提到資料庫的名稱
- RECORD 1.2:在標題或摘要中,如果適用的話,應該要載明地區以及該研究的收案時間或觀察時間
- RECORD 1.3:若該研究用到多個資料庫之間的連結,應該要在標題或摘要中清楚地陳述。
筆者補充:
1.1的「資料的類型」指的是必須盡可能的在標題或摘要就讓讀者明白所使用的資料來源,譬如「Title(略): A population-based cohort study between 1997 to 2013 from National Health Insurance Research Database (NHIRD) in Taiwan」,此標題就符合了1.1與1.2的要求,假使會造成標題過長,則可考慮改放到摘要中。倘若作者還有連結其他資料庫,例如死因資料、出生登記資料等,則可以在摘要中提及,以符合1.3的要求。
第6點是關於研究對象的說明,包括三個子項目:
- RECORD 6.1:選擇研究族群的方法(例如用來辨認研究對象的代碼或演算法)應該要詳細的列示。若不可行,要盡可能的解釋為何不適用。
- RECORD 6.2:若有關於用來選擇研究對象的代碼或演算法的驗證研究,要盡量引用。若驗證研究在本研究有做,但是尚未發表,那麼要提供方法與結果的細節。
- RECORD 6.3:若該研究使用到多個資料庫的連結,可考慮使用流程圖或其他視覺化的呈現,以展示資料連結的過程。另外列出在連結時的每一階段的個體數量(筆者註:人數、人次或住院次等)。
筆者補充:
6.1跟6.2的規定應該比較明顯是針對資料庫類型的研究,例如以健保資料庫來說最常用來收案的方式就是疾病碼(ICD-9 CM code)、手術處置碼(ICD-9 OP code)或醫令碼(Order code),這必然是要報告的。6.2的要求則是要盡可能地找到驗證研究,或是該研究可以自行驗證,通常可以用自家醫院的病人資料作疾病碼的驗證,例如以健保資料庫收集全台灣心衰竭的住院病人,則可以自家醫院的心衰竭病人作為驗證的對象。
第7點是關於變項的說明,只有一個項目:
- RECORD 7.1:必須提供用來辨識暴露因子、結果變項、混淆變項與效果修飾因子的代碼或演算法的完整清單。若無法提供,則必須說明原因。
筆者補充:
7.1的規定也是明顯是針對資料庫類型的研究,以健保資料庫為例,作者應該要能提供疾病碼、手術處置碼或醫令碼(for 藥物、處置等),通常會放在該研究的附錄表。他們所謂的「混淆變項」是控制變項或共變量的意思(Control variable or covariate),而「效果修飾因子」指的是交互作用的變項(Interaction)。這邊筆者要幫他們補充一下,關於排除條件(Exclusion criteria)的代碼也應該要說明。
表一、RECORD新增項目
|
STROBE Item No. |
RECORD items |
---|---|---|
Title and abstract |
|
|
|
1 |
RECORD 1.1: The type of data used should be specified in the title or abstract. When possible, the name of the databases used should be included.
RECORD 1.2: If applicable, the geographic region and timeframe within which the study took place should be reported in the title or abstract.
RECORD 1.3: If linkage between databases was conducted for the study, this should be clearly stated in the title or abstract. |
Introduction |
|
|
Methods |
|
|
Participants |
6 |
RECORD 6.1: The methods of study population selection (such as codes or algorithms used to identify subjects) should be listed in detail. If this is not possible, an explanation should be provided.
RECORD 6.2: Any validation studies of the codes or algorithms used to select the population should be referenced. If validation was conducted for this study and not published elsewhere, detailed methods and results should be provided.
RECORD 6.3: If the study involved linkage of databases, consider use of a flow diagram or other graphical display to demonstrate the data linkage process, including the number of individuals with linked data at each stage. |
Variables |
7 |
RECORD 7.1: A complete list of codes and algorithms used to classify exposures, outcomes, confounders, and effect modifiers should be provided. If these cannot be reported, an explanation should be provided. |
Data access and cleaning methods |
新增 |
RECORD 12.1: Authors should describe the extent to which the investigators had access to the database population used to create the study population.
RECORD 12.2: Authors should provide information on the data cleaning methods used in the study. |
Linkage |
新增 |
RECORD 12.3: State whether the study included person-level, institutional-level, or other data linkage across two or more databases. The methods of linkage and methods of linkage quality evaluation should be provided. |
Results |
|
|
Participants |
13 |
RECORD 13.1: Describe in detail the selection of the persons included in the study (i.e., study population selection) including filtering based on data quality, data availability and linkage. The selection of included persons can be described in the text and/or by means of the study flow diagram. |
Discussion |
|
|
Limitations |
19 |
RECORD 19.1: Discuss the implications of using data that were not created or collected to answer the specific research question(s). Include discussion of misclassification bias, unmeasured confounding, missing data, and changing eligibility over time, as they pertain to the study being reported. |
Other Information |
|
|
Accessibility of protocol, raw data, and programming code |
新增 |
RECORD 22.1: Authors should provide information on how to access any supplemental information such as the study protocol, raw data, or programming code. |
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