{
  "abstract": "Patient-reported outcomes(PROs),as an important tool for directly assessing health status,symptom burden,and quality of life from the patient 's perspective,are increasingly valued in modern medical research. However,PROs data possess inherent characteristics such as repeated measurements,multidimensionality,prevalent missingness,and non-normal distribution,which pose numerous challenges to their statistical analysis,including inconsistent method selection,poor comparability of results,and low regulatory recognition. This article systematically reviews the data types derived from PROs in different application scenarios and the corresponding statistical analysis strategies. It also analyzes methodological considerations in visualization,missing data,multiple correction,baseline covariates,and cross-cultural comparisons,aiming to provide methodological references for PROs data analysis.",
  "abstract_shown": true,
  "affiliations": [
    "Health Statistics Teaching and Research Office,Department of Military Preventive Medicine,Air Force Military MedicalUniversity,Xi'an,Shaanxi 710032,China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "YANG Zhe"
    },
    {
      "name": "YUAN Peng"
    },
    {
      "name": "JU Ying"
    },
    {
      "name": "LU Wenjing"
    },
    {
      "name": "SHANG Lei"
    },
    {
      "name": "ZHAI Zhongjie"
    },
    {
      "name": "LIANG Ying"
    },
    {
      "name": "ZHANG Haiyue"
    },
    {
      "name": "WANG Yue"
    },
    {
      "name": "TAN Zhijun"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9gkdg4ezr2bnj.bib",
  "cited_by": 0,
  "doi": "10.13429/j.cnki.cjcr.2026.10.027",
  "fulltext_url": "http://zglcyj.ijournals.cn/zglcyj/ch/reader/create_pdf.aspx?file_no=20261027",
  "id": "9gkdg4ezr2bnj",
  "issns": [
    "1674-8182"
  ],
  "landing_url": "https://doi.org/10.13429/j.cnki.cjcr.2026.10.027",
  "language": "zh",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "R"
    ],
    [
      "openalex",
      "2613|Statistical Methods in Clinical Trials"
    ]
  ],
  "openalex": "W7224129145",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-26",
  "publisher": "The Editorial Department of Chinese Journal of Clinical Research",
  "ris": "https://research.draconitic.com/paper/9gkdg4ezr2bnj.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:47:14Z",
      "native_id": "6cb5ebcdef834fb3b11885b372054044",
      "source": "doaj",
      "url": "https://doi.org/10.13429/j.cnki.cjcr.2026.10.027"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "openalex:2613|Statistical Methods in Clinical Trials",
      "subfield": "statistics"
    }
  ],
  "title": "Analysis methods and strategies for patient-reported outcomes data in clinical research",
  "title_text": "Analysis methods and strategies for patient-reported outcomes data in clinical research",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:47:14Z",
  "url": "https://research.draconitic.com/paper/9gkdg4ezr2bnj",
  "venue": "Zhongguo linchuang yanjiu",
  "versions": []
}