lung cancer
Conditions
Interventions
None listed
Sponsors
Eligibility
Inclusion criteria
Inclusion criteria: Eligible studies included full-text articles, brief reports, and conference abstracts published in English that reported sensitivity and specificity data for the immunohistochemical marker INSM1 in diagnosing SCLC and LCNEC. Articles providing only sensitivity or specificity data were excluded, as bivariate analysis requires both. Although one-gate patient recruitment is preferable for diagnostic accuracy assessments, two-gate studies, e.g., those that selected LCNEC patients and control groups (such as adenocarcinoma or squamous cell carcinoma) from separate datasets, were also included. All sample types, including surgical specimens, bronchoscopic specimens, and pleural effusion cell blocks, were eligible. Additionally, samples from non-pulmonary origins were accepted if they represented metastatic lung cancer in other organs or lymph nodes. The reference standard for this analysis was a pathological diagnosis made by pathologists. Studies where INSM1 influenced the pathological diagnosis were not excluded but were scored with deductions in the QUADAS-2 evaluation.
Exclusion criteria
Exclusion criteria: studies focusing on neuroendocrine tumors (e.g., Merkel cell carcinoma) or other non-pulmonary neuroendocrine tumors that did not provide lung cancer-specific data were excluded, even if INSM1 data were available.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Two analytical models were employed: 1.The NSCLC model aimed to identify LCNEC, excluding SCLC. 2.The lung cancer model focused on identifying neuroendocrine-associated cancers, including both SCLC and LCNEC. Sensitivity, specificity, the area under the curve (AUC), and the diagnostic odds ratio (DOR) were evaluated. If multiple cutoffs were used in an original article, all weakly, moderately, and strongly positive results were collectively considered positive. | — |
Countries
Japan
Contacts
Yokohama City University Hospital Chemotherapy Center