Column Mapping

The mapping interface helps you connect your source CSV columns to SDTM variables.

Overview

Column mapping is a critical step that defines how your source data transforms into SDTM-compliant output.

flowchart LR
    subgraph Source[Source CSV]
        S1[SUBJ_ID]
        S2[PATIENT_AGE]
        S3[GENDER]
        S4[VISIT_DATE]
    end

    subgraph Mapping[Fuzzy Matching]
        M[Match<br/>Algorithm]
    end

    subgraph Target[SDTM Variables]
        T1[USUBJID]
        T2[AGE]
        T3[SEX]
        T4[RFSTDTC]
    end

    S1 --> M --> T1
    S2 --> M --> T2
    S3 --> M --> T3
    S4 --> M --> T4
    style M fill: #4a90d9, color: #fff

The Mapping Interface

┌─────────────────────────────────────────────────────────────┐
│ Source Columns          │  Target Variables                 │
├─────────────────────────┼───────────────────────────────────┤
│ SUBJ_ID         ────────│──▶  USUBJID                       │
│ PATIENT_AGE     ────────│──▶  AGE                           │
│ GENDER          ────────│──▶  SEX                           │
│ VISIT_DATE      ────────│──▶  RFSTDTC                       │
│ RACE_DESC       ────────│──▶  RACE                          │
│ [Unmapped]              │     ETHNIC (Required)             │
└─────────────────────────┴───────────────────────────────────┘

Automatic Mapping

Trial Submission Studio uses fuzzy matching to suggest mappings:

How It Works

1. Analyzes source column names
2. Compares against SDTM variable names
3. Calculates similarity scores
4. Suggests best matches

Match Confidence

• High (>80%) - Strong name similarity, auto-accepted
• Medium (50-80%) - Review recommended
• Low (<50%) - Manual mapping needed

Example Matches

Manual Mapping

To Map a Column

1. Click on the source column
2. Click on the target variable
3. A connection line appears

To Unmap a Column

1. Click on the connection line
2. Or right-click and select “Remove Mapping”

To Change a Mapping

1. Remove the existing mapping
2. Create a new mapping

Required vs Optional Variables

Required Variables

Shown with a red indicator. Must be mapped for valid output:

• STUDYID - Study identifier
• DOMAIN - Domain abbreviation
• USUBJID - Unique subject identifier

Optional Variables

Shown without indicator. Map if data is available.

Expected Variables

Shown with yellow indicator. Expected for the domain but not strictly required.

Data Type Considerations

The mapping interface warns about type mismatches:

Controlled Terminology

For variables with controlled terminology:

• The interface shows valid values
• Warns if source values don’t match
• Suggests value mappings

CT Normalization

The Transform tab allows you to normalize values to CDISC Controlled Terminology:

Values are automatically transformed to their standardized form (e.g., “Years” → “YEARS”).

Supplemental Qualifiers (SUPP)

For non-standard variables that need to be captured as supplemental qualifiers, use the SUPP tab:

Configure QNAM, QLABEL, QORIG, and QEVAL for each supplemental qualifier variable.

Mapping Templates

Save a Template

1. Complete your mappings
2. File → Save Mapping Template
3. Name your template

Load a Template

1. Import your data
2. File → Load Mapping Template
3. Select the template
4. Review and adjust as needed

Best Practices

1. Review all automatic mappings - Don’t blindly accept
2. Map required variables first - Ensure compliance
3. Check controlled terminology - Validate allowed values
4. Save templates - Reuse for similar datasets

Next Steps

• Validation - Validate your mappings
• SDTM Variables - Variable reference