Q (sonnet): What are the most frequently administered systemic therapy regimens for lung cancer patients in the MSK-CHORD Study?

▶ list_guides
{}

▶ get_study_guide
{
 "study_id": "msk_chord_2024"
}

◀ result
{"result":[{"uri":"cbioportal://mutation-frequency-guide","description":"Comprehensive guide for calculating gene mutation frequencies with gene-specific profiling denominators"},{"uri":"cbioportal://clinical-data-guide","description":"Guide for querying clinical data including patient vs sample level considerations"},{"uri":"cbioportal://sample-filtering-guide","description":"Guide for filtering samples and studies in cBioPortal queries"},{"uri":"cbioportal://common-pitfalls","description":"Guide to avoid common mistakes when querying cBioPortal data. If you already know which numbered pitfall applies, fetch just that section via read_guide(\"cbioportal://common-pitfalls#<number>\") (e.g. #16) instead of the full guide"},{"uri":"cbioportal://treatment-guide","description":"Guide for querying treatment/clinical event data including drug agents, timelines, and linking to genomic data"},{"uri":"cbioportal://faq-guide","description":"General cBioPortal FAQ: history, how to cite, data types, reference genome, abbreviations, GISTIC thresholds, API access"},{"uri":"cbioportal://statistical-tests-guide","description":"Statistical test selection guide — decision matrix for choosing Fisher's exact, Wilcoxon, chi-squared, t-test, ANOVA, etc. based on data type and group count"},{"uri":"cbioportal://gene-expression-guide","description":"Gene expression / copy-number / methylation analysis. Covers genetic_alteration_derived, profile_type discovery, and the gene_pair_coexpression view for Spearman correlation between two genes"},{"uri":"cbioportal://external-resources-guide","description":"Guide for finding external linked resources such as imaging, pathology, Minerva, HTAN, or other resource_* table links before declaring data unavailable"},{"uri":"cbioportal://gene-resolution-guide","description":"Guide for resolving ambiguous gene symbols, aliases, gene families, and shorthand such as CD3 before querying expression or alteration data"},{"uri":"cbioportal://study-resolution-guide","description":"Guide for resolving requested studies, avoiding silent substitute cohorts, and redirecting to known external cBioPortal instances when data is not in this deployment"},{"uri":"cbioportal://germline-guide","description":"Guide for querying germline variant data — storage columns, study discovery, query patterns, and somatic vs germline considerations"},{"uri":"cbioportal://study-guide/{study_id}","description":"Dynamic study-specific guide - use get_study_guide(study_id) tool to generate"}]}

◀ result
# MSK-CHORD (MSK, Nature 2024)

**Study ID:** `msk_chord_2024`

## Overview
Targeted sequencing via MSK-IMPACT panels. Clinical annotations include some derived from natural language processing (denoted NLP).

**Exactly five cancer types** (`CANCER_TYPE`, patients): Non-Small Cell Lung Cancer 7,809, Colorectal Cancer 5,543, Breast Cancer 5,368, Prostate Cancer 3,211, Pancreatic Cancer 3,109. There is **no melanoma** or any other cancer type; say so up front if asked, instead of substituting another type.

**No therapy-response variable.** There is no RECIST, objective response, or best-response attribute or event. For treatment-outcome questions (e.g. immunotherapy response), say this first; the only proxies are `OS_MONTHS`/`OS_STATUS`, or NLP radiology progression events (`Diagnosis` events with `SUBTYPE = 'Progression'`, key `PROGRESSION` = Y/N/Indeterminate), in patients with `Treatment` events of the relevant `SUBTYPE` (e.g. `Immuno`: 3,341 patients). Hand off the comparison to cBioPortal group comparison / survival.

**Nearly one sample per patient: 24,950 patients / 25,040 samples.** Only 90 patients have more than one sample, and all 90 have samples from two different cancer types (second primaries); only 26 have both a `Primary` and a `Metastasis` sample. There is no meaningful same-patient (paired) primary-vs-metastasis cohort. For "same patient" / paired questions, say this up front, then offer the **unpaired** comparison of all `Primary` vs `Metastasis` samples (`SAMPLE_TYPE`), labelled as unpaired.
```sql
SELECT countIf(n > 1) AS multi_sample_patients,         -- 90
       countIf(has_p AND has_m) AS primary_and_met      -- 26
FROM (SELECT patient_unique_id, count() AS n,
             has(groupArray(attribute_value), 'Primary') AS has_p,
             has(groupArray(attribute_value), 'Metastasis') AS has_m
      FROM clinical_data_derived
      WHERE cancer_study_identifier = 'msk_chord_2024' AND attribute_name = 'SAMPLE_TYPE'
      GROUP BY patient_unique_id);
```

## Gene Panels
This study uses multiple MSK-IMPACT panel versions:
- **IMPACT341**: Earlier version, 341 genes
- **IMPACT410**: 410 genes
- **IMPACT468**: 468 genes  
- **IMPACT505**: Latest version, 505 genes

**Important:** Different samples may have different gene coverage. Always use gene-specific denominators when calculating mutation frequencies.

## Clinical Attributes - Semantic Guide

### Cancer Classification
| Attribute | Description | Values |
|-----------|-------------|--------|
| `CANCER_TYPE` | Broad cancer category | e.g., "Non-Small Cell Lung Cancer", "Breast Cancer" |
| `CANCER_TYPE_DETAILED` | Specific subtype | e.g., "Lung Adenocarcinoma", "Invasive Ductal Carcinoma" |
| `ONCOTREE_CODE` | OncoTree classification code | Standardized cancer type codes |

### Sample Information
| Attribute | Description | Values |
|-----------|-------------|--------|
| `SAMPLE_TYPE` | Sample origin | Primary, Metastasis, Local Recurrence, Unknown |
| `SAMPLE_CLASS` | Sample … (5439 more chars)

▶ read_guide
{
 "uri": "cbioportal://treatment-guide"
}

▶ clickhouse_list_table_columns
{
 "table": "clinical_event_derived"
}

◀ result
# Treatment Data Query Guide

## Overview

Treatment data in cBioPortal is stored in **clinical event tables**, separate from clinical attributes. This allows for timeline-based treatment records with start/stop dates.

## Start Here: Treatment Views

For "most common treatments / agents / regimens in study X", use the parameterized views (documented in `cbioportal://clinical-data-guide`, Study-View Chart Counts):

```sql
-- Patients per agent (the portal's Treatment chart), with type/subtype arrays
SELECT * FROM treatment_counts_in_study(study='msk_chord_2024') ORDER BY patients DESC LIMIT 20;

-- Same-day agent combinations (investigational, prior-medication and radiation events excluded)
SELECT * FROM treatment_regimens_in_study(study='msk_chord_2024') ORDER BY patients DESC LIMIT 20;
```

Write raw event queries (below) only for subgroups, timelines or keys the views do not expose.

## Key Tables

| Table | Description |
|-------|-------------|
| `clinical_event` | Event records with patient_id, event_type, start_date, stop_date |
| `clinical_event_data` | Key-value pairs linked to each clinical_event_id |

## Schema

```
clinical_event
├── clinical_event_id (PK)
├── patient_id (FK → patient.internal_id)
├── event_type (Treatment, TREATMENT, Diagnosis, SURGERY, etc.)
├── start_date (days from diagnosis)
└── stop_date (days from diagnosis)

clinical_event_data
├── clinical_event_id (FK)
├── key (AGENT, SUBTYPE, etc.)
└── value
```

## Event Types

Not all studies have all event types. Common ones include:

| Event Type | Description |
|------------|-------------|
| `Treatment` / `TREATMENT` | Drug/therapy administration |
| `SURGERY` | Surgical procedures |
| `Diagnosis` | Diagnosis events |
| `LAB_TEST` | Laboratory results |
| `Sequencing` | Sequencing events |
| `Sample acquisition` | Sample collection |
| `PATHOLOGY` / `Pathology` | Pathology reports |

## Basic Treatment Queries

### List Available Event Types in a Study

```sql
SELECT DISTINCT ce.event_type, COUNT(*) as event_count
FROM clinical_event ce
JOIN patient p ON ce.patient_id = p.internal_id
JOIN cancer_study cs ON p.cancer_study_id = cs.cancer_study_id
WHERE cs.cancer_study_identifier = 'your_study_id'
GROUP BY ce.event_type
ORDER BY event_count DESC;
```

### List Treatment Data Keys in a Study

```sql
SELECT DISTINCT ced.key, COUNT(*) as cnt
FROM clinical_event ce
JOIN clinical_event_data ced ON ce.clinical_event_id = ced.clinical_event_id
JOIN patient p ON ce.patient_id = p.internal_id
JOIN cancer_study cs ON p.cancer_study_id = cs.cancer_study_id
WHERE cs.cancer_study_identifier = 'your_study_id'
  AND ce.event_type IN ('Treatment', 'TREATMENT')
GROUP BY ced.key
ORDER BY cnt DESC;
```

### Get Most Common Treatment Agents

```sql
SELECT 
    ced.value as agent,
    COUNT(DISTINCT ce.patient_id) as patient_count
FROM clinical_event ce
JOIN clinical_event_data ced ON ce.clinical_event_id = ced.clinical_event_id
JOIN patient p ON ce.patient_id = p.internal_id
JOIN cancer_stud … (6220 more chars)

◀ result
{"columns":[{"name":"clinical_event_id","type":"Int64"},{"name":"patient_id","type":"Nullable(Int64)"},{"name":"patient_stable_id","type":"String"},{"name":"start_date","type":"Nullable(Int64)"},{"name":"stop_date","type":"Nullable(Int64)"},{"name":"event_type","type":"LowCardinality(String)"},{"name":"cancer_study_identifier","type":"LowCardinality(String)"}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT * FROM treatment_regimens_in_study(study='msk_chord_2024') ORDER BY patients DESC LIMIT 20"
}

▶ clickhouse_list_table_columns
{
 "table": "clinical_data_derived"
}

◀ result
{"rows":[{"regimen":"CAPECITABINE","n_agents":1,"patients":4434,"treated_patients":21224,"pct_of_treated_patients":20.9},{"regimen":"FLUOROURACIL + LEUCOVORIN + OXALIPLATIN","n_agents":3,"patients":2974,"treated_patients":21224,"pct_of_treated_patients":14},{"regimen":"LEUPROLIDE","n_agents":1,"patients":2846,"treated_patients":21224,"pct_of_treated_patients":13.4},{"regimen":"PACLITAXEL","n_agents":1,"patients":2279,"treated_patients":21224,"pct_of_treated_patients":10.7},{"regimen":"GEMCITABINE","n_agents":1,"patients":2038,"treated_patients":21224,"pct_of_treated_patients":9.6},{"regimen":"ZOLEDRONIC ACID","n_agents":1,"patients":1902,"treated_patients":21224,"pct_of_treated_patients":9},{"regimen":"LETROZOLE","n_agents":1,"patients":1700,"treated_patients":21224,"pct_of_treated_patients":8},{"regimen":"IRINOTECAN","n_agents":1,"patients":1624,"treated_patients":21224,"pct_of_treated_patients":7.7},{"regimen":"CYCLOPHOSPHAMIDE + DOXORUBICIN","n_agents":2,"patients":1612,"treated_patients":21224,"pct_of_treated_patients":7.6},{"regimen":"ANASTROZOLE","n_agents":1,"patients":1519,"treated_patients":21224,"pct_of_treated_patients":7.2},{"regimen":"TAMOXIFEN","n_agents":1,"patients":1448,"treated_patients":21224,"pct_of_treated_patients":6.8},{"regimen":"BEVACIZUMAB","n_agents":1,"patients":1441,"treated_patients":21224,"pct_of_treated_patients":6.8},{"regimen":"FLUOROURACIL + IRINOTECAN + LEUCOVORIN + OXALIPLATIN","n_agents":4,"patients":1362,"treated_patients":21224,"pct_of_treated_patients":6.4},{"regimen":"OXALIPLATIN","n_agents":1,"patients":1339,"treated_patients":21224,"pct_of_treated_patients":6.3},{"regimen":"GEMCITABINE + PACLITAXEL PROTEIN-BOUND","n_agents":2,"patients":1312,"treated_patients":21224,"pct_of_treated_patients":6.2},{"regimen":"DEGARELIX","n_agents":1,"patients":1309,"treated_patients":21224,"pct_of_treated_patients":6.2},{"regimen":"ABIRATERONE","n_agents":1,"patients":1267,"treated_patients":21224,"pct_of_treated_patients":6},{"regimen":"DOCETAXEL","n_agents":1,"patients":1233,"treated_patients":21224,"pct_of_treated_patients":5.8},{"regimen":"FULVESTRANT","n_agents":1,"patients":1218,"treated_patients":21224,"pct_of_treated_patients":5.7},{"regimen":"CARBOPLATIN + PEMETREXED","n_agents":2,"patients":1188,"treated_patients":21224,"pct_of_treated_patients":5.6}]}

◀ result
{"columns":[{"name":"internal_id","type":"Int32"},{"name":"sample_unique_id","type":"String","comment":"Globally unique sample ID: cancer_study_identifier + \"_\" + sample.stable_id. Empty for patient-level attributes. Use this for sample filtering and joins."},{"name":"patient_unique_id","type":"String","comment":"Globally unique patient ID: cancer_study_identifier + \"_\" + patient.stable_id. Present for both sample and patient-level attributes."},{"name":"attribute_name","type":"LowCardinality(String)","comment":"Clinical attribute name (e.g., SAMPLE_TYPE, CANCER_TYPE, AGE, OS_MONTHS). Use with attribute_value for filtering. AGE may be floored or capped for de-identification (e.g. all children recorded as 18, or everyone 89+ recorded as 89 or 90): before age statistics check for a pile-up at the min/max, and if present compute age from DAYS_TO_BIRTH (-days / 365.25)."},{"name":"attribute_value","type":"String","comment":"Value of the clinical attribute (String). For SAMPLE_TYPE: Primary, Metastasis, Local Recurrence, Unknown. Missing values are empty strings, so use toFloat64OrNull(attribute_value) for numeric comparisons — CAST fails on them."},{"name":"cancer_study_identifier","type":"LowCardinality(String)"},{"name":"type","type":"LowCardinality(String)","comment":"Data level: \"sample\" for sample-level attributes (e.g., SAMPLE_TYPE), \"patient\" for patient-level attributes (e.g., AGE, OS_MONTHS)."}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH lung_patients AS (
    SELECT DISTINCT patient_unique_id
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'msk_chord_2024'
      AND attribute_name = 'CANCER_TYPE'
      AND attribute_value = 'Non-Small Cell Lung Cancer'
),
tx_events AS (
    SELECT ce.clinical_event_id,
           ce.patient_stable_id,
           concat('msk_chord_2024_', ce.patient_stable_id) AS patient_unique_id,
           ce.start_date
    FROM clinical_event ce
    JOIN patient p ON ce.patient_id = p.internal_id
    JOIN cancer_study cs ON p.cancer_study_id = cs.cancer_study_id
    WHERE cs.cancer_study_identifier = 'msk_chord_2024'
      AND ce.event_type IN ('Treatment','TREATMENT')
),
lung_tx AS (
    SELECT t.* FROM tx_events t
    INNER JOIN lung_patients lp ON t.patient_unique_id = lp.patient_unique_id
),
agent_subtype AS (
    SELECT lt.clinical_event_id, lt.patient_unique_id, lt.start_date,
           agent.value AS agent, subtype.value AS subtype,
           inv.value AS investigative
    FROM lung_tx lt
    JOIN clinical_event_data agent ON lt.clinical_event_id = agent.clinical_event_id AND agent.key = 'AGENT'
    LEFT JOIN clinical_event_data subtype ON lt.clinical_event_id = subtype.clinical_event_id AND subtype.key = 'SUBTYPE'
    LEFT JOIN clinical_event_data inv ON lt.clinical_event_id = inv.clinical_event_id AND inv.key = 'RX_INVESTIGATIVE'
    WHERE (subtype.value IS NULL OR subtype.value NOT IN ('Radiation Therapy','Prior Medications to MSK'))
      AND (inv.value IS NULL OR inv.value != 'Y')
),
regimens AS (
    SELECT patient_unique_id, start_date,
           arraySort(groupArray(agent)) AS agents
    FROM agent_subtype
    GROUP BY patient_unique_id, start_date
)
SELECT arrayStringConcat(agents, ' + ') AS regimen,
       length(agents) AS n_agents,
       COUNT(DISTINCT patient_unique_id) AS patients
FROM regimens
GROUP BY regimen, n_agents
ORDER BY patients DESC
LIMIT 20
"
}

◀ result
{"error_message":"Query execution failed: HTTPDriver for https://dl96orhu96.us-east-1.aws.clickhouse.cloud:8443 received ClickHouse error code 47\n Code: 47. DB::Exception: Identifier 'ce.patient_stable_id' cannot be resolved from table with name ce. In scope  tx_events AS t. (UNKNOWN_IDENTIFIER) (version 26.4.1.2359 (official build))\n"}

▶ clickhouse_run_select_query
{
 "query": "
WITH lung_patients AS (
    SELECT DISTINCT patient_unique_id
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'msk_chord_2024'
      AND attribute_name = 'CANCER_TYPE'
      AND attribute_value = 'Non-Small Cell Lung Cancer'
),
lung_tx AS (
    SELECT ced.clinical_event_id,
           concat('msk_chord_2024_', ced.patient_stable_id) AS patient_unique_id,
           ced.start_date
    FROM clinical_event_derived ced
    INNER JOIN lung_patients lp
        ON concat('msk_chord_2024_', ced.patient_stable_id) = lp.patient_unique_id
    WHERE ced.cancer_study_identifier = 'msk_chord_2024'
      AND ced.event_type IN ('Treatment','TREATMENT')
),
agent_subtype AS (
    SELECT lt.clinical_event_id, lt.patient_unique_id, lt.start_date,
           agent.value AS agent, subtype.value AS subtype,
           inv.value AS investigative
    FROM lung_tx lt
    JOIN clinical_event_data agent ON lt.clinical_event_id = agent.clinical_event_id AND agent.key = 'AGENT'
    LEFT JOIN clinical_event_data subtype ON lt.clinical_event_id = subtype.clinical_event_id AND subtype.key = 'SUBTYPE'
    LEFT JOIN clinical_event_data inv ON lt.clinical_event_id = inv.clinical_event_id AND inv.key = 'RX_INVESTIGATIVE'
    WHERE (subtype.value IS NULL OR subtype.value NOT IN ('Radiation Therapy','Prior Medications to MSK'))
      AND (inv.value IS NULL OR inv.value != 'Y')
),
regimens AS (
    SELECT patient_unique_id, start_date,
           arraySort(groupArray(agent)) AS agents
    FROM agent_subtype
    GROUP BY patient_unique_id, start_date
)
SELECT arrayStringConcat(agents, ' + ') AS regimen,
       length(agents) AS n_agents,
       COUNT(DISTINCT patient_unique_id) AS patients
FROM regimens
GROUP BY regimen, n_agents
ORDER BY patients DESC
LIMIT 20
"
}

◀ result
{"rows":[{"regimen":"CARBOPLATIN + PEMETREXED","n_agents":2,"patients":1184},{"regimen":"OSIMERTINIB","n_agents":1,"patients":1062},{"regimen":"PEMBROLIZUMAB","n_agents":1,"patients":745},{"regimen":"GEMCITABINE","n_agents":1,"patients":708},{"regimen":"CISPLATIN + PEMETREXED","n_agents":2,"patients":685},{"regimen":"CARBOPLATIN + PEMBROLIZUMAB + PEMETREXED","n_agents":3,"patients":624},{"regimen":"NIVOLUMAB","n_agents":1,"patients":533},{"regimen":"ZOLEDRONIC ACID","n_agents":1,"patients":525},{"regimen":"ERLOTINIB","n_agents":1,"patients":483},{"regimen":"MEGESTROL","n_agents":1,"patients":475},{"regimen":"BEVACIZUMAB + CARBOPLATIN + PEMETREXED","n_agents":3,"patients":444},{"regimen":"CARBOPLATIN + PACLITAXEL","n_agents":2,"patients":430},{"regimen":"DOCETAXEL","n_agents":1,"patients":425},{"regimen":"CARBOPLATIN","n_agents":1,"patients":392},{"regimen":"BEVACIZUMAB","n_agents":1,"patients":319},{"regimen":"DOCETAXEL + RAMUCIRUMAB","n_agents":2,"patients":309},{"regimen":"GEMCITABINE + VINORELBINE","n_agents":2,"patients":306},{"regimen":"PEMETREXED","n_agents":1,"patients":270},{"regimen":"CRIZOTINIB","n_agents":1,"patients":266},{"regimen":"DURVALUMAB","n_agents":1,"patients":235}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH lung_patients AS (
    SELECT DISTINCT patient_unique_id
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'msk_chord_2024'
      AND attribute_name = 'CANCER_TYPE'
      AND attribute_value = 'Non-Small Cell Lung Cancer'
),
lung_tx AS (
    SELECT DISTINCT concat('msk_chord_2024_', ced.patient_stable_id) AS patient_unique_id
    FROM clinical_event_derived ced
    INNER JOIN lung_patients lp
        ON concat('msk_chord_2024_', ced.patient_stable_id) = lp.patient_unique_id
    WHERE ced.cancer_study_identifier = 'msk_chord_2024'
      AND ced.event_type IN ('Treatment','TREATMENT')
)
SELECT (SELECT COUNT(*) FROM lung_patients) AS total_lung_patients,
       (SELECT COUNT(*) FROM lung_tx) AS lung_patients_with_treatment_event
"
}

◀ result
{"rows":[{"total_lung_patients":7809,"lung_patients_with_treatment_event":7486}]}

▶ resolve_and_route
{
 "studyIds": [
  "msk_chord_2024"
 ]
}

◀ result
{"success":true,"message":"Found 1 study. Use the metadata to call the appropriate navigation tool(s).","data":{"totalCount":1,"studiesWithMetadata":[{"studyId":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","sampleCount":25040,"studyViewUrl":"https://www.cbioportal.org/study?id=msk_chord_2024","metadata":{"clinicalAttributeIds":["ADRENAL_GLANDS","BONE","CANCER_TYPE","CANCER_TYPE_DETAILED","CLINICAL_GROUP","CLINICAL_SUMMARY","CNS_BRAIN","CURRENT_AGE_DEID","DIAGNOSIS_DESCRIPTION","ETHNICITY","FRACTION_GENOME_ALTERED","GENDER","GENE_PANEL","GLEASON_FIRST_REPORTED","GLEASON_HIGHEST_REPORTED","GLEASON_SAMPLE_LEVEL","HER2","HISTORY_OF_PDL1","HR","ICD_O_HISTOLOGY_DESCRIPTION","INTRA_ABDOMINAL","LIVER","LUNG","LYMPH_NODES","METASTATIC_SITE","MSI_COMMENT","MSI_SCORE","MSI_TYPE","MUTATION_COUNT","NUM_ICDO_DX","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","OTHER","PATHOLOGICAL_GROUP","PDL1_POSITIVE","PLEURA","PRIMARY_SITE","PRIOR_MED_TO_MSK","RACE","REPRODUCTIVE_ORGANS","SAMPLE_CLASS","SAMPLE_COUNT","SAMPLE_COVERAGE","SAMPLE_TYPE","SMOKING_PREDICTIONS_3_CLASSES","SOMATIC_STATUS","STAGE_HIGHEST_RECORDED","TMB_NONSYNONYMOUS","TUMOR_PURITY"],"molecularProfileIds":["msk_chord_2024_cna","msk_chord_2024_mutations","msk_chord_2024_structural_variants"],"availableComparisonTabs":["overlap","clinical","survival","alterations","mutations"]}}]}}

▶ navigate_to_study_view
{
 "studyIds": [
  "msk_chord_2024"
 ],
 "filterJson": {
  "clinicalDataFilters": [
   {
    "attributeId": "CANCER_TYPE",
    "values": [
     {
      "value": "Non-Small Cell Lung Cancer"
     }
    ]
   }
  ]
 }
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/study/summary?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Non-Small%20Cell%20Lung%20Cancer%22%7D%5D%7D%5D%7D","url":"https://www.cbioportal.org/study/summary?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Non-Small%20Cell%20Lung%20Cancer%22%7D%5D%7D%5D%7D","data":{"studyIds":["msk_chord_2024"],"studies":[{"studyId":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","sampleCount":25040}],"tab":"summary","hasFilters":true,"hasPlotsConfig":false,"pageDescription":"Overview of all study data displayed as interactive charts summarizing available clinical and genomic data. Click within a chart to filter. Additional charts may be available in the Charts menu."}}

═ answer (success)
## Systemic Therapy Regimens in Lung Cancer (MSK-CHORD)

MSK-CHORD's only lung cancer cohort is **Non-Small Cell Lung Cancer (NSCLC)** — 7,809 patients, of whom 7,486 have at least one recorded treatment event. Regimens below are defined as same-day agent combinations (excluding radiation therapy, prior-to-MSK medications, and investigational agents), reported as **raw patient counts** (percentages of total NSCLC patients cannot be reliably calculated — treatment data absence doesn't distinguish "not given" from "not collected").

| Regimen | # Agents | Patients |
|---|---|---|
| Carboplatin + Pemetrexed | 2 | 1,184 |
| Osimertinib | 1 | 1,062 |
| Pembrolizumab | 1 | 745 |
| Gemcitabine | 1 | 708 |
| Cisplatin + Pemetrexed | 2 | 685 |
| Carboplatin + Pembrolizumab + Pemetrexed | 3 | 624 |
| Nivolumab | 1 | 533 |
| Zoledronic Acid | 1 | 525 |
| Erlotinib | 1 | 483 |
| Megestrol | 1 | 475 |
| Bevacizumab + Carboplatin + Pemetrexed | 3 | 444 |
| Carboplatin + Paclitaxel | 2 | 430 |
| Docetaxel | 1 | 425 |
| Carboplatin | 1 | 392 |
| Bevacizumab | 1 | 319 |
| Docetaxel + Ramucirumab | 2 | 309 |
| Gemcitabine + Vinorelbine | 2 | 306 |
| Pemetrexed | 1 | 270 |
| Crizotinib | 1 | 266 |
| Durvalumab | 1 | 235 |

**Key patterns:** platinum-doublet chemotherapy (carboplatin/cisplatin + pemetrexed) dominates, consistent with standard NSCLC first-line regimens; osimertinib and erlotinib reflect EGFR-targeted therapy use; pembrolizumab/nivolumab/durvalumab represent checkpoint immunotherapy (as monotherapy or combined with chemo); crizotinib reflects ALK/ROS1-targeted therapy.

[Explore MSK-CHORD NSCLC Cohort in Study View](https://www.cbioportal.org/study/summary?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Non-Small%20Cell%20Lung%20Cancer%22%7D%5D%7D%5D%7D)

Overview of all study data displayed as interactive charts summarizing available clinical and genomic data. Click within a chart to filter. Additional charts may be available in the Charts menu.