Dataset Viewer
Auto-converted to Parquet Duplicate
patient_id
stringclasses
500 values
day
int64
0
728
visit_type
stringclasses
2 values
ctdna_vaf
float64
0
0.57
⌀
exhaustion_marker
float64
0
1
⌀
sod_rel
float64
0
235
⌀
BSC-SIM-0001
0
blood
0.02299
0.1718
null
BSC-SIM-0001
0
imaging
null
null
0.9797
BSC-SIM-0001
14
blood
0.021425
0.1597
null
BSC-SIM-0001
28
blood
0.023126
0.228
null
BSC-SIM-0001
42
blood
0.024398
0.3079
null
BSC-SIM-0001
56
blood
0.02471
0.3154
null
BSC-SIM-0001
56
imaging
null
null
1.0327
BSC-SIM-0001
84
blood
0.029468
0.4416
null
BSC-SIM-0001
98
blood
0.029909
0.4773
null
BSC-SIM-0001
112
blood
0.033932
0.437
null
BSC-SIM-0001
112
imaging
null
null
1.095
BSC-SIM-0001
126
blood
0.036347
0.5577
null
BSC-SIM-0001
140
blood
0.037475
0.5271
null
BSC-SIM-0001
154
blood
0.046311
0.5196
null
BSC-SIM-0001
168
blood
0.051095
0.5731
null
BSC-SIM-0001
168
imaging
null
null
1.5998
BSC-SIM-0001
182
blood
0.055276
0.636
null
BSC-SIM-0001
196
blood
0.058638
0.6312
null
BSC-SIM-0001
210
blood
0.069911
0.7174
null
BSC-SIM-0001
224
blood
0.079523
0.6833
null
BSC-SIM-0001
224
imaging
null
null
1.4087
BSC-SIM-0001
238
blood
0.092675
0.726
null
BSC-SIM-0001
252
blood
0.113492
0.7276
null
BSC-SIM-0001
266
blood
0.121594
0.6896
null
BSC-SIM-0001
280
blood
0.135239
0.7513
null
BSC-SIM-0001
280
imaging
null
null
2.0451
BSC-SIM-0001
294
blood
0.176569
0.6935
null
BSC-SIM-0001
308
blood
0.223518
0.771
null
BSC-SIM-0001
322
blood
0.243967
0.9092
null
BSC-SIM-0001
336
blood
0.313814
0.8816
null
BSC-SIM-0001
336
imaging
null
null
2.4832
BSC-SIM-0001
350
blood
0.375043
0.8319
null
BSC-SIM-0001
364
blood
0.403954
0.8537
null
BSC-SIM-0001
378
blood
0.498946
0.8625
null
BSC-SIM-0001
392
blood
0.508001
0.9168
null
BSC-SIM-0001
392
imaging
null
null
3.1387
BSC-SIM-0001
406
blood
0.525079
0.9621
null
BSC-SIM-0001
420
blood
0.502233
0.9089
null
BSC-SIM-0001
434
blood
0.509572
0.8927
null
BSC-SIM-0001
448
blood
0.516813
0.8622
null
BSC-SIM-0001
448
imaging
null
null
4.1125
BSC-SIM-0001
462
blood
0.498352
0.8092
null
BSC-SIM-0001
476
blood
0.468312
0.9666
null
BSC-SIM-0001
490
blood
0.528403
0.7646
null
BSC-SIM-0001
504
blood
0.534925
0.8954
null
BSC-SIM-0001
504
imaging
null
null
5.0493
BSC-SIM-0001
532
blood
0.499329
0.8575
null
BSC-SIM-0001
546
blood
0.534042
0.8786
null
BSC-SIM-0001
560
blood
0.50628
0.9804
null
BSC-SIM-0001
560
imaging
null
null
6.4329
BSC-SIM-0001
574
blood
0.487959
0.7997
null
BSC-SIM-0001
588
blood
0.509189
0.8234
null
BSC-SIM-0001
602
blood
0.511045
0.8144
null
BSC-SIM-0001
616
blood
0.507938
0.8766
null
BSC-SIM-0001
616
imaging
null
null
9.0984
BSC-SIM-0001
644
blood
0.480908
0.9221
null
BSC-SIM-0001
658
blood
0.511115
0.8271
null
BSC-SIM-0001
672
blood
0.519079
0.8292
null
BSC-SIM-0001
672
imaging
null
null
11.7355
BSC-SIM-0001
686
blood
0.526183
0.9781
null
BSC-SIM-0001
700
blood
0.485329
0.811
null
BSC-SIM-0001
714
blood
0.496319
0.8553
null
BSC-SIM-0001
728
blood
0.50876
0.8265
null
BSC-SIM-0001
728
imaging
null
null
14.048
BSC-SIM-0002
0
blood
0.038573
0.2349
null
BSC-SIM-0002
0
imaging
null
null
0.8642
BSC-SIM-0002
14
blood
0.03129
0.2037
null
BSC-SIM-0002
28
blood
0.027474
0.2643
null
BSC-SIM-0002
42
blood
0.022619
0.3022
null
BSC-SIM-0002
56
blood
0.020567
0.2809
null
BSC-SIM-0002
56
imaging
null
null
0.8461
BSC-SIM-0002
70
blood
0.017406
0.2031
null
BSC-SIM-0002
84
blood
0.016291
0.3151
null
BSC-SIM-0002
98
blood
0.01411
0.3497
null
BSC-SIM-0002
112
blood
0.013203
0.2431
null
BSC-SIM-0002
112
imaging
null
null
0.8126
BSC-SIM-0002
126
blood
0.011219
0.3072
null
BSC-SIM-0002
140
blood
0.010183
0.3272
null
BSC-SIM-0002
154
blood
0.009172
0.3111
null
BSC-SIM-0002
168
blood
0.008202
0.3194
null
BSC-SIM-0002
168
imaging
null
null
0.5688
BSC-SIM-0002
182
blood
0.007507
0.3266
null
BSC-SIM-0002
196
blood
0.006276
0.2782
null
BSC-SIM-0002
210
blood
0.00592
0.3031
null
BSC-SIM-0002
224
imaging
null
null
0.6093
BSC-SIM-0002
238
blood
0.004169
0.2171
null
BSC-SIM-0002
252
blood
0.004264
0.2979
null
BSC-SIM-0002
266
blood
0.003309
0.2391
null
BSC-SIM-0002
280
blood
0.003196
0.1421
null
BSC-SIM-0002
280
imaging
null
null
0.4249
BSC-SIM-0002
294
blood
0.002746
0.2075
null
BSC-SIM-0002
322
blood
0.001951
0.2027
null
BSC-SIM-0002
336
blood
0.001727
0.2325
null
BSC-SIM-0002
336
imaging
null
null
0.3317
BSC-SIM-0002
350
blood
0.00161
0.2532
null
BSC-SIM-0002
364
blood
0.001354
0.3111
null
BSC-SIM-0002
378
blood
0.001051
0.209
null
BSC-SIM-0002
392
blood
0.000884
0.2319
null
BSC-SIM-0002
392
imaging
null
null
0.2732
BSC-SIM-0002
420
blood
0.000701
0.176
null
End of preview. Expand in Data Studio

bsc-simulated-nsclc-sample

A sample of 500 simulated non-small cell lung cancer (NSCLC) patients on immunotherapy, with serial circulating tumor DNA (ctDNA) draws and imaging over two years. It shows the data format used to evaluate the BSC Engine.

Simulated data only. No row is a real patient, and the data contains no protected health information. Nothing here is suitable for clinical use.

What's included and what isn't

  • Included: patient baseline characteristics and every visit observation (blood draws and scans).
  • Not included: the ground truth (true resistance-onset day and progression status), the simulator, and the engine. Those are part of the BSC Engine, which Scalar Logic Group, LLC is offering for acquisition (info@scalarlogicgroup.com).

The patients were drawn at random from one of the two 10,000-patient reference cohorts behind the v8 results (preprint v8) and given new IDs.

Files

patients.csv — one row per patient (500 rows)

Column Description
patient_id Sample ID, BSC-SIM-0001 to BSC-SIM-0500
age_at_diagnosis Age in years
pd_l1_expression_pct PD-L1 tumor proportion score, %
treatment_regimen Immunotherapy regimen

visits.csv — one row per visit (32,228 rows)

Column Description
patient_id Links to patients.csv
day Days since treatment start (0–728)
visit_type blood (every 14 days; about 5% of draws are missing, as in real follow-up) or imaging (every 56 days)
ctdna_vaf Blood visits: mean variant allele fraction across 16 tracked variants. 0 means not detected (below a limit of detection of 0.01% VAF)
exhaustion_marker Blood visits: simulated T-cell exhaustion marker, scaled 0–1
sod_rel Imaging visits: sum of target-lesion diameters relative to baseline (1.0 = baseline)

How it was generated

  • Tumor dynamics. A mechanistic simulator models competing tumor clones and immune exhaustion with a power-law memory kernel, so resistance builds up gradually rather than switching on at once.
  • Assay noise. Measured ctDNA follows a proportional noise model: CV of 25%, 12%, 8% and 4% at 0.1%, 0.5%, 1% and 5% VAF, 16 tracked variants, and 4% draw-to-draw pre-analytical variation. Baseline VAF has a median of 1.2%, and 12.4% of patients are non-detectable at baseline. These noise parameters have not yet been confirmed with vendor validation data.
  • Imaging. Scans record lesion size with measurement noise. Progression is typically called by a RECIST-style rule: at least 1.2 × nadir and at least 5% absolute.

Appropriate uses

  • Testing pipelines, schemas and ingestion code for serial ctDNA and imaging data
  • Exploring the data format before discussing the BSC Engine
  • Teaching longitudinal liquid-biopsy data

Not appropriate for

  • Benchmarking or validating a model (there's no ground truth here)
  • Any clinical or diagnostic use

License

CC BY-NC 4.0: free for non-commercial use with credit to Scalar Logic Group, LLC. For commercial use, contact info@scalarlogicgroup.com.

Related

Downloads last month
38