{"as_of":"2026-08-20T17:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:784a67a64bc1161d35fc4b7986613f2dc0edc88e0ca60519e8f4da8c0dddfda1","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T13:33:59.477627Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.13234/citation-record","integrity":"/paper/2412.13234/integrity","json":"/paper/2412.13234/citation-record.json","paper":"/paper/2412.13234"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/ijc.34473","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:03:20.376878Z","title":"The evidence base of US Food and Drug Administration approvals of novel cancer therapies from 2000 to 2020","venue":"International Journal of Cancer","work_id":"cfe78e3c-59c8-4a04-8030-565519b79512","year":2000},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.317404Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:79a1ce44646dc96e22ddf8f0d134309e6b93253b5c25861ef59003f7f6e2e4e3","observation_id":"60199fde-7eb5-4916-ab85-6a8e7f26e92d","resolution":{"observed_at":"2026-08-11T13:33:59.842429Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.321329Z","title":"Cancer statistics, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.321329Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:91f9e19dcb0e5bad942b619c83e08e338a5ca128ef6062ec098c0014f548b53f","observation_id":"387e50aa-c4eb-49f5-b3aa-1620f1f3cd8c","resolution":{"observed_at":"2026-08-11T13:33:59.321329Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.urolonc.2022.05.028","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.819605Z","title":"Inﬂuence of ﬁrst-line chemotherapy regimen on survival outcomes of patients with advanced urothelial carcinoma who received second-line immune checkpoint inhibitors","venue":null,"work_id":"2dde0b66-829d-41f4-9800-30dc2caf69d0","year":2022},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.324764Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:b726e06f7ded5009418059521e7c00826b0477a34ca467c20ed7158c9f357105","observation_id":"07610f60-c0da-422e-8a8a-4eb5979fd77a","resolution":{"observed_at":"2026-08-11T13:33:59.823823Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1200/jco.2016.69.6336","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.808124Z","title":"Cost- Effectiveness of Immune Checkpoint Inhibition in BRAF Wild-Type Advanced Melanoma","venue":null,"work_id":"c3cf38a3-0342-48b7-9b1f-dcf464572978","year":2017},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.328911Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:18ed24b86c4a280fdb95f069f96a20b6093236887b79ef177781fc393c9d5a8b","observation_id":"cc970c51-6c89-4731-be7d-88706d770e83","resolution":{"observed_at":"2026-08-11T13:33:59.812367Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/ajhp/zxaa197","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.797671Z","title":"Optimal sequencing strategies in the treatment of EGFR mutation– positive non–small cell lung cancer: Clinical beneﬁts and cost-effectiveness","venue":null,"work_id":"055910af-ce04-4876-a274-a782ee8e56f4","year":2020},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.333510Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:9881df629cdb5ef76497a457e6c7610709182dab22d25193f0a8202ae0ee5b19","observation_id":"b3d47253-9e93-434e-8687-baae81da9147","resolution":{"observed_at":"2026-08-11T13:33:59.801369Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.10514","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:34:00.515181Z","title":null,"venue":null,"work_id":"c5c15119-827b-4c3b-93b4-a7b4fa48a1bc","year":2023},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.338073Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:ca2f65d271eb526427805c420546633697a12c0f85d45a18005b93ba6c2b72b3","observation_id":"0db5c772-c752-4c8b-8b75-6f3eda5531bf","resolution":{"observed_at":"2026-08-11T13:34:00.519630Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10549-016-3978-6","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-19T11:03:45.297681Z","title":"Cost-effectiveness analysis of 1st through 3rd line sequential targeted therapy in HER2-positive metastatic breast cancer in the United States","venue":"Breast Cancer Research and Treatment","work_id":"d0967447-7987-43d3-854b-9e1875c44308","year":2016},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.343380Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:d9e8176b089909f0da87d4f067a29cc7f0b8c649ab5a3121c507f1569733a249","observation_id":"aacf0430-1be9-448b-b309-c435a035ee1c","resolution":{"observed_at":"2026-08-11T13:33:59.791209Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.breast.2019.11.012","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.776933Z","title":"A cost-effectiveness analysis of trastuzumab-containing treatment sequences for HER-2 positive metastatic breast cancer patients in Taiwan","venue":null,"work_id":"0a4a95b0-2d81-4b03-b5f1-e9367efd5e88","year":2020},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.347204Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:ddb0722365c6ce5af71d2263f6e6cb3b9fa3c9e01dedc48f842e40808c12ab1b","observation_id":"5eedf5e0-b946-4a8c-9577-471b79240b34","resolution":{"observed_at":"2026-08-11T13:33:59.780588Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1200/jop","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:34:00.449315Z","title":"Cost-Effectiveness Analysis of Different Sequences of the Use of Epidermal Growth Factor Receptor Inhibitors for Wild-Type KRAS Unresectable Metastatic Colorectal Cancer","venue":null,"work_id":"14d27c2b-182b-4d7f-93f7-e685da6f4982","year":2016},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.350833Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:4a16ca846150a49df254d50a26c0e1dd735c7451df20bbf6cd8ca36d214b3ec5","observation_id":"f695d477-d7d6-4873-aae4-628c146bda97","resolution":{"observed_at":"2026-08-11T13:34:00.452716Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.354311Z","title":"State-Transition Modeling: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.354311Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:e409f23bcb4a73a875be8866426dc74cad59e5ad7807544c3026d8c8f81ed7f1","observation_id":"e3b31f10-a44d-48e9-aad3-d49a65c769ef","resolution":{"observed_at":"2026-08-11T13:33:59.354311Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1177/0272989x18754513","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.760540Z","title":"Microsimulation modeling for health decision sciences using R: a tutorial","venue":null,"work_id":"fc7bb6b4-7078-4322-8c53-a11bef370e94","year":2018},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.357978Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:b0f54daa1a13772bbbca22c4cb0ff74ab6d5e0201741d3d1e2e139dabe7099ef","observation_id":"203b875c-6ae9-4cb4-bc7d-04cb83b76560","resolution":{"observed_at":"2026-08-11T13:33:59.764406Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"6998.2019","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:34:00.157333Z","title":"Cohort versus patient level simulation for the economic evaluation of single versus combination immuno-oncology therapies in metastatic melanoma","venue":null,"work_id":"0f163636-3af6-4154-84fc-6e5a6784c576","year":2019},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.361639Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:e7a2fb5fa37f5715af02bae44288d35e4580ca114118a9bf47a6a99f95f2966e","observation_id":"3143f673-d453-42fa-8a57-ff9d36d24318","resolution":{"observed_at":"2026-08-11T13:34:00.162523Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.34196/ijm.00175","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.749086Z","title":"A Brief, Global History of Microsimulation Models in Health: Past Applications, Lessons Learned and Future Directions","venue":null,"work_id":"6c5a24c8-ab3e-4b35-b5f5-28f04185f3a2","year":2017},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.365203Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:bcf15a60e7274086ccf14b639511370d537e76d0b1bdb931e1fc6b545ada4493","observation_id":"4e17f87d-f310-4cd9-a36b-67d65cbe7df5","resolution":{"observed_at":"2026-08-11T13:33:59.753315Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1177/0272989x231201621","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.737228Z","title":"Cost-Effectiveness Analysis for Therapy Sequence in Advanced Cancer: A Microsimulation Approach with Application to Metastatic Prostate Cancer","venue":null,"work_id":"e9597a57-2650-415b-a2c0-5d878974df9f","year":2023},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.369870Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:87aeaafa6963bcbd01e7b29b05ccd11b2274312038fc5566ba135c61c4222662","observation_id":"18220b1b-1190-4572-bc96-cfaf11cb5c3f","resolution":{"observed_at":"2026-08-11T13:33:59.741180Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/annonc/mdr156","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.725432Z","title":"Comparative effectiveness of cisplatin-based and carboplatin-based chemotherapy for treatment of advanced urothelial carcinoma","venue":null,"work_id":"793447e2-c46b-4c41-9eac-a419d62c58b1","year":2012},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.373760Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:ceacd2f800029ca1685a20176040f8a0bd9754f50b19bf45008d4c479235f881","observation_id":"e78621de-1eda-4d54-8bf7-ff604c48608f","resolution":{"observed_at":"2026-08-11T13:33:59.729464Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1101/2020.03.16.20037143","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.714511Z","title":"Comparison of Population Characteristics in Real-World Clinical Oncology Databases in the US: Flatiron Health, SEER, and NPCR","venue":null,"work_id":"4a793af9-b696-4b05-b49c-b3ec6e728372","year":2023},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.377359Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:801e96c1ba5322177f68e343039584d33854c64451737b7803cd2fab15508878","observation_id":"b7761051-0131-42ee-9b59-5670bc875165","resolution":{"observed_at":"2026-08-11T13:33:59.718161Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.09765","last_updated":"2020-01-13T22:58:48Z","snapshot_observed_at":"2026-08-20T07:16:06.647126Z","submitted_at":"2020-01-13T22:58:48Z","title":"Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research","version":1},"cited_work":{"arxiv_id":"2001.09765","doi":"10.48550/arxiv.2001.09765","metadata_source":"pith","pith_arxiv_id":"2001.09765","snapshot_observed_at":"2026-08-11T18:16:15.004306Z","title":"Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research","venue":"cs.CY","work_id":"44c81311-1f4e-4170-8d48-33f67294b9b3","year":2020},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.380875Z"},"links":{"cited_paper":"/paper/2001.09765","citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:bcd26046e8b8412eab08e9a8e2028c2b199430abb71a0b4749a127866063db74","observation_id":"c10cb40d-011b-466c-b051-900e825cf062","resolution":{"observed_at":"2026-08-11T13:33:59.708006Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.385254Z","title":"Tutorial in biostatistics: competing risks and multi- state models","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.385254Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:3072efc24b4e02605693d2c601189a8d7ec68f5ece9302943e927c16ba00a8e0","observation_id":"a519d23e-f62c-4db5-84b4-138e622d467e","resolution":{"observed_at":"2026-08-11T13:33:59.385254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.388965Z","title":"mstate: An R Package for the Analysis of Competing Risks and Multi-State Models","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.388965Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:670b670bbee1648b7c657506f0838f1ec49cd5d702c16e781a796e49e57252a8","observation_id":"d9470a70-f398-4bc7-b6ab-aedac077f1b4","resolution":{"observed_at":"2026-08-11T13:33:59.388965Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.392721Z","title":"Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.392721Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:e99320c7d3ed2543d498a3a3915bd5ea713a8593edb96be8fcf202652b86ef90","observation_id":"575a2915-f973-4a35-898d-a9124b2ce5a0","resolution":{"observed_at":"2026-08-11T13:33:59.392721Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/pds.5639","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:03:20.376878Z","title":"Differences in target estimands between different propensity score- based weights","venue":"Pharmacoepidemiology and Drug Safety","work_id":"6d3002a4-0466-43cb-b703-6b5eed9545e5","year":2023},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.396198Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:c555dd6c8ba7bb51f922e73286e2b363c2ecba8f86fa56ef26605b583d48ed85","observation_id":"86977154-1952-499b-b189-8763a6b435df","resolution":{"observed_at":"2026-08-11T13:33:59.676545Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.400045Z","title":"Propensity score estimation: machine learning and classiﬁcation methods as alternatives to logistic regression","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.400045Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:212ca7d3091d55066ff42ee462648b85ab78cc3a7d32e010e07152dc49b78660","observation_id":"0cee78d8-0da2-4f0f-8e07-2cbf8a23f59e","resolution":{"observed_at":"2026-08-11T13:33:59.400045Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.cmpb.2012.09.003","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.654732Z","title":"A simulation procedure based on copulas to generate clustered multi-state survival data","venue":null,"work_id":"3c2c05b1-6d78-4e61-8166-8a1f514f19ec","year":2013},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.403453Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:6321504278f1550367f20676e7c756a44fd483619ffc59d6d25519891748b0a1","observation_id":"989c4292-3e64-4897-9341-58eee842c95b","resolution":{"observed_at":"2026-08-11T13:33:59.659210Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:34:00.547119Z","title":"Modelling Dependence with Copulas in R | R-bloggers","venue":null,"work_id":"f5b59a1d-688f-4831-a234-9072b2d1aa04","year":2015},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.407307Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:77b1fe58e216b2c0d35784743fa1f15f5a877d8e80e071804bedc97db283eca4","observation_id":"49d9a322-baa9-4240-bb64-6968cdc04348","resolution":{"observed_at":"2026-08-11T13:34:00.550712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-319-43742-2_24","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-13T11:03:48.094449Z","title":"Markov Models and Cost Effectiveness Analysis: Applications in Medical Research","venue":null,"work_id":"aa8f4099-c1dd-4155-b015-9eef451f3125","year":2016},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.410499Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:267a15441ea2179d6a75b0854b32a1c97a4a6274c3d280c66402d6815d92a24d","observation_id":"818a159d-ced9-4a9f-a854-2656c6a8180e","resolution":{"observed_at":"2026-08-11T13:33:59.647728Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s12325-022-02091-8","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-20T11:03:42.707129Z","title":"Analysis of a Real-World Progression Variable and Related Endpoints for Patients with Five Different Cancer Types","venue":"Advances in Therapy","work_id":"0332649f-8c5b-48ef-9cef-ce5f976c8b98","year":2022},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.413366Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:39a4fc4179cc69c26d89c1371b292c369e18b3f799fc5792cb40c8cbd63e7ea2","observation_id":"c2bac506-5ac6-4c35-a0ef-e2beea7c5af8","resolution":{"observed_at":"2026-08-11T13:33:59.637843Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.clgc.2022.10.001","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.624072Z","title":"Avelumab Maintenance Treatment After First-line Chemotherapy in Advanced Urothelial Carcinoma–A Cost-Effectiveness Analysis","venue":null,"work_id":"be30bad1-8bf4-4c21-bbd2-b4acfc217ace","year":2023},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.416510Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:54f4a85b3562f1135173ec3b9ccf091231347f37b35acf871f7896ac93009355","observation_id":"00f3eec9-1967-40a8-ab41-c8d66cd80418","resolution":{"observed_at":"2026-08-11T13:33:59.627754Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1186/s12955-018-1077-6","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.612990Z","title":"Quality of life in bladder cancer patients receiving medical oncological treatment; a systematic review of the literature","venue":null,"work_id":"e78e0256-b6a7-4cdc-aedf-e458e8a541d3","year":2019},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.420006Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:495b4313d9c95df1ad1c6d417d76836d0eb28403eb419a06ec5654529eb1db4a","observation_id":"a89e3db4-8c83-46fb-999b-36be6497eb20","resolution":{"observed_at":"2026-08-11T13:33:59.617839Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[{"edge_observation":{"observed_at":"2026-08-11T18:18:05.448406+00:00","source":"paper_reference_links","state":"open"},"event_date":"2020-01-23","event_type":"correction","notice_doi":"10.1186/s12955-019-1247-1","provenance":{"observed_at":"2026-07-11T03:01:30.67789+00:00","source":"crossref","source_record_id":"10.1186/s12955-019-1247-1->10.1186/s12955-018-1077-6:correction"}}],"reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.euo.2018.09.009","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.602498Z","title":"Cost-effectiveness of Pembrolizumab for Patients with Advanced, Unresectable, or Metastatic Urothelial Cancer Ineligible for Cisplatin- based Therapy","venue":null,"work_id":"bf445e1e-4c02-445b-9efd-906f9a4aa6bd","year":2019},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.423132Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:8ccf64112d920cda77b8b26fd24647b6ab96ed8ce75eed03b06f3aa9600c6c98","observation_id":"9870b5bf-3625-48f3-acc4-492e71f667b0","resolution":{"observed_at":"2026-08-11T13:33:59.606249Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.eururo.2018.03.006","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.592549Z","title":"Cost-effectiveness of Pembrolizumab in Second-line Advanced Bladder Cancer","venue":null,"work_id":"a512a996-13ff-40f4-9285-4c91800faf4e","year":2018},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.426917Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:563d603677d3363af4c789cb80dcb01224d50d0766129ecce12c6f0aacb3981c","observation_id":"64bb2b06-b346-4906-b14b-53eac204af90","resolution":{"observed_at":"2026-08-11T13:33:59.596107Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.eururo.2006.12.029","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.582427Z","title":null,"venue":null,"work_id":"f14d3f79-029c-4fa7-9ca4-6df93e677a94","year":2007},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.431070Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:df7fd05a75b664fb0da6c38e7e2875f4ee838efb66bece4c08a2463b7f1a6fa7","observation_id":"23c52861-32f1-43f1-8643-aed04ce4bce0","resolution":{"observed_at":"2026-08-11T13:33:59.586008Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:34:00.536344Z","title":"Pembrolizumab as Second-Line Therapy for Advanced Urothelial Carcinoma","venue":null,"work_id":"5e32083e-ad9a-48bc-8fbf-15976440567a","year":2017},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.434810Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:e6198bf96be5084783f7cff9af4091ac0db41362cbdedf7f95bf50a608bb9bda","observation_id":"20c0800a-de9c-4c17-8d08-278128b3d900","resolution":{"observed_at":"2026-08-11T13:34:00.540520Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:34:00.525260Z","title":"Accessed November 7, 2024","venue":null,"work_id":"67103af6-a0b0-4425-8797-a2f518321ad5","year":2024},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.443269Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:d28dda28882f6703074615fb80e3064b7fd421d4f9cc3d7e78e88152d714ed4c","observation_id":"4d06331d-1ce0-4451-b36f-e5125b6e1527","resolution":{"observed_at":"2026-08-11T13:34:00.528467Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.clgc.2020.07.006","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.560775Z","title":null,"venue":null,"work_id":"a72b9354-5f5f-429e-8d45-c2909743770e","year":2021},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.447039Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:9aa5883f2de3da29ff70d67803ebf365bb0d101a180699a26c4dced3a986f005","observation_id":"f10c88c0-8ef5-4ba6-8eda-539225711e9f","resolution":{"observed_at":"2026-08-11T13:33:59.564784Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"6998.2020","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:34:00.089545Z","title":"The cost effectiveness of pembrolizumab versus chemotherapy or atezolizumab as second-line therapy for advanced urothelial carcinoma in the United States","venue":null,"work_id":"817d8c0d-d26a-4a52-8bc7-f9592c339f6c","year":2020},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.451238Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:593d247073b2923db72704f1f5cb2997d99f7b4910ab445252fdd43e2223a06a","observation_id":"28af06d2-bce8-40f3-9f58-773669d41142","resolution":{"observed_at":"2026-08-11T13:34:00.095564Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1055/s-0039-1677738","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.550414Z","title":"Using Electronic Health Records to Identify Adverse Drug Events in Ambulatory Care: A Systematic Review","venue":null,"work_id":"96b75be2-1d3a-4432-98ec-8cc66db15f90","year":2019},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.455032Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:3a8f9cc511cb88d9ea2df6191fd29d02f649f852c83ac41155d6a9224c70f95e","observation_id":"f6f91b4e-685c-451c-aab4-8253aa096294","resolution":{"observed_at":"2026-08-11T13:33:59.553810Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1200/cci.20.00109","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.538852Z","title":"Automated Identiﬁcation of Patients With Immune-Related Adverse Events From Clinical Notes Using Word Embedding and Machine Learning","venue":null,"work_id":"f84adf50-a746-4af1-93d3-cff8100e3ed2","year":2021},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.458769Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:8ad95303bf931c6ac979a0419a42a0dc73738d00934438c9695248bd9990a3fa","observation_id":"5e77ab4a-3779-4eae-a4fa-546c336d941e","resolution":{"observed_at":"2026-08-11T13:33:59.543195Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s40273-015-0309-4","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-20T11:03:42.707129Z","title":"Dealing with Time in Health Economic Evaluation: Methodological Issues and Recommendations for Practice","venue":"PharmacoEconomics","work_id":"14a983f4-a06a-4a15-bff4-40d413fe2230","year":2015},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.462353Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:5b777688c19393acd1a2112d8a1cd6fd3885093643ec1058e318923998dd093b","observation_id":"a8977a12-3360-4089-b13e-09076ae137e8","resolution":{"observed_at":"2026-08-11T13:33:59.531819Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.466677Z","title":"A Proportional Hazards Model for the Subdistribution of a Competing Risk","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.466677Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:8295049bac9834cff44b6cb5eecd502fad0acb3b87ac3c39de191446c18fbadf","observation_id":"f6a0b32b-d793-4375-8746-9381d6044e59","resolution":{"observed_at":"2026-08-11T13:33:59.466677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/sim.9023","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T11:03:20.376878Z","title":"Fine-Gray subdistribution hazard models to simultaneously estimate the absolute risk of different event types: Cumulative total failure probability may exceed 1","venue":"Statistics in Medicine","work_id":"f19e8a76-b902-4de2-b0ac-e5d1b057d0d9","year":2021},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.470415Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:6e826e6c1c3edf6e1d0b4d32f27ee580e6cfa9e12819c8d4389e7ef56a7e3177","observation_id":"b1fb377f-4aff-4d96-98cb-03003529b157","resolution":{"observed_at":"2026-08-11T13:33:59.521394Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18637/jss.v089.i09","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.503825Z","title":"Bayesian, and Non-Bayesian, Cause-Speciﬁc Competing-Risk Analysis for Parametric and Nonparametric Survival Functions: The R Package CFC","venue":null,"work_id":"fa04cfec-8e9e-4f7d-b749-40b28112db5e","year":2019},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.473882Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:1442eedb439f321b4639912156b0a779fbcf9519e93cd8eca0b641516762987d","observation_id":"4d2729f1-0b8a-4b4d-b3e0-93d426e51c8e","resolution":{"observed_at":"2026-08-11T13:33:59.509216Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2021.14723","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.900007Z","title":"Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer","venue":null,"work_id":"5249a4e1-cd64-4817-ae98-e40b0eaedd7d","year":2021},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.477627Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:8588eea7fe6f3c64f4d922ca86c992ff1bf5720d76f0b541b00e494af637ca0a","observation_id":"2956726b-8c5b-4b52-b08f-5a87a566d880","resolution":{"observed_at":"2026-08-11T13:33:59.905115Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1056/nejmoa1613683","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:33:59.571975Z","title":null,"venue":null,"work_id":"f2b1a8c5-2527-4b46-9ba8-03ee780d869e","year":null},"citing_paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data","version":2},"reference_index":1026,"source":"pdf_text","source_observed_at":"2026-08-11T13:33:59.438631Z"},"links":{"citing_paper":"/paper/2412.13234"},"observation_digest":"sha256:259602ace3c7e645e39425f7106c3b125f703a9da28e8d1728462565d129616b","observation_id":"e4d8d1e0-65aa-4e40-84aa-86c92a4709cb","resolution":{"observed_at":"2026-08-11T13:33:59.575860Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.13234","last_updated":"2024-12-19T17:53:18Z","latest_version":2,"primary_category":"q-bio.QM","snapshot_observed_at":"2026-08-15T09:53:52.041174Z","submitted_at":"2024-12-17T16:10:17Z","title":"Modeling therapy sequence for advanced cancer: A microsimulation approach leveraging Electronic Health Record data"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":1,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":7,"verified_exact":31,"verified_fuzzy":3},"total_outbound_references":43},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2412.13234."}