Skip to main content

Advertisement

Log in

Evaluating pituitary adenomas using national research databases: systematic review of the quality of reporting based on the STROBE scale

  • Research
  • Published:
Neurosurgical Review Aims and scope Submit manuscript

Abstract

The use of national research databases has become more prevalent for studying various neurosurgical diseases. Despite the advantages of using large databases to glean clinical insight, variation remains in the methodology and reporting among studies. Using STROBE and RECORD guidelines, we evaluated the quality of reporting of the database literature investigating surgical management of benign pituitary adenomas. In this systematic review of the PubMed/MEDLINE database, we identified studies employing large national research databases of patients who underwent surgery for benign pituitary adenoma. We evaluated each of these studies using the STROBE-RECORD reporting guideline criteria to assess their quality. A total of 42 studies from 2003 to 2020 were identified for inclusion. The two raters demonstrated a κ = 0.228 with 84% overall agreement. Commonly underreported criteria included bias (discussed in 56% of studies), main result reporting (70%), subgroup analysis (69%), generalizability (68%), and funding (57%). These factors, in addition to the data sources/measurement criteria, also had the largest discrepancies between reviewers. About 20% of administrative database reviews did not accurately address bias or control for confounding variables. We found frequent underreporting of crucial information and criteria that can be challenging to identify may limit large database studies of pituitary adenomas. Improved reporting of certain criteria is critical to optimize reader understanding of large database studies. This would allow better dissemination and implementation of study findings, especially as the use of these research tools increases.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

These data are from publicly accessible databases.

References

  1. Asemota AO, Gallia GL (2019) Impact of frailty on short-term outcomes in patients undergoing transsphenoidal pituitary surgery. J Neurosurg 132:360–370. https://doi.org/10.3171/2018.8.JNS181875

    Article  PubMed  Google Scholar 

  2. Asemota AO, Ishii M, Brem H, Gallia GL (2017) Comparison of complications, trends, and costs in endoscopic vs microscopic pituitary surgery: analysis from a US health claims database. Neurosurgery 81:458–472. https://doi.org/10.1093/neuros/nyx350

    Article  PubMed  Google Scholar 

  3. Asemota AO, Ishii M, Brem H, Gallia GL (2019) Costs and Their predictors in transsphenoidal pituitary surgery. Neurosurgery 85:695–707. https://doi.org/10.1093/neuros/nyy441

    Article  PubMed  Google Scholar 

  4. Asemota AO, Ishii M, Brem H, Gallia GL (2021) Geographic variation in costs of transsphenoidal pituitary surgery in the United States. World Neurosurg 149:e1180–e1198. https://doi.org/10.1016/j.wneu.2020.02.145

    Article  PubMed  Google Scholar 

  5. Azad TD, Lee YJ, Vail D, Veeravagu A, Hwang PH, Ratliff JK, Li G (2017) Endoscopic vs. microscopic resection of sellar lesions – a matched analysis of clinical and socioeconomic outcomes. Front Surg 4:33. https://doi.org/10.3389/fsurg.2017.00033

  6. Barker FG 2nd, Klibanski A, Swearingen B (2003) Transsphenoidal surgery for pituitary tumors in the United States, 1996–2000: mortality, morbidity, and the effects of hospital and surgeon volume. J Clin Endocrinol Metab 88:4709–4719. https://doi.org/10.1210/jc.2003-030461

    Article  CAS  PubMed  Google Scholar 

  7. Bashjawish B, Patel S, Kilic S, Hsueh WD, Liu JK, Baredes S, Eloy JA (2018) Examining the “July effect” on patients undergoing pituitary surgery. Int Forum Allergy Rhinol 8:1157–1161. https://doi.org/10.1002/alr.22164

    Article  PubMed  Google Scholar 

  8. Bellazzi R (2014) Big data and biomedical informatics: a challenging opportunity. Yearb Med Inform 9:8–13. https://doi.org/10.15265/IY-2014-0024

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Benchimol EI, Smeeth L, Guttmann A, Harron K, Moher D, Petersen I, Sorensen HT, von Elm E, Langan SM, Committee RW (2015) The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. PLoS Med 12:e1001885. https://doi.org/10.1371/journal.pmed.1001885

    Article  PubMed  PubMed Central  Google Scholar 

  10. Brinjikji W, Lanzino G, Cloft HJ (2014) Cerebrovascular complications and utilization of endovascular techniques following transsphenoidal resection of pituitary adenomas: a study of the Nationwide Inpatient Sample 2001–2010. Pituitary 17:430–435. https://doi.org/10.1007/s11102-013-0521-1

    Article  CAS  PubMed  Google Scholar 

  11. Broder MS, Neary MP, Chang E, Cherepanov D, Katznelson L (2014) Treatments, complications, and healthcare utilization associated with acromegaly: a study in two large United States databases. Pituitary 17:333–341. https://doi.org/10.1007/s11102-013-0506-0

    Article  CAS  PubMed  Google Scholar 

  12. Broder MS, Neary MP, Chang E, Cherepanov D, Ludlam WH (2015) Burden of illness, annual healthcare utilization, and costs associated with commercially insured patients with Cushing disease in the United States. Endocr Pract 21:77–86. https://doi.org/10.4158/EP14126.OR

    Article  PubMed  Google Scholar 

  13. Broder MS, Neary MP, Chang E, Ludlam WH (2015) Incremental healthcare resource utilization and costs in US patients with Cushing’s disease compared with diabetes mellitus and population controls. Pituitary 18:796–802. https://doi.org/10.1007/s11102-015-0654-5

    Article  PubMed  Google Scholar 

  14. Bur AM, Brant JA, Newman JG, Hatten KM, Cannady SB, Fischer JP, Lee JY, Adappa ND (2016) Incidence and risk factors for prolonged hospitalization and readmission after transsphenoidal pituitary surgery. Otolaryngol Head Neck Surg 155:688–694. https://doi.org/10.1177/0194599816652379

    Article  PubMed  Google Scholar 

  15. Burton T, Le Nestour E, Bancroft T, Neary M (2013) Real-world comorbidities and treatment patterns of patients with acromegaly in two large US health plan databases. Pituitary 16:354–362. https://doi.org/10.1007/s11102-012-0432-6

    Article  CAS  PubMed  Google Scholar 

  16. Burton T, Le Nestour E, Neary M, Ludlam WH (2016) Algorithm development and the clinical and economic burden of Cushing’s disease in a large US health plan database. Pituitary 19:167–174. https://doi.org/10.1007/s11102-015-0695-9

    Article  PubMed  Google Scholar 

  17. Chen H, Hailey D, Wang N, Yu P (2014) A review of data quality assessment methods for public health information systems. Int J Environ Res Public Health 11:5170–5207. https://doi.org/10.3390/ijerph110505170

    Article  PubMed  PubMed Central  Google Scholar 

  18. Cheng P, Gilchrist A, Robinson KM, Paul L (2009) The risk and consequences of clinical miscoding due to inadequate medical documentation: a case study of the impact on health services funding. Health Inf Manag 38:35–46. https://doi.org/10.1177/183335830903800105

    Article  PubMed  Google Scholar 

  19. Chung SY, Sylvester MJ, Patel VR, Zaki M, Baredes S, Liu JK, Eloy JA (2018) Impact of obstructive sleep apnea in transsphenoidal pituitary surgery: an analysis of inpatient data. Laryngoscope 128:1027–1032. https://doi.org/10.1002/lary.26731

    Article  PubMed  Google Scholar 

  20. Cote DJ, Dasenbrock HH, Muskens IS, Broekman MLD, Zaidi HA, Dunn IF, Smith TR, Laws ER Jr (2017) Readmission and other adverse events after transsphenoidal surgery: prevalence, timing, and predictive factors. J Am Coll Surg 224:971–979. https://doi.org/10.1016/j.jamcollsurg.2017.02.015

    Article  PubMed  Google Scholar 

  21. Cuschieri S (2019) The STROBE guidelines. Saudi J Anaesth 13:S31–S34. https://doi.org/10.4103/sja.SJA_543_18

    Article  PubMed  PubMed Central  Google Scholar 

  22. Deb S, Vyas DB, Pendharkar AV, Rezaii PG, Schoen MK, Desai K, Gephart MH, Desai A (2019) Socioeconomic predictors of pituitary surgery. Cureus 11:e3957. https://doi.org/10.7759/cureus.3957

    Article  PubMed  PubMed Central  Google Scholar 

  23. Desai SV, Fang CH, Raikundalia MD, Baredes S, Liu JK, Eloy JA (2015) Impact of postoperative pneumonia following pituitary surgery. Laryngoscope 125:1792–1797. https://doi.org/10.1002/lary.25307

    Article  PubMed  Google Scholar 

  24. Ezzat S, Asa SL, Couldwell WT, Barr CE, Dodge WE, Vance ML, McCutcheon IE (2004) The prevalence of pituitary adenomas: a systematic review. Cancer 101:613–619. https://doi.org/10.1002/cncr.20412

    Article  PubMed  Google Scholar 

  25. Gittleman H, Ostrom QT, Farah PD, Ondracek A, Chen Y, Wolinsky Y, Kruchko C, Singer J, Kshettry VR, Laws ER, Sloan AE, Selman WR, Barnholtz-Sloan JS (2014) Descriptive epidemiology of pituitary tumors in the United States, 2004–2009. J Neurosurg 121:527–535. https://doi.org/10.3171/2014.5.JNS131819

    Article  PubMed  Google Scholar 

  26. Goljo E, Parasher AK, Iloreta AM, Shrivastava R, Govindaraj S (2016) Racial, ethnic, and socioeconomic disparities in pituitary surgery outcomes. Laryngoscope 126:808–814. https://doi.org/10.1002/lary.25771

    Article  PubMed  Google Scholar 

  27. Goshtasbi K, Lehrich BM, Abouzari M, Abiri A, Birkenbeuel J, Lan MY, Wang WH, Cadena G, Hsu FPK, Kuan EC (2020) Endoscopic versus nonendoscopic surgery for resection of pituitary adenomas: a national database study. J Neurosurg 134:816–824. https://doi.org/10.3171/2020.1.JNS193062

    Article  PubMed  PubMed Central  Google Scholar 

  28. Grossman R, Mukherjee D, Chaichana KL, Salvatori R, Wand G, Brem H, Chang DC, Quinones-Hinojosa A (2010) Complications and death among elderly patients undergoing pituitary tumour surgery. Clin Endocrinol (Oxf) 73:361–368. https://doi.org/10.1111/j.1365-2265.2010.03813.x

    Article  Google Scholar 

  29. Gurel MH, Han Y, Stevens AL, Furtado A, Cox D (2017) Treatment adherence and persistence with long-acting somatostatin analog therapy for the treatment of acromegaly: a retrospective analysis. BMC Pharmacol Toxicol 18:22. https://doi.org/10.1186/s40360-017-0124-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Hanba C, Svider PF, Jacob JT, Guthikonda M, Liu JK, Eloy JA, Folbe AJ (2017) Lower airway disease and pituitary surgery: is there an association with postoperative cerebrospinal fluid leak? Laryngoscope 127:1543–1550. https://doi.org/10.1002/lary.26364

    Article  PubMed  Google Scholar 

  31. Harbaugh CM, Cooper JN (2018) Administrative databases. Semin Pediatr Surg 27:353–360. https://doi.org/10.1053/j.sempedsurg.2018.10.001

    Article  PubMed  Google Scholar 

  32. Johnson EK, Nelson CP (2013) Values and pitfalls of the use of administrative databases for outcomes assessment. J Urol 190:17–18. https://doi.org/10.1016/j.juro.2013.04.048

    Article  PubMed  PubMed Central  Google Scholar 

  33. Kestle JR (2015) Administrative database research. J Neurosurg 122:441–442. https://doi.org/10.3171/2014.4.JNS14689

    Article  PubMed  Google Scholar 

  34. Lawrence LA, Baker AB, Nguyen SA, Karnezis TT, Soler ZM, Schlosser RJ (2016) Predictors of 30-day morbidity and mortality in transnasal microscopic pituitary tumor excision. Int Forum Allergy Rhinol 6:206–213. https://doi.org/10.1002/alr.21641

    Article  PubMed  Google Scholar 

  35. Lee CC, Kimmell KT, Lalonde A, Salzman P, Miller MC, Calvi LM, Manuylova E, Shafiq I, Edward Vates G (2016) Geographic variation in cost of care for pituitary tumor surgery. Pituitary 19:515–521. https://doi.org/10.1007/s11102-016-0738-x

    Article  PubMed  Google Scholar 

  36. Lee YJ, Wong A, Filimonov A, Sangal NR, Yeon Chung S, Hsueh WD, Baredes S, Eloy JA (2018) Impact of body mass index on perioperative outcomes of endoscopic pituitary surgery. Am J Rhinol Allergy 32:404–411. https://doi.org/10.1177/1945892418787129

    Article  PubMed  Google Scholar 

  37. Lepard J, Shank C, Agee B, Hadley M, Walters B (2019) Neurosurgical resident research education: a survey of United States residency program directors. J Neurosurg:1–10. https://doi.org/10.3171/2019.7.JNS19632

  38. Little AS, Chapple K (2013) Predictors of resource utilization in transsphenoidal surgery for Cushing disease. J Neurosurg 119:504–511. https://doi.org/10.3171/2013.1.JNS121375

    Article  PubMed  Google Scholar 

  39. Little AS, Chicoine MR, Kelly DF, Sarris CE, Mooney MA, White WL, Gardner PA, Fernandez-Miranda JC, Barkhoudarian G, Chandler JP, Prevedello DM, Liebelt BD, Sfondouris J, Mayberg MR, Group TS (2020) Evaluation of surgical resection goal and its relationship to extent of resection and patient outcomes in a multicenter prospective study of patients with surgically treated, nonfunctioning pituitary adenomas: a case series. Oper Neurosurg (Hagerstown) 18:26-33. https://doi.org/10.1093/ons/opz085

  40. Maltenfort MG (2015) Understanding large database studies. J Spinal Disord Tech 28:221. https://doi.org/10.1097/BSD.0000000000000296

    Article  PubMed  Google Scholar 

  41. McLaughlin N, Laws ER, Oyesiku NM, Katznelson L, Kelly DF (2012) Pituitary centers of excellence. Neurosurgery 71:916–924; discussion 924–916. https://doi.org/10.1227/NEU.0b013e31826d5d06

  42. Mobbs RJ (2004) The importance of the journal club for neurosurgical trainees. J Clin Neurosci 11:57–58. https://doi.org/10.1016/s0967-5868(03)00074-2

    Article  PubMed  Google Scholar 

  43. Moher D, Liberati A, Tetzlaff J, Altman DG, Group P (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 151:264-269, W264. https://doi.org/10.7326/0003-4819-151-4-200908180-00135

  44. Mortini P, Albano L, Barzaghi LR, Losa M (2021) Pituitary surgery. Presse Med:104079. https://doi.org/10.1016/j.lpm.2021.104079

  45. Muhlestein WE, Akagi DS, McManus AR, Chambless LB (2018) Machine learning ensemble models predict total charges and drivers of cost for transsphenoidal surgery for pituitary tumor. J Neurosurg 131:507–516. https://doi.org/10.3171/2018.4.JNS18306

    Article  PubMed  Google Scholar 

  46. Mukherjee D, Zaidi HA, Kosztowski T, Chaichana KL, Salvatori R, Chang DC, Quinones-Hinojosa A (2009) Predictors of access to pituitary tumor resection in the United States, 1988–2005. Eur J Endocrinol 161:259–265. https://doi.org/10.1530/EJE-09-0043

    Article  CAS  PubMed  Google Scholar 

  47. Nguyen S, Cox P, Campbell JM, Brockmeyer DL, Karsy M (2021) Evaluating the utility and quality of large administrative databases in pediatric spinal neurosurgery research. Childs Nerv Syst 37:2993–3001. https://doi.org/10.1007/s00381-021-05331-4

    Article  PubMed  Google Scholar 

  48. Oravec CS, Motiwala M, Reed K, Kondziolka D, Barker FG 2nd, Michael LM 2nd, Klimo P Jr (2018) Big data research in neurosurgery: a critical look at this popular new study design. Neurosurgery 82:728–746. https://doi.org/10.1093/neuros/nyx328

    Article  PubMed  Google Scholar 

  49. Parasher AK, Workman AD, Kidwai SM, Goljo E, Signore AD, Iloreta AM, Genden EM, Shrivastava R, Navathe A, Govindaraj S (2018) Costs in pituitary surgery: racial, socioeconomic, and hospital factors. J Neurol Surg B Skull Base 79:522–527. https://doi.org/10.1055/s-0038-1635081

    Article  PubMed  PubMed Central  Google Scholar 

  50. Patil CG, Lad SP, Harsh GR, Laws ER Jr, Boakye M (2007) National trends, complications, and outcomes following transsphenoidal surgery for Cushing’s disease from 1993 to 2002. Neurosurg Focus 23:E7. https://doi.org/10.3171/foc.2007.23.3.9

    Article  PubMed  Google Scholar 

  51. Placzek H, Xu Y, Mu Y, Begelman SM, Fisher M (2015) Clinical and economic burden of commercially insured patients with acromegaly in the United States: a retrospective analysis. J Manag Care Spec Pharm 21:1106–1112. https://doi.org/10.18553/jmcp.2015.21.12.1106

    Article  PubMed  Google Scholar 

  52. Raikundalia MD, Pines MJ, Svider PF, Baredes S, Folbe AJ, Liu JK, Eloy JA (2015) Characterization of transsphenoidal complications in patients with acromegaly: an analysis of inpatient data in the United States from 2002 to 2010. Int Forum Allergy Rhinol 5:417–422. https://doi.org/10.1002/alr.21498

    Article  PubMed  Google Scholar 

  53. Rizvi ZH, Ferrandino R, Luu Q, Suh JD, Wang MB (2019) Nationwide analysis of unplanned 30-day readmissions after transsphenoidal pituitary surgery. Int Forum Allergy Rhinol 9:322–329. https://doi.org/10.1002/alr.22241

    Article  PubMed  Google Scholar 

  54. Shahrestani S, Ballatori AM, Chen XT, Ton A, Strickland BA, Brunswick A, Zada G (2020) Analysis of modifiable and nonmodifiable risk factors in patients undergoing pituitary surgery. J Neurosurg 134:1816–1823. https://doi.org/10.3171/2020.4.JNS20417

    Article  PubMed  Google Scholar 

  55. Spinazzi EF, Pines MJ, Fang CH, Raikundalia MD, Baredes S, Liu JK, Eloy JA (2015) Impact and cost of care of venous thromboembolism following pituitary surgery. Laryngoscope 125:1563–1567. https://doi.org/10.1002/lary.25161

    Article  PubMed  Google Scholar 

  56. Svider PF, Keeley BR, Husain Q, Mauro KM, Setzen M, Liu JK, Eloy JA (2013) Regional disparities and practice patterns in surgical approaches to pituitary tumors in the United States. Int Forum Allergy Rhinol 3:1007–1012. https://doi.org/10.1002/alr.21216

    Article  PubMed  Google Scholar 

  57. Svider PF, Raikundalia MD, Pines MJ, Baredes S, Folbe AJ, Liu JK, Eloy JA (2016) Inpatient complications after transsphenoidal surgery in Cushing’s versus non-Cushing’s disease patients. Ann Otol Rhinol Laryngol 125:5–11. https://doi.org/10.1177/0003489415595424

    Article  PubMed  Google Scholar 

  58. Swearingen B, Wu N, Chen SY, Pulgar S, Biller BM (2011) Health care resource use and costs among patients with Cushing disease. Endocr Pract 17:681–690. https://doi.org/10.4158/EP10368.OR

    Article  PubMed  Google Scholar 

  59. van Walraven C, Bennett C, Jennings A, Austin PC, Forster AJ (2011) Proportion of hospital readmissions deemed avoidable: a systematic review. CMAJ 183:E391-402. https://doi.org/10.1503/cmaj.101860

    Article  PubMed  PubMed Central  Google Scholar 

  60. Vandenbroucke JP, von Elm E, Altman DG, Gotzsche PC, Mulrow CD, Pocock SJ, Poole C, Schlesselman JJ, Egger M, Initiative S (2007) Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. PLoS Med 4:e297. https://doi.org/10.1371/journal.pmed.0040297

    Article  PubMed  PubMed Central  Google Scholar 

  61. Vlasak AL, Shin DH, Kubilis PS, Roper SN, Karachi A, Hoh BL, Rahman M (2020) Comparing standard performance and outcome measures in hospitalized pituitary tumor patients with secretory versus nonsecretory tumors. World Neurosurg 135:e510–e519. https://doi.org/10.1016/j.wneu.2019.12.059

    Article  PubMed  Google Scholar 

  62. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP (2007) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 370:1453–1457. https://doi.org/10.1016/s0140-6736(07)61602-x

    Article  Google Scholar 

  63. Wallace DR, Kuhn DR (2011) Failure modes in medical device software: an analysis of 15 years of recall data. Int J Reliab Qual Saf Eng 08:351–371. https://doi.org/10.1142/s021853930100058x

    Article  Google Scholar 

  64. Wilson D, Jin DL, Wen T, Carmichael JD, Cen S, Mack WJ, Zada G (2015) Demographic factors, outcomes, and patient access to transsphenoidal surgery for Cushing’s disease: analysis of the Nationwide Inpatient Sample from 2002 to 2010. Neurosurg Focus 38:E2. https://doi.org/10.3171/2014.11.FOCUS14694

    Article  PubMed  Google Scholar 

  65. Wong A, Filimonov A, Lee YJ, Hsueh WD, Baredes S, Liu JK, Eloy JA (2018) The impact of resident and fellow participation in transsphenoidal pituitary surgery. Laryngoscope 128:2707–2713. https://doi.org/10.1002/lary.27349

    Article  PubMed  Google Scholar 

  66. Yolcu Y, Wahood W, Alvi MA, Kerezoudis P, Habermann EB, Bydon M (2020) Reporting methodology of neurosurgical studies utilizing the American College of Surgeons-National Surgical Quality Improvement Program Database: a systematic review and critical appraisal. Neurosurgery 86:46–60. https://doi.org/10.1093/neuros/nyz180

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank Kristin Kraus for editorial assistance.

Author information

Authors and Affiliations

Authors

Contributions

Khan, Yu, and Yost completed the analysis. Khan, Yu, Yost, Cutler, Henson, Azab, Colby, and Karsy wrote and edited the main manuscript text. Karsy supervised the work. Khan, Yu, Yost, Cutler, Henson, Azab, Colby, and Karsy reviewed the manuscript.

Corresponding author

Correspondence to Michael Karsy.

Ethics declarations

Ethical approval and consent to participate

This was a study of the published literature, so no ethical approval or consent to participate is required.

Human and animal ethics

Not applicable.

Consent for publication

Not applicable.

Competing interests

Karsy has received royalties from Thieme Medical Publishing. The other authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khan, M., Yost, S., Yu, S. et al. Evaluating pituitary adenomas using national research databases: systematic review of the quality of reporting based on the STROBE scale. Neurosurg Rev 45, 3801–3815 (2022). https://doi.org/10.1007/s10143-022-01888-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10143-022-01888-z

Keywords

Navigation