1 / 56

Funding Source

Funding Source. Lung Cancer Surgery: Decisions Against Life Saving Care Sponsored by the American Cancer Society Grant #: RSGPB-05-217-01-CPPB. Racial Disparities in the Treatment  of Early Stage Lung Cancer: Which Interventions Will Work?  . Case 1.

neil
Download Presentation

Funding Source

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Funding Source Lung Cancer Surgery: Decisions Against Life Saving Care Sponsored by the American Cancer Society Grant #: RSGPB-05-217-01-CPPB

  2. Racial Disparities in the Treatment  of Early Stage Lung Cancer: Which Interventions Will Work?  

  3. Case 1 A 53 year old African-American man presented to the emergency department with cough. A CXR was performed that revealed a 2.5 cm pulmonary nodule. A CT was immediately obtained and showed the nodule to be spiculated and not calcified. The patient was told that he might have a cancerous tumor and was referred for a follow-up appointment.

  4. Case 1 His cough resolved, so he did not keep the appointment. He returned 6 months later and had an 8cm tumor on CXR with mediastinal invasion. ***What could have been done differently?

  5. Case 2 A 67 year old smoker who had a CXR for a persisting cough after a URI was found to have a 2.1 cm lung nodule. Also has multiple blebs surrounding the nodule precluding a needle biopsy. PET CT shows the nodule is hot (18 SUV). There’s a 1.6 cm ipsilateral, hilar node on the CT that does not light up on the PET.

  6. Case 2 Other pertinent clinical data: • FEV-1 45% of predicted • Has known CAD with an LAD stent 6 months ago (no current sx) and a 50-60% RCA lesion • EF – 35 to 40% • Baseline Creatinine 2.4 ***Surgery yes or no?

  7. Proportion responding that they believe that clinically similar patients receive different care on the basis of race/ethnicity by proximity to practice (n=344)Lurie, N. et al. Circulation 2005;111:1264-1269

  8. Why Study Early Stage Lung Cancer? • Fatal Disease • Surgery only reliable chance of cure • No treatment only 6% survive five-years • A few absolute contraindications are defined • Have to have strong reasons to refuse or recommend against

  9. Administrative data reveal lower surgical rates and survival for African-Americans diagnosed with Stages I and II, non-small cell lung cancer

  10. Bach et al. Racial differences in the treatment of early stage lung cancer. N Engl J Med 1999;341:1198. 44 excess deaths per 1000 lung cancer cases due to decisions against surgery!

  11. Lathan et al. J Clin Onc 2006;24:413-418 • OR for Black patients to receive staging procedures compared to Caucasians 0.75 • OR for Black patients who were actually staged to receive surgery compared to Caucasians 0.55

  12. Fig 1. Reasons recorded in Surveillance, Epidemiology, and End Results for why surgery was not performed among patients who had undergone invasive staging Lathan, C. S. et al. J Clin Oncol; 24:413-418 2006

  13. Administrative data controlled for insurance, income, and co-morbidities. No specific reasons for treatment disparity despite near certain death within 4 years post-diagnosis

  14. Reference – Prospective Cohort Study Cykert, Dilworth-Anderson,Monroe, et al. Factors associated with decisions to undergo surgery among patients with newly diagnosed early stage lung cancer. JAMA 2010; 303:2368-2376.

  15. Methods 5 communities Pulmonary, Oncology, Thoracic Surgery, ED, and Generalist Practices Direct referral vs chest CT review protocol

  16. Inclusion Criteria > 18 years old Tissue diagnosis of non-small cell lung cancer or > 60% probability using a Bayesian Model Clinical / Radiological Stage I or II disease English Speaking

  17. Timing of Enrollment Patient informed of the diagnosis of definite or probable lung cancer Survey administered verbally by trained RA before treatment plan established

  18. The Questionnaire 106 items Including: Demographics SF-12 Mental Adjustment to Cancer Scale Trust Perceptions of provider-patient communication

  19. “Exposure to air” Perceived certainty of diagnosis Attitudes about lung cancer Dyspnea Decision participants Religiosity

  20. Chart Abstraction Timing: At least 4 months after diagnosis Surgery: Yes / No and Date PFT’s Co-Morbid Diagnoses Clinical Stage Surgical Stage

  21. Statistical Analysis Primary Outcome: Lung Cancer Surgery Within 4 Months of Diagnosis Independent variables a priori in models: - demographics - SF-12 component scores - tissue vs presumptive diagnosis - perception of diagnostic certainty - Mental Adjustment to Cancer scales - “air exposure” - trust - co-morbid conditions

  22. Variables entered after bivariate comparisons if p < 0.1 - attitudes about lung cancer - religiosity - other decision participant - perceptions of provider-patient communications

  23. Results Patients enrolled – 437 - 7 patients not Caucasian or AA - 32 with advanced cancer - 6 with benign dx - 6 with FEV-1 < 25% predicted (no surgeries below this level) 386 met entry criteria and remained eligible for lung resection surgery

  24. Results • 67 percent (N = 257) with biopsy proven diagnosis at enrollment - 62% surgical resection • 33 percent CT-defined probable disease - 64% surgical resection • 88 percent tissue diagnosis confirmed

  25. Results: Demographic Data

  26. 4 Month Surgery Rates All enrollees (N = 386) Caucasian 66%* African-American 55% *p = .05

  27. 4 Month Surgery Rates • Tissue confirmed only (N = 339) Caucasian 75%* African-American 63% *p = .03

  28. Lung Surgery Rates – Bivariate Comparisons

  29. Regression Analysis - All Patients

  30. Regression Analysis - All Patients

  31. Regression Analysis - African Americans

  32. Regression Analysis - African-Americans * The Trust Paradox

  33. Regression Analysis – White Patients

  34. Regression Analysis – White Patients • No Regular Source of Care OR 1.3, 95% CI .32 – 5.3

  35. Co-morbidities • Strand TE et al. Risk factors for 30-day mortality after resection of lung cancer and prediction of their magnitude. Thorax 2007;62:991-7. - Minimal effect of Charlson Co-morbidity Index on 30 day survival (3.8% CCI of 0, 5.8% CCI 1-2, only 6.5% of patients had CCI > 3)

  36. Co-morbidities • Battafarano et al. Impact of comorbidity on survival after surgical resection in patients with stage I non-small cell lung cancer. Journal of Thoracic and Cardiovascular Surgery 2002;123:280-7. - Average 3-year survival – no comorbidities 86% - Average 3-year survival – severe comorbidities 70% - Average 3-year survival without surgery* 10 – 15% * Bach N Engl J Med 1999; 341:1198

  37. Results • N = 386 • 66 deaths at one year • 100% follow up • AA patients 4.4 years younger than W • Average age of survivors 65.6 years; average age died 70.1 years (p = 0.002)

  38. Results *P < 0.05

  39. ---------------------------------------------------------------------------------------------------------------------------------------------------- pt_died | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- d_demomari2 | .5643592 .175378 -1.84 0.066 .3069302 1.037699 medincy1 | .8405706 .2744353 -0.53 0.595 .4432697 1.593971 d2_demoedu | 1.124134 .350837 0.37 0.708 .6097647 2.072403 d_demorace | 1.097042 .3950806 0.26 0.797 .5415986 2.222126 age50th | 3.445103 1.14981 3.71 0.000 1.791067 6.626626 dxdiabetes | 1.255789 .4429175 0.65 0.518 .629068 2.506894 dxcoronary~e | 1.121822 .3708338 0.35 0.728 .5868777 2.144374 demosex | 1.288879 .3964429 0.83 0.409 .7053315 2.355217 had_surg | .5193712 .1558765 -2.18 0.029 .2884102 .9352874 rscy | .6981523 .3100482 -0.81 0.418 .2923701 1.667122 dxhyperten~n | .5987609 .1868083 -1.64 0.100 .3248522 1.103624 comorbtotal3 | 2.785209 1.175041 2.43 0.015 1.218282 6.367485 comorbtotal1 | 1.454711 .4823543 1.13 0.258 .7595123 2.786242 ------------------------------------------------------------------------------

  40. Results • Factors associated with one-year mortality for early stage lung cancer - Age over 66 (OR 3.4, 1.8 – 6.6) - >2 comorbidities (OR 2.8, 1.2 – 6.4) - lung cancer surgery (OR 0.52, 0.29 – 0.93)

  41. Conclusions Excluding patients with PFT defined absolute contra-indications, disparities in treatment for early stage, non-small cell lung cancer remain The impact of poor communication is apparent in both White patients and African-Americans Lack of a regular source of care exacerbates the effect on African-Americans

  42. Conclusions Co-morbid conditions are markedly associated with decisions against surgery for African-American patients This impact is NOT apparent with White patients This finding suggests a systematic or implicit bias when considering higher risk African-American patients for lung cancer surgery

  43. Implicit (Unintended) Bias • Schulman et al. The effect of race and sex on physicians' recommendations for cardiac catheterization. N Engl J Med 1999;340:618-26. • Green et al. Implicit Bias among Physicians and its Prediction of Thrombolysis Decisions for Black and White Patients. Journal of General Internal Medicine 2007;22:1231-8.

  44. Possible Solutions • Know that disparities (beyond what is attributable to SES, education, and insurance) exist • Think in the context of the ideal

  45. Communication • Johnson RL et al., Patient race/ethnicity and quality of patient-physician communication during medical visits. Am J Public Health 2004;94:2084-90. • Gordon HS et al. Racial differences in doctors' information-giving and patients' participation. Cancer 2006;107:1313-20. • Williams SW, et al. Communication, Decision Making, and Cancer: What African Americans Want Physicians to Know. Journal of Palliative Medicine 2008:1221-6. (Interest on a human level person and family - appropriate language)

  46. Communication • Paasche-Orlow MK et al. Tailored education may reduce health literacy disparities in asthma self-management. Am J Respir Crit Care Med 2005;172:980-6. • Clever SL, Ford DE, Rubenstein LV, et al. Primary care patients' involvement in decision-making is associated with improvement in depression. Med Care 2006;44:398-405.

  47. Communication • Rosenzweig et al. The attitudes, communication, treatment, and support intervention to reduce breast cancer disparity. Oncol Nurse Forum 2011;38: 85-89. - Pilot delivered by AA breast cancer survivor 1. Discussion chemotherapy 2. Importance of communicating knowledge needs and distress 3. Explanation of path results and rx plan 4. Survivor video - (N = 24) % total dose chemo received / prescribed 94% vs. 74%

  48. Intervention Design • Provider education: Lung cancer disparity data and local surgical and co-morbidity data by race • Co-morbidity checklist with individual patients • Real time registry with warning indicators • Provider receives race-specific data feedback • Super-navigator – Enhanced communication; dropout interventions (stratify by low health literacy)

More Related