Male Obesity and Semen Analysis Parameters

Male Obesity and Semen Analysis Parameters
By:Joseph Petty, MD
Samuel Prien, PhD
Amantia Kennedy, MSIV
Sami Jabara, MD

Background: Obesity

* Obesity is a growing problem.
* The Behavioral Risk Factor Surveillance System, in conjunction with the CDC, conducted a national survey and found that in 2000, the prevalence of obesity (BMI >30 kg/m2) was 19.8%, a 61% increase since 1991.
* Obesity affects female and male fertility.
* In a study comparing IVF success rates and female obesity, it was shown that a 0.1 unit increase in waist-hip ratio led to a 30% decrease in probability of conception per cycle 2.
* In couples complaining of infertility, male factor plays a role in up to 40% of cases.

Background: Semen Parameters
* What parameters best predict fertility?
* National Cooperative Reproductive Medicine Network: 765 infertile couples (no conception after 12 months), and 696 fertile couples
* greatest discriminatory power was in the percentage of sperm with normal morphologic features.

Hypothesis
* Since there is an observed correlation between obesity and male factor infertility, our hypothesis is that an increased BMI is associated with higher rate of abnormal semen parameters, especially sperm morphology.

Recent Studies
* Danish study by Jensen et al. enrolled 1,558 young men (mean 19 years old) when they presented for their compulsory physical exam as part of their country’s military drafting system.
* The authors showed decreased sperm counts and concentration (39 million/mL vs. 46million/mL) in those with an elevated BMI (>25kg/m2). They did not, however, observe a difference in morphology.
* Hormonal differences
* Kort et al. looked at semen analysis results in 520 men
* grouped according to their BMI, and measured the average normal-motile-sperm count (NMS = volume x concentration x %motility x %morphology)
* Kort concluded that men with high BMI values (>25) present with few normal-motile sperm cells
* Hammoud et al., showed a increased incidence of oligospermia and increased BMI and also showed decreased levels of progressively motile sperm
* Considered each parameter separately.

Sexual function
* Agricultural study: The association between BMI and infertility was similar for older and younger men, disproving the theory that erectile dysfunction in older men is a significant factor.
* Hammoud et al., though primarily concerned with hormones, looked at erectile dysfunction directly and showed that there was no correlation with increases in BMI
* Nguyen et al., effect of BMI is essentially unchanged regardless of coital frequency, suggesting that decreased libido in overweight men is not a significant factor

Hormonal Profile
* Danish study, observed decreased FHS and inhibin B levels in the obese.
* Pauli et al., observed with increases in BMI a decreased total T, decreased SHBG, increased estrogen and decreased FSH and inhibin B.
* Inhibin B, cited for its usefulness as a novel marker for spermatogenesis and its role in pituitary gonadotropin regulation.
* Pauli: no correlation of BMI or skinfold thickness with semen analysis parameters, though it was observed that men with proven paternity versus those without had lower BMI.

Interventions: Gastric Bypass
* One case series of 6 male patients after bariatric surgery showed secondary azoospermia with complete spermatogenic arrest.
* none of the subjects had a semen analysis before the bariatric surgery, but all had fathered a pregnancy previously
* malabsorption of nutrients
* Hammoud et al., part of Utah Obesity Study
* effect of the gastric bypass surgery on sex steroids and sexual function
* Cohort of 64 severely obese men
* Along with a significant decrease in BMI, they found decreased levels of estradiol, and increases in total and free testosterone along with a reported improvement in quality of sexual function.
* Semen analysis parameters were not considered in this study

Study Design
* Retrospective chart review for all couples and individual patients presenting for an infertility consultation and evaluation at the Texas Tech Physicians Center for Fertility and Reproductive Surgery from September 2005 through January 2008.
* Intake questionnaire: demographic, medical, surgical and fertility history.

Questionnaire
* Previous pregnancies fathered: current or previous partner
* Psychiatric disorders included any degree of depression, bipolar disorder or any other psychiatric disorder requiring medical therapy.
* Tobacco and alcohol users: whether they admitted to light, moderate, or heavy use, patient underreporting.
* Chemical exposures: contact with pesticides, herbicides, and heavy metals.
* Sexual dysfunction: mainly erectile dysfunction and decreased libido.
* Genitourinary anomalies: hypospadias, varicocele, genitourinary surgery, testicular torsion or inguinal hernia or trauma
* Other medical problems included mainly diabetes, hypertension, thyroid disease, autoimmune disease, and cancer.
* Patients grouped according to their BMI as normal (20-24 kg/m2, N = 24), overweight (25-30 kg/m2, N = 43), or obese (>30 kg/m2, N = 45), as standardized by the World Health Organization
* Semen analysis parameters: morphology, volume, concentration, percent motility, and presence of absence of agglutination, in accordance with World Health Organization (WHO) guidelines
* SPSS statistical software was used to run analysis of variance (ANOVA) and post-hoc Tukey HSD tests between the groups. A p-value <0.05 was considered statistically significant.

Exclusion Criteria
* questionnaire was missing or if they had an otherwise incomplete chart.
* missing vital statistics (i.e. height and weight),
* 235 total charts reviewed,
o 60 no semen analysis or outside lab.
o 63 patients had either missing vital statistics or a missing questionnaire
o This left a total of 112 patients with valid data to be considered.


Results
* The BMI groups were statistically similar as far as demographic characteristics and confounding variables
* There was no statistically significant difference between the semen parameters of all three BMI groups.
* slight trend towards a decreasing sperm concentration with increases in BMI

Conclusion
* In this study, overweight and obese men did not have an increased rate of teratozoospermia, asthenospermia, or oligospermia.

Discussion
* Inconsistencies
* Small sample size
* Kort and data interpretation
* Change the normal hormonal milieu, addressed by Jensen study.
* Sertoli cell function, increased aromatase, role of leptin
* Aggerholm study: altered hormones not correlated with semen abnormalities in overweight men (25.1-30.0 kg/m2), slightly decreased sperm concentration in overweight but not in obese


Future Studies
* What affects morphology specifically?
o Hormones
o Result of secondary disease, i.e.. Diabetes
o Genetic mutations
o Weight loss surgery and other interventions
* Overall, there is no doubt that increases in BMI have a detrimental effect on male fertility, but a satisfactory explanation of the mechanism for this phenomenon has yet to be given.

References
Male Obesity and Semen Analysis Parameters

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Management of Radiation Accident victim

Physician and Hospital Responses to Radiological Incidents
By: Robert E Henkin, MD, FACNP, FACR
Professor of Radiology
Director, Nuclear Medicine

Robert H. Wagner, MD, MSMIS
Associate Professor of Radiology
Section on Nuclear Medicine/Department of Radiology
Loyola University
Maywood, IL

Experience of Authors

* Dr Wagner trained at Loyola and the DOE in Oak Ridge - Radiation Emergency Assistance Center/Training Site (REAC/TS)
* Drs Wagner and Henkin co-wrote the original manual for hospital management that was used by the State of Illinois
* Dr Wagner is has been consultant for Radiation Management Consultants since 1990 and trains and drills approximately 5 hospitals/year until 1998. Developed the plan for radiation accidents at Loyola

* Dr Henkin is a member of the Radiation Information Network of the American College of Nuclear Physicians
* Drs Wagner and Henkin are Board Certified by ABNM

Radiation and Terrorism
* Public perceptions of radiation
* The good news and the bad news
* Terrorism scenarios
* Types of radiation injuries
* Hospital response to radiation incidents

The Public Perceptions
The Bad News
* Almost nothing creates more terror than radiation
o It’s invisible to touch, taste, and smell
o Most people have unrealistic ideas about radiation
o Most physicians don’t even understand it
* The objective of the terrorist is as much or more panic than it is physical harm

The Good News

* Nuclear Medicine and Radiation Therapy professionals are well trained in the fundamentals of radiation
* Respect radiation, but do not fear it
* Understand what radiation can and cannot do
* There have been industrial radiation accidents that we have learned much from
* It is easily detected in contrast to biological and chemical agents

What Can We Expect?
* Radiological/Nuclear Terrorism
o A true nuclear detonation
o A failed nuclear detonation
o Radiation dispersal device
* Power Plant attacks

A Nuclear Detonation
* Least likely scenario (fortunately)
* Most likely from a stolen nuclear weapon
* Results would be devastating, both psychologically and in terms of damage

The Unthinkable
* Effects of a 1 megaton detonation in Chicago
o 30% of all hospitals destroyed in 50 mile radius
o Transportation and infrastructure compromised
o Emergency vehicles and professionals unable to respond
o Walking wounded with burns may have been fatally irradiated – unknown effects for days to weeks

Radiological Devices
* Not a “nuclear explosion”
* Consists of a bomb designed to disperse radioactive materials in air and water
o Designed to create panic
o Difficult to clean up, material spreads
o Biological effects may take years to appear
* “A Dirty War” HBO/BBC Films 2005

Failed Nuclear Detonation
* Most likely from an improvised nuclear device (IND)
* Beyond the scope of an individual terrorist – would need 10-15 people
* Greatest barrier is availability of weapons grade material
* Would create a critical mass or explosion, but not the same degree as a true nuclear detonation.
* Nuclear material needs to stay in contact for a longer period of time to allow flux to form

Radiological Dispersal Device
* The most likely scenario
* Simply a bomb loaded with radioactive materials
* Uses stolen hospital or industrial materials
* Acute effects are limited to psychological and traumatic injury
* Long term effects would be on contamination of large areas
* Huge expense for cleanup

Chernobyl Comparison
Co-60 food irradiation pencil in a RDD
Radiation Levels
* Inner ring – same as permanently closed around Chernobyl
* Middle ring – same as permanently controlled area around Chernobyl
* Outer ring – same as periodically controlled zone around Chernobyl

Cancer Deaths
Co-60 food irradiation pencil in a RDD

Increase risk of cancer
* Inner ring – 1 per 100 people
* Middle ring – 1 per 1,000 people
* Outer ring – 1 per 10,000 people

What do I Need to Know?
* Fundamental Radiobiology
o Radiation effects are delayed
o Burns if you see them are chemical or thermal in origin.
o Dose limits
* Key personnel
* Contamination control
* Focus on the medical problems

1. Radiation - Fundamentals
* Types of Radiation
* All radiation is part of the electromagnetic spectrum
* This spectrum ranges from infrared through radio/TV transmission and beyond
* Ranges of common exposures

Radiation - Definition
* Energy that is transferred through space
* Examples
o Microwaves
o Radio waves
o Visible Light
o Nuclear radiation (Alpha, Beta, Gamma)
o X-Radiation

Effectiveness of a Lead Apron
Isotope
Percent Stopped
Don’t wear one during an accident!
Measurement Units
* Roentgen – radiation dose measured in air
* Radiation Absorbed Dose (RAD) – a pseudo biologic unit
* Gray – 100 RADS
* Radiation Effective Dose Man (REM) – a biologically corrected dose
* Millrem - .001 REM

We Live in Radioactive World
* Naturally occurring radioactive elements abound
* Cosmic radiation
* Man-made radiation accounts for less than 1% of total radiation
* Average human dose 150 to 170 mR/year
* Dose varies by geographic location

Low Level Radiation 500 - 5,000 mR
High Level Radiation 5- 50 R
Decrease In Sperm Count (transient)
High Level Radiation 500- 5,000 R
LD 50/60 (Estimated With Intensive Support - Possible BMT)
Neurological syndromes
Typical Therapy for Cancer (Divided Doses)
Contamination In Perspective

Radiation Injuries
* Dependent on dose
o Non-Stochastic effects (Dose related)
+ Decrease in sperm count – 15 R
+ Hematological effects – 150 R
+ Gastrointestinal effects, epilation – 300 R
+ CNS effects – 1000 R
o Stochastic Effects (Non-dose related)
+ Increase in cancer risk
+ Genetic abnormalities
Burns From Radiation
* Generally do not appear immediately
* Healing is extremely poor
* Not likely to be seen in the acute setting

2. Introduction to Radiobiology
* Mechanism of Cellular Injury
* Comparison of Tissue Sensitivities
* Dose Effect Relationships
* Genetic Effects
* Carcinogenic Effects
* Embryonic and Fetal Effects
* How to Limit Exposure
Mechanism of Cellular Injury
DNA STRAND
Biological Effects of Radiation Depend on:
* Total Dose Received
* Rate of Exposure
* Total or Partial Body
Radiation In Perspective
Genetic Effects
Radiation In Perspective
Carcinogenic Effects
Embryonic and Fetal Effects
Methods of Decreasing Exposure to Staff

* Time – linear relationship
* Distance – geometric relationship
* Shielding – half value layers.....

What’s My Role?

* Learn the institutional protocols
* Do not wait for the disaster to train
* Know who and where your resources are
* Do not contribute to panic with uninformed statements
* Refer questions to the scene commanders

Management of Radiation Accident victim

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Clinical Trials

Medical Epidemiology Clinical Trials

A clinical trial is
* A cohort study
* A prospective study
* An interventional study
* An experiment
* A controlled study

The Structure of a Clinical Trial
Various Aspects Are Standardized and Protocol-based
* Subject selection (who are these people?!)
* Subject assignment
* H & P data
* Therapeutic intervention
* Lab calibration
* Outcome evaluation

Subject Selection
* Adequate number of subjects
* Adequate number of expected endpoints
* Easy to follow-up
* Willing to participate (give consent)
* Eligibility (criteria)
* Efficacy Versus Effectiveness
* Internal Validity (validity) versus External Validity (generalizability)

Phases
* Phase I: find toxic dose
* Phase II: no controls
* Phase III: RCT
* Phase IV: Post marketing?

Types of Control Groups
* Historical
* Contemporaneous
* Concurrent
* Randomized

Allocating Treatment
* Complete (Simple) randomization
* Restricted randomization

Complete Randomization
* Patients assigned by Identical chance process (but not necessarily in equal numbers)
* Mechanics
* Insures process fairness
* Does not insure balance, especially in small studies.Therefore, may still need statistical adjustment

Randomization
* The only way to deal with unknown confounders.

Philosophy of Randomization
* Why are randomized trials not “epidemiologic” studies?
* Why randomization is so special?
* Has nothing to do with sampling bias.
* Randomization (random allocation) versus random sample.
* Does NOT deal with “chance” as a possible explanation of the difference. To the contrary.
* Can be used to create groups of unequal size.
* Baseline characteristics (table 1).

Allocation Concealment
* Define.
* Why do we need it?
* How is it done?
* Buzz words
* Versus blinding

Buzz Words
* Central (phone) randomization
* Sequentially numbered, opaque, sealed envelopes
* Sealed envelopes from a closed bag
* Numbered or coded bottles or containers

Restricted Randomization
* Stratification
* Blocking (Permuted Block Design)
* Stratified Blocking

Stratified Randomization
* Why

Scheme of stratified randomization
Blocking
* Why?
* Ensures close balance of the numbers in each group at all times during trial.
* How is it done?
* More importantly when stratified.
* Problem If block size is discovered.
* Remedy: more blinding, varying block size, larger blocks.
* Basic, Randomized (random-sized), Stratified

Problems With Concurrent Controls

Use your imagination
Examples
Problems With Contemporaneous Controls
* Regional population differences.
* Regional practice differences.
* Diagnostic variations.
* Referral pattern biases.
* Variations in data collections.

Problems With Historical Controls
* A lot more

Why Do Controls in a Randomized Trial Do So Well ?!
* Volunteerism
* Eligibility
* Placebo effect
* Hawthorne effect
* Regression towards the mean

Placebo Effect
* Placebo can do just about anything (prolong life, cure cancer).
* Improve athletic performance
* Lower T4 count
* Placebo can do just about anything (prolong life, cure cancer).
* Placebo can also cause side effects (nocebo, Wile E Coyote effect).
* Placebo effect is very useful in medicine but in epidemiology it causes problems, so we try to equalize it between the 2 groups.
* We use placebo for other benefits.

Hawthorne Effect
* Hawthorne works of the Western Electric Co. Chicago, IL

Regression Towards the Mean
Course Evaluation Question
Explains difficult material:
* Strongly agree
* Agree
* Neutral
* Disagree
* Strongly disagree
* What difficult material ?

Regression Towards the Mean
Explains difficult material
ATTENTION
CAUTION
DIFFICULT MATERIAL AHEAD!

Regression Towards the Mean

* Example
* Individuals with initially abnormal results tend on average to have more normal (closer to the mean) results later.
* Lab tests, BP etc.
* Recheck before randomization. Run-in period.
* Sophomore slump, medical school, Airforce landing feedback, most dangerous intersections.

Quicken Loans
* Rates this low seldom stay around long and tend to go up quickly and without warning

Why Does Prognosis Improve Over Time ?
1. Initial reports come from referral centers..
2. Publicity
3. Physicians’ awareness
4. Development of a Diagnostic Test
* Allows diagnosis of atypical cases.
* Is an incentive for physicians. It’s more challenging to diagnose difficult cases.
* Physicians with zero diagnostic skill can now diagnose this disease.
* Allows diagnosis of non-cases.
* Allows population based studies.
5. Publicity that a disease is very common relieves clinician from worrying that they may be overdiagnosing it.
6. Placebo effect increases over time. Why?

7. Safer treatment (laparoscopic cholecystectomy) lowers the threshold for doing surgery. So patients having surgery are not as sick as before.

Stage Migration Bias
Will Rogers Effect
8.Improved staging tests cause an apparent improvement of prognosis in every stage.
Stage Migration Bias Will Rogers Effect

“BEFORE-AFTER” STUDY
Mortality by severity level
Severity distribution
Mortality by severity level
Will Rogers Effect
* When subjects with the most severe disease in each stratum are moved to the next (more severe) stratum - for whatever reason - this will cause an apparent improvement of prognosis in every stage.
* Common.
Exclusions
Exclusion Criteria
* Excluded patients are “ineligible”. So, Why the separate category?
* More informative
* Usually very large number.
* Usually underestimates. Real number even bigger. Why?

Exclusion Criteria
What to watch for
* Patient preference
* Clinician preference
* No reason given

Drop ins and Drop outs
* Define.
* Typical case
* Other

Subjects who drop out of study or change treatment. But available for outcome assessment.
* Intention to treat analysis
* Once randomized always analyzed
* Why ?

1. Change in therapy may be related to outcome or eligibility
2. To get the full benefit of randomization
3. Effectiveness versus efficacy
Five-Year Mortality in Coronary Drug Project
A COHORT STUDY OF RECURRENT MI BY PARTICIPATION IN
A GRADUATED EXERCISE PROGRAM FOLLOWING INTITIAL MI

RECURRENT MI
YES NO TOTAL
PARTICIPATION IN GRADUATED EXERCISE PROGRAM

A RANDOMIZED CLINICAL TRIAL OF ENDURANCE TRAINING FOR PREVENTION OF RECURRENT MI
More on “Intention to Treat”
* Always analyze the results of the subjects according to the group they were randomized to. No exclusions.
* Even if they received no intervention.
* Even if they didn’t have the disease (example).
* The philosophy of “Intention to Treat” analysis
* Addresses the ultimate (and only) question for the clinician: Does prescribing treatment make a difference?
* LDL targets?!

Alternatives to “Intention to Treat” Analysis. (PROBLEMATIC)
* “Per Protocol” analysis.
How is it done?
Problems.
* “As Treated” analysis.
How?
Problems.

“Per Protocol” analysis.
* Censoring data after subjects become non-adherent
* Preserves randomization
* Stops counting events (when? “Carry-over” effect)
* Reduced power

“As Treated” analysis
* Change the treatment arm of the subject as he/she changes exposure
* The follow-up time and the events will be assigned to current exposure
* Retain all events.
* Randomization violated.
* Have to assign “lag-time” (latency) and Carry-over time.

Loss to follow up
Differential vs. Random
+ Compare their baseline variables with the rest of the subjects.
+ Chase a subgroup.
+ Worst case scenario

Objectives of Subgroup Analysis
* Support the main finding
* Check the consistency of main finding
* Address specific concerns re efficacy or safety in specific subgroup

It may also generate hypotheses for future studies. But that is not a reason to do it.

Inappropriate Uses of Subgroup Analysis
* Rescue a negative trial
* Rescue a harmful trial
* Data dredging: find interesting results without a prespecified plan or hypothesis

To Avoid Inappropriate Uses of Subgroup Analysis
* Prespecify analysis plan.
* Prespecify hypotheses to be tested based on prior evidence.
* Plan adequate power in the subgroups
* Avoid the previous pitfalls.

Problems with Subgroup Analysis
* Low power
* Multiplicity
* Test for interaction
* Comparability of the treatment groups maybe compromised
* Over-interpretation

Blinding
* PATIENTS Single blind.
* CLINICAL THERAPISTS usually double blind.
* Double Dummy
* CLINICAL EVALUATORS. Have to specify.
* Subjective vs. objective assessment

DSMB
* Data and Safety Monitoring Board
* Have duty toward:
* Current study participants (ongoing treatment)
* Future participants.
* Enough evidence to change practice
* Enough evidence to withstand criticism. (Unable to randomize afterward).

Multiple looks
* Alpha spending
DSMB
* Data Safety Monitoring Board
* Early Termination rules
* O’Brien-Fleming
* Early vs. late
* Benefit vs. harm (blinding?)
* Multiplicity
* Rules. Scenarios.
CLINICAL TRIALS JARGON
* Consecutive patients (versus a random sample)
* Baseline characteristics of patients (to see if randomization worked)
* Number of subjects and average duration of follow-up
(versus patient years)
* Interim analysis, problems
* Cumulative incidence (versus incidence density)
* Relative risk (Odds Ratio, or Hazard Ratio) (hopefully <1)is:
rate of outcome in a drug group
rate of outcome in a placebo group
* Relative risk reduction (similar to attributable risk %). But here it is 1-RR.
* Absolute difference in risk (ADR)= risk in control group – risk in intervention group (similar to AR) very important, sometimes not reported
* Relative risk reduction versus absolute difference in risk
* Number needed to treat NNT =1/ADR very useful (remember time)

Descriptions of “Trials”
* 34% relative decrease in the incidence of MI. The decrease is statistically significant. The 95% CI ranges from 55% relative decrease to a 9% relative decrease.

* 1.4% decrease in …. (2.5% versus 3.9%). The decrease is statistically significant. The 95% confidence interval ranges from a 2.5% decrease to a ..

* 77 persons must be treated for an average of just over 5 years to prevent 1 MI.

Ratings of Trials
(-5=harmful,+5=very effective)

Medical Epidemiology Clinical Trials.ppt

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